Exploring Olfactory Bulb Volume and Its Shrinkage in Aging and Neurodegeneration: A Systematic Review and Meta-Analysis of Observational Studies

Abstract

Background

The olfactory bulb (OB) plays a crucial role in processing smells and has significant neuroplasticity throughout life. Age-related changes in OB volume (OBV) are associated with declining olfactory function, potentially impacting quality of life and serving as an early marker of neurodegenerative diseases. This study conducted a meta-analysis to assess OBV changes across diverse age groups in healthy individuals, explored its association with olfactory function, and further examined OB atrophy in Parkinson's disease (PD) and Alzheimer's disease (AD).

Materials and Methods

A systematic review and meta-analysis were conducted following PRISMA guidelines. Studies evaluating OBV through MRI in healthy individuals and patients with PD or AD were included. Data were extracted on age, sex, olfactory function, and OBV. Meta-regression was performed to assess the correlation between OBV and age, while subgroup analyses examined the effects of sex and laterality.

Results

Twenty-nine studies were analyzed, including 12 on healthy individuals, 7 on AD, and 11 on PD. The pooled mean OBV was 54.5 mm³ (95% CI, 42.03–66.98) for the right OB and 55.56 mm³ (95% CI, 42.96–68.15) for the left OB, with no significant sex or laterality differences. OBV showed a moderate negative correlation with age (r = −0.53 to −0.59, p < 0.05), suggesting progressive atrophy with aging. Olfactory function, assessed through the Threshold, Differentiation, and Identification (TDI) and the University of Pennsylvania Smell Identification Test (UPSIT) scores, was also moderately correlated with OBV (r = 0.48, p < 0.01). In neurodegenerative diseases, OBV reduction was greater, with shrinkage of 0.9 to 0.93 SD in PD and 1 to 1.05 SD in AD, primarily attributed to pathological degeneration.

Conclusion

Age-related OBV reduction is a normal physiological process with a moderate impact on olfactory function. While neurodegenerative diseases exacerbate OB atrophy, at least 40% of OB shrinkage observed in PD appears to be age-related. OBV could serve as a potential biomarker for aging and early neurodegeneration.

 

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Keywords

olfactory bulb - olfactory dysfunction - aging - magnetic resonance imaging - neurodegenerative diseases - Parkinson's disease - Alzheimer's disease

Introduction

The olfactory bulb (OB) is situated above the cribriform plate on both sides of the crista galli in the anterior cranial fossa. This structure is circularly laminated and has olfactory glial cells and olfactory glomeruli. The axons from olfactory neurons in the nasal cavity run in the outer plexiform layer and form synapses with mitral, tufted, and periglomerular cells. The myelinated axons of mitral cells run in the inner plexiform layers, which contain recurrent and deep collaterals of mitral, tufted cells. Axons of mitral cells form granule cell layers, which contain a majority of granule cells and their processes.[1] This unique organization forms in the first relay center of the olfactory pathway, which has no connection to the thalamus, runs as the olfactory stria, and ends in the entorhinal cortex and the amygdala. The OB plays a crucial role in processing smells and uses its connections to the limbic system and cerebral cortex to associate smells with feelings and memories.[2] Developmentally, the olfactory primordia are observed no earlier than day 41 of the embryo. Marlier et al showed preference for odor in the prenatal period in the last trimester of pregnancy.[3] Olfactory processing ability undergoes frequent changes in children and adults due to the continuous synaptogenesis and plasticity of stem cells from the subventricular zone. The OB undergoes continuous renewal and is populated with new granular and periglomerular cells via the rostral migratory stream, which invades the glomerular and granular cell layers and becomes periglomerular and granular cells.[4] Schneider and Floemer documented OB and exhibited a similar maturation parallel to the cerebral white matter maturation during the postnatal period until the end of the 2nd year to achieve adult characteristics.[5] Increased OB volume (OBV) and improved olfactory function were found to be positively correlated in children aged 1 to 17 years due to rapid neurogenesis.[4] Neurogenesis declines with age, and many people older than 65 years may suffer from partial (hyposmia) or total (anosmia) loss of smell despite this lifetime neuroplasticity.[6] [7] Along with aging, neurodegenerative illnesses like Parkinson's disease (PD) and Alzheimer's disease (AD) are associated with olfactory dysfunction (OD). Although obvious symptoms are generally used to diagnose these conditions, research indicates that the pathological onset of OD happens years earlier. Prior to cognitive or motor problems, olfactory impairments frequently rank among the initial symptoms.[8] [9] [10] [11] Research suggests that olfactory tests, such as the University of Pennsylvania Smell Identification Test (UPSIT), can function as early biomarkers for these illnesses when paired with other diagnostic instruments. Olfactory testing has fascinated many researchers, given its potential as an affordable, noninvasive method for early neurodegenerative disease screening. The structural changes in OB usually precede OD.

In magnetic resonance imaging (MRI), OB is a bilateral, small, oval structure located in the anterior cerebral fossa with intermediate signal strength on T1-weighted images and hyperintense on T2-weighted images ([Fig. 1]). T1-weighted MPRAGE is used to assess volumetrics. Owing to ongoing advancements, volumetric analyses based on MRI provide a perfect tool for accurately assessing OBV, which appears to be linked to OB functional state.[6] [12] OBV has a moderate-to-strong correlation with olfactory function in terms of the UPSIT or the Threshold, Differentiation, and Identification (TDI) score of odor. Though OD is a serious issue, it often goes unrecognized. Roughly 75% of individuals with anosmia or OD are unaware of their condition until testing confirms it.[13] The routine evaluation of olfactory function in the elderly is essential, specifically because OD is not only a sign of serious health ailments but also leads to higher mortality in fire or similar household accidents. OD is due to neurodegenerative changes in OB as well as olfactory pathways, either age-associated or pathological. The changes are observed in nasal pathologies as bottom-up mechanisms, such as a reduction in the number of receptors, diminishing epithelium, changes in olfactory sensory cells, and substitution of olfactory with respiratory epithelia following exposure to airborne infection, air pollution, cigarette smoke, and xenobiotics. The age-associated degeneration in OB could be observed due to frequent insult of nasal pathologies or top-down neurodegeneration of the olfactory center due to glial and neuronal loss following amyloid deposition, along with hereditary variables, which could have an impact on olfactory function throughout one's life.[14]

Fig. 1 Olfactory bulb in T2-weighted MRI image marked by down arrow head (from teaching image repository).

Human olfactory impairment is linked to age-related structural alterations in the brain and OB. As people age, their olfactory function deteriorates, and the percentage of adults aged 65 to 80 years who experience clinically significant loss of olfaction or anosmia rises from 50 to 80%.[15] [16] OBV shrinkage was observed in the elderly subjects. Similar shrinkage in AD and Parkinsonism was also observed either due to aging or pathological neurodegeneration or both. The present meta-analysis was conducted to assess the mean OBV in healthy individuals and patients with cognitive impairment and age-related degeneration. The pooled mean OBV and its correlation with mean age are computed. The age-related shrinkage of OBV is evaluated. The effect of other predictors (e.g., sex, laterality, and duration of disease) is discussed. This study critically assesses the potential of OBV as an early disease biomarker as well as its role in neurodegeneration and aging.

 

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Materials and Methods

The present study was conducted as per the protocol of the PRISMA guidelines. The present systematic review was prospectively registered with the Open Science Framework (OSF) registries, OSF Registration: https://doi.org/10.17605/OSF.IO/NF43U. The research question and selection criteria of this study were formulated by the PICOS model ([Table 1]).

Table 1 Inclusion and exclusion criteria

Inclusion criteria	Exclusion criteria
▪ Population: all age groups ▪ Intervention/Exposure: ageing and cognitive impairment disorders (Parkinsonism and Alzheimer's disease) ▪ Control: healthy subjects ▪ Outcome: olfactory bulb volume ▪ Studies: cross-sectional, case–control or cohort MRI-based studies	• Animal studies • MRI <1.5T • Intraclass correlation coefficient <0.7 • Review and commentaries • Case report or series

Search strategy: The keywords included were MeSH terms, EMTREE terms, and common synonyms. These keywords (“Olfactory,” “Bulb,” “Volume,” “Health,” “Neurodegenerative,” “Aging,” “Age Changes,” “Cognitive,” “Impairment,” “Dysfunction,” “Disorder,” “Dementia,” “Alzheimer,” “Parkinson” “Human”) were utilized along with Boolean operators: or, and, not. The search string was prepared with various combinations of keywords and operators. Three common databases were utilized for the search strategy, i.e., PubMed, Scopus, and Google Scholar.

Screening of Literature

Duplicate studies were eliminated in Zotero after importing the retrieved studies from PubMed, Embase, and Google Scholar into the Zotero reference manager. The remaining citations were evaluated by two authors using the selection criteria. The full-text version was also acquired to evaluate the study more thoroughly, if it was unclear from the title or abstract what the study was about. Disagreements over the selection of any studies were settled by consulting the third author. Theses and abstracts from conferences were also considered gray literature. When insufficient data were discovered, the investigators of the research were approached, if possible.

 

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Data Extraction

Two writers independently selected records together with information from the eligible research. A standardized data extraction form was used to gather baseline data, including published year, study nation, criteria for diagnosis, sample number, sex, average age, olfactory functional score, MRI magnetic field intensity, and the volume of the left and right OB. To settle differences, the three authors came to an agreement.

 

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Study Quality Assessment

For observational studies, two authors independently evaluated each included study using the Newcastle-Ottawa Score (NOS).[17] Subject selection, the impact of aging and diseases, confounding variables, and comparability were all assessed in these studies. Every component was given a rating, with a higher score denoting higher quality. Every item numbered in the selection and exposure categories would receive a maximum score of one star, while the comparability category might receive up to two stars. A rating of six or more indicates a high-quality study.

 

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Statistical Analysis

The data were extracted from the available studies and reported as means with standard deviations or, when necessary, derived from medians, ranges, or interquartile ranges through mean mean-variance method.[18] Volumetric estimations of the olfactory bulb were conducted using either 1.5T or 3T MRI, with variations in imaging protocols across studies. Olfactory function was assessed using multiple standardized tests, including the UPSIT, Sniffin' Sticks, the Brief Smell Identification Test (B-SIT), the San Diego Odor Identification Test (SDOIT), and the Barcelona Smell Test-24 (BAST-24), along with the TDI score.[12]

Given the methodological differences among studies, effect sizes were calculated using mean difference (MD) or standardized mean differences (SMD) to eliminate the effects of variations in measurement scales and units. In this context, standard deviation (SD) served as the unit of effect size, minimizing potential biases arising from ethnic differences and imaging protocols. The sample size and standard error (SE) were used to compute 95% confidence intervals (CIs).

To evaluate heterogeneity among studies, both the Cochrane Q test and the Higgins I ² index were applied. Fixed-effects analysis was used when the Higgins I ² index showed modest heterogeneity (<50%). On the other hand, a random-effects model was employed when the heterogeneity exceeded 50%. Sensitivity analysis was used to find possible outliers. Furthermore, if there were enough studies available for each covariate, subgroup analyses and meta-regression were performed to investigate the origins of heterogeneity. In addition to funnel plots, Begg's and Egger's regression models were used to evaluate publication bias if there was funnel plot asymmetry.

 

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Results

Study Characteristics and Quality Assessment

Twenty-nine studies[1] [4] [8] [9] [10] [11] [14] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] fulfilled the requirements for inclusion in this systematic review ([Fig. 2]). These studies, published between 2005 and 2023, included 12 studies on healthy individuals, 7 on AD, and 11 on Parkinsonism. The baseline characteristics and quality assessment of these studies are summarized in [Table 2]. The quality of the studies, as measured using the Newcastle-Ottawa Scale (NOS), ranged from six to eight, indicating generally good methodological quality ([Table 3]).

Fig. 2 PRISMA (2020) flow diagram of literature search and selection for studies on olfactory bulb volume.

Table 2 Characteristics of included studies

Author (year)	Type of study	Country and ethnicity	MRI technical parameters	Sample size	OBV
Mueller et al (2005)[19]	Pilot study	Germany	1.5T system (Magnetom Vision; Siemens, Erlangen, Germany) using the cp-head coil. OBV: by manual segmentation of the coronal slices through the OBs	11 PD/9 controls	No significant difference in OBV between PD and controls. OBV correlated significantly with overall olfactory function expressed as “TDI scores” (r = 0.19, r = 0.28, r = 0.23)
Buschhüter et al (2008)[20]	Cross-sectional	Germany	1.5T MRI system (Sonata Vision; Siemens) using the cp-head coil, OBV: AMIRA 3D visualization and modeling system (Visage Imaging, Carlsbad, USA), manual segmentation	125 healthy adults (19–79 y)	OBV correlated with olfactory function, decreased with age. Olfactory function expressed as the TDI score was slightly higher in men (left: 36.8; right: 35.9) compared to the TDI scores of women (left: 34.5; right: 34.2)
Thomann et al (2009)[11]	Cross-sectional	University of Heidelberg, Germany	1.5T MRI, T1-weighted 3D MP-RAGE, 126 slices, 256 × 256 matrix, voxel size 0.98 × 0.98 × 1.8 mm, TR = 10 ms, TE = 4 ms OBV: manual segmentation function of BRAINS2 software	21 early AD patients, 21 healthy controls	Right: 112.85 mm3 (AD), 127.41 mm3 (control) Left: not specified, olfactory score not evaluated
Thomann* et al (2009)[21]	Cross-sectional	Germany	1.5T Magnetom Symphony MR scanner (Siemens Medical Solutions, Erlangen, Germany). OBV: manual segmentation function of BRAINS2 software	29 MCI, 27 AD/30 controls	OBV: AD (85.92 ± 8.18 mm3), MCI (90.81 ± 9.27 mm3), control (95.73 ± 9.77 mm3) Olfactory score not evaluated
Rombaux et al (2010)[14]	Case–control	Belgium	1.5T MRI system (Signa Echospeed, GEMS, Milwaukee, WI, USA), OBV: planimetric manual contouring with 2 mm slice thickness	22 olfactory loss/22 controls	Mean right, left, and total OB volumes were, respectively, 26.9, 26.5, and 57.1 mm3 for patients vs. 37.9, 36.6, and 74.5 mm3 for controls. OBV was reduced in olfactory loss compared to controls. TDI orthonasal: Patients: 14.5 (12.5–16.6) Control: 30.4 (28.3–32.5)
Hummel et al (2011)[4]	Cross-sectional	France	1.5T MRI system (Sonata; Siemens) using the cp-head coil. manual segmentation of coronal slices, OBV: manual segmentation using the AMIRA 3-D visualization and modeling system (Visage Imaging, Carlsbad, USA)	87 children and adolescents (1–17 y)	Right: 68 mm3, left: 71 mm3. Female children generally had slightly better olfactory function (smell), as indicated by a TDI score of 27.9 ± 5.8, compared to male children's TDI score of 26.9 ± 6.1. Olfactory function improved steadily with age for both genders, rising from around 18.7 (males) and 17.4 (females) at age 6–33.3 (males) and 34.6 (females) at age 17. This improvement showed a strong and statistically significant correlation with age (r = 0.76, p < 0.001)
Wang et al (2011)[22]	Cross-sectional	China	3T system (Signa VH/i Excite II 3T; GE Healthcare, Milwaukee, Wisconsin) OBV: a workstation (GE Advantage Windows 4.2) by manual segmentation of the coronal sections	29 PD/29 controls	OBV: PD (37.30 ± 10.23 mm3), control (44.87 ± 11.84 mm3) (p < 0.05). Olfactory threshold significantly higher in patients with PD than in control subjects (3.82 ±  1.25 and 0.45 ± 0.65, respectively; t = 14.59, p = 0.0001)
Brodoehl et al (2012)[8]	Cross-sectional	Germany	3.0T MR scanner (Trio; Siemens). OBV: MIPAV software package (Center for Information Technology, National Institutes of Health, Bethesda, MD)	16 PD/16 controls	OBV: PD (91.2 ± 15.72 mm3), control (131.4 ± 24.56 mm3) (p < 0.05). In the PD group, TDI exhibited an inverse correlation with age ( r = 0.62; p < 0.01) and a positive correlation with OBV (whole bulb volume: r = 0.52, p = 0.041
Hakyemez et al (2013)[23]	Case–control	Turkey	1.5T system (Achieva; Philips Healthcare, Best, the Netherlands). Volumetric measurements were performed by an experienced radiologist who was blinded to the olfactory test data by manual segmentation of coronal T2-weighted slices	28 PD/19 controls	OBV higher in PD but not statistically significant, UPSIT olfactory score UPSIT: stage 1: 15.60 ± 5.19 (9–25) Stage 2: 15.33 ± 4.52 (8–26) Control: 21.05 ± 5.08 (14–30)
Chen et al (2014)[24]	Cross-sectional	China	1.5T Phillips platform. Olfactory scanning using a 3D-TSE sequence. OBV: volume VBM analysis of olfaction-associated gray matter evident in each voxel was performed using the VBM function of the SPM8 imaging package of MatLab 7.1	20 PD, 14 MSA/12 controls	OBV: PD (55.1 ± 10.7 mm3), control (75.9 ± 8.4 mm3) (p < 0.0001) Olfactory score not evaluated
Altinayar et al (2014)[25]	Case–control	Turkey	1.5T MRI (Siemens Avanto), 3D T2-weighted, OBV: OsiriX MD Workstation, Manual Tracing	41 PD (27 TDPD, 14 NTDPD)/19 controls	OBV reduced in NTDPD, no difference in TDPD vs. controls. Butanol threshold test PD: 2.53 ± 1.73, 2.34 ± 1.38, control: 2.63 ± 1.57, 2.53 ± 1.67. Odor identification test PD: 2.17 ± 2.02, 2.48 ± 2.43, control: 3.89 ± 2.02, 4.16 ± 1.98
Servello et al. (2015)[10]	Pilot study	University of Rome, Italy	3.0T MRI scanner (Siemens Magnetom Verio, Erlangen, Germany), with 3T Matrix Head Coil. OBV: a workstation (Advantage Workstation, General Electric, Milwaukee, USA). Using a manual segmentation of T1- and T2-weighted coronal sections	AD (n = 25), MCI (n = 25), healthy elderly (n = 28)	Right: 34.92 mm3 (AD) Left: 36.90 mm3 (AD) TDI score: Control: 31.3 ± 5.9 AD: 20.0 ± 7.0
Yu et al (2015)[26]	Cross-sectional	China	1.5 T Phillips platform. Olfactory scanning using a 3D-TSE sequence. OBV: volume VBM analysis of olfaction-associated gray matter evident in each voxel was performed using the VBM function of the SPM8 imaging package of MatLab 7.1	Fifty patients with AD and 50 healthy subjects	Bilateral and average OB volumes were smaller in AD group [(29.78 ± 5.17) mm3, (30.14 ± 4.87) mm3, (30.05 ± 5.08) mm3] than in control group [(36.65 ± 4.08) mm3, (36.56 ± 4.12) mm3, (36.46 ± 4.11) mm3] (p < 0.01). Olfactory testing revealed that AD patients had higher scores than the control group (1.50 ± 0.17, 2.80 ± 0.31, p < 0.05)
Paschen et al. (2015)[27]	Cross-sectional	Germany	3T MRI (Siemens Skyra) with eight-channel SENSE head coil, OBV: manual segmentation of the OB on a workstation for diagnostic reading (IMPAX EER20 XIISU1; AGFA Health Care, Mortsel, Belgium	52 PD/31 controls	OBV: PD (42.1 mm3 right, 41.5 mm3 left), no significant difference from controls TDI score: PD-21.2 Control: 32.6 Normosmic/hyposmic/anosmic: PD: 7/35/10, Control: 23/8/0
Tanik et al. (2016)[28]	Cross-sectional	Turkey	1.5T system (Ingenia, model 7813-72, series 381, Philips Medical Systems Nederland, Tilburg, the Netherlands) with a standard quadrature head coil. OBV: double blind methods, not reported	25 PD/40 controls	OBV significantly reduced in PD (p < 0.001) Olfactory score not evaluated
Campabadal et al (2017)[29]	Case–control longitudinal	Spain	3T MRI (Siemens Trio), OBV: automated FreeSurfer stream (vs. 5.1; available at: http://surfer.nmr.harvard.edu)	25 PD/24 controls	Progressive OBV loss over 4 y, correlated with basal ganglia volume changes, UPSIT olfactory score PD: 20.6 (7.5) and 18.7 (6.4) Control: 31.3 (3.1) and 30.0 (4.7)
Chen et al. (2018)[30]	Cross-sectional	Affiliated Brain Hospital of Guangzhou Medical University, China	Philips 3.0T MRI, T1-weighted, TR = 8.2 ms, TE = 3.8 ms, TI = 1,100 ms, flip angle = 8°, 188 slices, slice thickness = 1 mm. OBV: planimetric manual contouring, and all surfaces were added	Late-life depression (n = 45), AD (n = 20), normal controls (n = 25)	OBV in AD: 27.39 ± 3.22 and in control: 37.35 ± 4.04. Olfactory score: AD: 5.8 ± 1.8 and 4.6 ± 1.8 Control: 11.8 ± 1.7 and 7.6 ± 2.5
Maghsoudi and Treimo 2019[31]	Observational study	Germany	3T MRI system (Siemens Trio) OBV: AMIRA 3D visualization and modeling system version 5.4.1(Build 006-5e11b Visage Imaging, Carlsbad, USA).	31 healthy participants (19 women, 12 men) aged 20–38	Mean left OB volume: 41.85 mm3 (SD: 18.2) Mean right OB volume: 36.23 mm3 (SD 16.4) Range (left OB): 0–78.66 mm3 Range (right OB): 0–59.22 mm3 TDI score: Female: 36.59 ± 2.42 Male: 35.83 ± 1.23
Karaoglan et al (2020)[32]	Cross-sectional	Turkey	3T MRI system (Ingenia 3.0T; Philips Healthcare, MRI-based volumetric measurements. The OBV:OSIRIX MD software (Pixmeo, Switzerland) was also calculated by manual contouring	195 children (BMI-based groups)	OBV higher in overweight/obese children, lower in morbidly obese. Olfactory score not evaluated.
Cullu et al (2020)[1]	Cross-sectional	Turkey	3T MRI (Siemens), coronal T2-weighted images, manual segmentation, OBV: workstation singo.via (Siemens, Berlin, Germany) by the Manual method	200 healthy Turkish adult population	Mean OBV: 91.17 ± 7.8 mm3, Olfactory score not evaluated.
Poessel et al (2020)[33]	Cross-sectional	Germany	3-Tesla Siemens SKYRA scanner equipped with a 20-channel head coil. OBV: multislice T2-weighted turbo spin-echo images, with TR/TE/FA = 6,630 ms/126 ms/160, acquired spatial resolution = 0.5 0.5 (in-plane), 1 mm slice thickness, 30 slices	67 adults (BMI-based groups)	OBV lower in obese individuals, negatively correlated with metabolic markers. TDI sum score 33.63, 3.90 (22.75, 40.25) Correlation with BMI r = 0.133 and OBV: r = 0.149
Sahin et al (2020)[34]	Cross-sectional	Turkey	1.5T MRI (Achieva, Philips), T2-weighted images. OBV: multiplanar reconstructions in a View 3D workstation and manual segmentation based on the contour stack principle	90 pediatric population (3–17 y)	Total OBV range: 70–197.9 mm3 Olfactory score not evaluated
Tremblay et al (2020)[35]	Cross-sectional	Canada	3T MRI (Siemens Prisma), T1-weighted, OBV: MIPAV 9.0 (NIH) manual tracing	15 PD/15 controls	OBV lower in PD than in controls (p < 0.001) Correlation between OBV and olfactory score (right: r = 0.492, p = 0.015; left: r = 0.517, p < 0.001, mean right-left volume: r = 0.538, p < 0.001)
Petekkaya et al (2020)[36]	Cross-sectional	Turkey	T1-weighted images scanned with a Philips Ingenia 1.5T MRI, OBV: IBASPM for olfactory bulb measurement, free toolbox in MATLAB for segmenting structures in MRI images (http://www.thomaskoenig.ch/Lester/ibaspm.htm)	9 AD patients, 12 healthy controls	Right: 0.85 ± 0.32 cm3 (AD), 1.21 ± 0.10 cm3 (control) Left: 0.84 ± 0.18 cm3 (AD), 1.04 ± 0.14 cm3 (control) Olfactory score not evaluated
Yildirim et al (2020)[37]	Case–control	Turkey	3T MRI (3 Tesla Magnetom MRI, Siemens). A 32-channel head coil. OBV: MPR with Syngo.Via Software (VB10B, Siemens)	106 patients + 17 controls	OBV decreased in the idiopathic and obstructive groups. Olfactory score not evaluated
Lu et al (2021)[38]	Cross-sectional	Germany	3-T MRI scanners with 64-channel head–neck coils (MAGNETOM Prisma; Siemens Healthcare), OBV: FreeSurfer software, version 6.0 (FreeSurfer)	541 general adult population (30+ y)	Right: 27.6 mm3 Left: 26.1 mm3 Olfactory score Overall: 9.8 (1.7) Women: 9.9 (1.6) Men 9.6 (1.8)
Guney et al (2022)[39]	Cross-sectional	Turkey	3T MR (Magnetom Skyra, Siemens, Germany) OBV: 3D Slicer software ver. 4.2.2-1, http://www.slicer.org)	190 pediatric population (1 mo to 18 y)	OBV increased with age, higher in males (right: 42.03 mm3, left: 42.33 mm3) Olfactory score not evaluated
Carnemolla et al (2022)[40]	Case–control	University of Sydney, Australia	3T MRI, T1-weighted, coronal orientation, 256 × 256 matrix, 200 slices, 1 mm2 in-plane resolution, slice thickness 1 mm, TE = 2.6 ms, TR = 5.8 ms OBV: manual identification of OBs was conducted using the imaging software MRIcron (https://www. mricro.com, 64-bit OSX Cocoa v1.0.20190902)	AD (n = 50), FTD subtypes (n = 119), controls (n = 55) baseline, 86 follow-up	OB volume at baseline and follow-up analyzed with 10–25% volume reduction over time Olfactory score not evaluated
Dutta et al (2023)[9]	Cross-sectional	India	3T MRI (Philips Achieva), T1/T2-weighted OBV: 3D Slicer software version 4.11.20210226	40 PD, 20 PSP, 10 MSA, 10 VP/30 controls	OBV: PD (113.3 ± 79.2 mm3), control (187.4 ± 65.0 mm3) (p = 0.003) Mean olfactory score: PD: 5.7 ± 2.5 (4–8), control 8.5 ± 0.8 (8–9)

Abbreviations: AD, Alzheimer's disease; FTD, frontotemporal dementia; OBV, olfactory bulb volume; PD, Parkinson's disease; TE, echo time; TR, repetition time; SMD, standardized mean differences; TDI, Threshold, Differentiation, and Identification; UPSIT, University of Pennsylvania Smell Identification Test.

Note: * is used to differentiate two different studies of same author.

Table 3 NOS (New-Castle Ottawa Score) quality assessment and grading of evidence based on OCEBM (Oxford Centre for Evidence-Based Medicine)

Author (year)	Type of study	Selection (0–4)	Comparability (0–2)	Outcome/Exposure (0–3)	Total score (0–9)	Quality rating	Level of evidence
Mueller et al (2005)[19]	Case–control	★★★	★	★	5/9	Moderate	Level 3
Buschhüter et al (2008)[20]	Cross-sectional	★★★	★★	★★	7/9	High	Level 4
Thomann et al (2009)[11]	Case–control	★★★★	★★	★★	8/9	Low-moderate	Level 4
Thomann* et al (2009)[21]	Case–control	★★★★	★★	★★	8/9	Low-moderate	Level 4
Rombaux et al (2010)[14]	Case–control	★★★	★★	★	6/9	Moderate	Level 3
Wang et al (2011)[22]	Case–control	★★★	★★	★★	7/9	High	Level 3
Hummel et al (2011)[4]	Cross-sectional	★★★	★★	★★	7/9	High	Level 4
Brodoehl et al (2012)[8]	Case–control	★★★	★★	★★	7/9	High	Level 3
Hakyemez et al (2013)[23]	Case–control	★★★	★	★★	6/9	Moderate	Level 3
Chen et al (2014)[24]	Case–control	★★★★	★	★★	7/9	High	Level 3
Altinayar et al (2014)[25]	Case–control	★★★	★★	★★	7/9	High	Level 3
Servello et al (2015)[10]	Pilot study	★★★	★	★★	6/9	Low-moderate	Level 4
Yu et al (2015)[26]	Cohort study	★★★	★	★★	6/9	Low-moderate	Level 4
Paschen et al (2015)[27]	Case–control	★★★	★★	★★	7/9	High	Level 3
Tanik et al (2016)[28]	Case–control	★★★★	★★	★★	8/9	High	Level 3
Campabadal et al (2017)[29]	Cohort (longitudinal)	★★★★	★★	★★★	9/9	High	Level 2
Chen et al (2018)[30]	Case–control	★★★★	★★	★★	8/9	Low-moderate	Level 4
Cullu et al (2020)[1]	Cross-sectional	★★★★	★★	★★	8/9	High	Level 4
Karaoglan et al (2020)[32]	Cross-sectional	★★★★	★★	★★	8/9	High	Level 4
Poessel et al (2020)[33]	Cross-sectional	★★★	★★	★★	7/9	High	Level 4
Sahin et al (2020)[34]	Cross-sectional	★★★	★★	★★	7/9	High	Level 4
Tremblay et al (2020)[35]	Case–control	★★★	★★	★	6/9	Moderate	Level 3
Petekkaya et al (2020)[36]	Small cohort study	★★★	★	★	5/9	Low-moderate	Level 4
Yildirim et al (2020)[37]	Case–control	★★★	★★	★	6/9	Moderate	Level 3
Lu et al (2021)[38]	Cross-sectional	★★★★	★★	★★★	9/9	High	Level 4
Guney et al (2022)[39]	Cross-sectional	★★★★	★★	★★	8/9	High	Level 4
Carnemolla et al (2022)[40]	Longitudinal cohort	★★★	★★	★★★	8/9	Moderate	Level 3
Dutta et al (2023)[9]	Case–control	★★★	★★	★★	7/9	High	Level 3

Note: * is used to differentiate two different studies of same author.

The pooled mean volumes of the right ([Fig. 3A]) and left ([Fig. 3B]) olfactory bulbs were 54.5 mm³ (95% CI: 42.03–66.98) and 55.56 mm³ (95% CI: 42.96–68.15), respectively. No significant difference was observed between the volumes of the right and left olfactory bulbs, with a standardized mean difference (SMD) of 0.47 SD (95% CI: −0.11 to 1.04, p = 0.15; [Fig. 4A]). Similarly, there was no significant gender difference in olfactory bulb volumes, with an SMD of 1.54 SD (95% CI: −0.73 to 3.80, p = 0.09; [Fig. 4B]).

Fig. 3 The pooled mean volumes of the right (A) and left (B) olfactory bulbs across studies in healthy populations. This forest plot reports the pooled mean olfactory bulb volume across included studies with data stratified by MRI strength. Random-effects models were used to account for substantial heterogeneity. Subgroup heterogeneity was high in 3T and low in 1.5T. The significant difference in mean volume between subgroups was detected (p < 0.05).

Fig. 4 Forest plot showing (A) the effect of laterality and (B) sex showing no differences. The forest reported in the standardized mean difference (SMD). The heterogeneity was minimal to low in both.

The correlation between age and olfactory bulb volume was analyzed, showing a moderate to strong correlation. The pooled correlation coefficients for the right ([Fig. 5A]) and left ([Fig. 5B]) olfactory bulb volumes with age were 0.53 (95% CI: 0.33–0.68, p = 0.03) and 0.59 (95% CI: 0.40–0.73, p < 0.01), respectively. These results suggest that age is a moderate to strong predictor of olfactory bulb size. Furthermore, the correlation between olfactory function and olfactory bulb volume was significant, with a pooled correlation coefficient of 0.48 (95% CI: 0.31–0.61, p < 0.01; [Fig. 6]), indicating a moderate relationship between olfactory function and olfactory bulb volume. Both age and olfactory function were identified as moderate predictors of olfactory bulb size.

Fig. 5 Forest plot showing pooled correlation (Pearson's r) between olfactory bulb volume and age: (A) right; (B) left. Subgroup difference between MRI protocols was insignificant, and substantial heterogeneity was observed in both.

Fig. 6 Forest plot showing pooled correlation (Pearson's r) between olfactory bulb volume and olfactory function (measured in olfactory score). TDI, Threshold, Discrimination, Identification; UPSIT: University of Pennsylvania Smell Identification Test. Heterogeneity was substantial, and the random effects model was used. Subgroup difference-based mode of olfactory score was insignificant (p = 0.62).

In neurodegenerative disorders such as Parkinsonism and AD, significant shrinkage of the olfactory bulb was observed. In Parkinsonism, the pooled shrinkage of the right ([Fig. 7A]) and left ([Fig. 7B]) olfactory bulb volumes was −0.9 SD (95% CI: −1.36 to −0.43) or −11.86 mm³ (95% CI: −18.44 to −5.28) and −0.93 SD (95% CI: −1.43 to −0.43) or −11.74 mm³ (95% CI: −17.58 to −5.89), respectively, based on 11 studies (n = 683; 370 Parkinsonism and 313 healthy control subjects). Meta-regression analysis revealed that age explained 43.3% of the shrinkage in Parkinsonism (R ² = 0.1876). Bubble plots show the effect of aging on OBV in Parkinsonism ([Fig. 8A, B]). The difference in olfactory scores explained 64% of the shrinkage in Parkinsonism (R ² = 0.410), although this may be an overestimate. The duration of Parkinsonism did not significantly contribute to the shrinkage observed.

Fig. 7 Forest plot showing the effect of Parkinsonism on olfactory bulb volume. (A) Right; (B) left. IV, inverse variance; SD, standard deviation.

Fig. 8 Bubble plot showing effect of aging on olfactory bulb volume in Parkinsonism. (A) Right; (B) left. SMD, standardized mean difference.

In AD, the pooled shrinkage of the right ([Fig. 9A]) and left ([Fig. 9B]) olfactory bulbs was −1.05 SD (95% CI: −1.69 to −0.40) or −7.96 mm³ (95% CI: −12.35 to −3.58), and −1.0 SD (95% CI: −1.63 to −0.37) or −7.51 mm³ (95% CI: −10.86 to −4.16), respectively, based on seven studies (n = 478; 232 AD subjects and 246 healthy control subjects). However, due to the limited reporting of age distribution (available in only three studies), meta-regression was not robustly performed in this outcome.

Fig. 9 Forest plot showing the effect of Alzheimer's disease on olfactory bulb volume. (A) Right; (B) left. IV, inverse variance; SD, standard deviation.

 

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Publication Bias

Visual inspection of the funnel plot ([Supplementary Fig. S1] [available in the online version only]) for the healthy dataset showed a symmetric distribution of study effects with a dense central clustering around the pooled effect. Both sides of the funnel were well populated, and no major asymmetry or large gaps were observed, suggesting minimal evidence of small-study publication bias.

In the Parkinsonism dataset, the funnel plot ([Supplementary Fig. S2] [available in the online version only]) revealed asymmetry on visual inspection. Smaller studies disproportionately show large negative effects. This distribution implied substantially small-study effects and potential bias. Egger's test was done for plot asymmetry, and it refuted the publication bias (t = 0.28, df = 9, p = 0.7865; bias estimate: 0.2953, SE = 1.0585).

The AD funnel plot ([Supplementary Fig. S3] [available in the online version only]) demonstrated plot asymmetry. Smaller studies with high standard error still tended to favor OBV shrinkage. Due to the inadequate number of studies, Egger's linear regression was not possible. So, the trimming of effect size was done by trim-fill analysis considering publication bias, and the computed OBV shrinkage was −7.09 mm³ (95% CI: −12.20 to −1.98) on the right side and 7.5 mm³ (95% CI: −10.86 to −4.16) on the left side.

 

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Discussion

The neural processes responsible for the gradual decline of human olfactory functionality are inadequately understood. Aging-related degeneration in peripheral olfactory structures, including receptor neurons, the olfactory epithelium, and the olfactory bulb, is undoubtedly a primary factor, while changes in higher cortical centers associated with odor perception, identification, and memory may also play a role. Notable age-related alterations in the olfactory bulb and epithelium have been observed in many isolated investigations before. This research examines the volumetric evaluation of the olfactory bulb as a neuroanatomical entity and its determinants, including age, sex, laterality, and olfaction. Notwithstanding the limited quantity of investigations, the findings align with the aforementioned assumption.

Summary of Findings

The pooled mean volume of right and left olfactory bulbs was observed to be 54.5 mm³ (95% CI: 42.03–66.98) and 55.56 mm³ (95% CI: 42.96–68.15; [Table 4]). The lower heterogeneity was observed in studies that used 1.5T MRI than in studies that used 3T MRI. The lower heterogeneity with 1.5T is most likely related to the standardized protocol and fewer artifacts than 3T, where protocol variability and technical challenges may cause higher heterogeneity.

Table 4 Summary of meta-analysis

OBV in healthy subjects and correlation with aging and olfactory function
Analysis	Group/Comparison	Pooled mean OBV/SMD	95% CI	p-Value	I 2 (%)	Sample size (n)	Model	Notes
Right OBV (mm3)	Healthy individuals	54.5 mm3	42.03–66.98	<0.001	99% Substantial heterogeneity	11 studies (N = 1,531)	Random effects	No significant sex or laterality difference
Left OBV9 (mm3)	Healthy individuals	56.22 mm3	42.96–68.15	<0.001	99% Substantial heterogeneity	11 studies (N = 1,531)	Random effects	No significant sex or laterality difference
Laterality (SMD)	Right vs. left OB	0.47 SD	−0.11 to 1.04	0.1461	31.6%	11 studies	Fixed effects	Not statistically significant
Sex differences (SMD)	Male vs. female	1.54 SD	−0.73 to 3.80	0.09	51%	5 studies (N = 692)	Random effects	Not statistically significant
OBV (right) correlation with age	All groups	r = 0.53	0.33–0.68	<0.001	97%	7 studies	Random effects	Moderate correlation
OBV (left) correlation with age	All groups	r = 0.52	0.4–0.73	<0.001	96%	8 studies	Random effects	Moderate correlation
OBV correlation with olfactory function (TDI, UPSIT)	All groups	r = 0.48	0.31–0.61	<0.01	75%	8 studies	Random effects	Moderate correlation
OBV in Parkinsonism and Alzheimer's disease as neurodegeneration
OBV shrinkage (SMD)	Parkinson's disease vs. control	Right: −0.9 SD or (−11.31 mm3) Left: -0.93SD or (−12.28 mm3)	Right: −1.36 to −43 SD or (−15.56 to −7.06 mm3) Left: −1.43 to −0.43 SD or (−16.40 to −8.16 mm3)	<0.001	88-91%	11 studies (n = 683 PD, 313 HC)	Random effects	OBV is significantly lower in PD. Meta-regression: age vs. OBV shrinkage R 2 = 0.1876 (≈43.3% explained) Meta-regression: olfaction score vs. OBV shrinkage R 2 = 0.410 (≈64% explained variance) Duration: negligible
OBV shrinkage (SMD)	Alzheimer's disease vs. control	Right: −1.05 SD or (−7.96 mm3 ) Left: −1.0 SD or (−7.51 mm3)	Right: −1.69 to −0.4SD or (−12.35 to −3.58 mm3) Left: −1.63 to −0.37 SD or (−10.86 to −5.19 mm3)	<0.001	90.4–90.7%	7 studies (n = 232 AD, 246 HC)	Random effects	Meta-regression with age and olfactory score not feasible (n < 7) due to inadequate data

Abbreviations: OBV, olfactory bulb volume; SMD, standardized mean differences; TDI, threshold, differentiation, and identification; UPSIT, University of Pennsylvania Smell Identification Test.

There was also no discernible disparity between the sexes and laterality. The association between age and olfactory bulb volume exhibited a moderate correlation, with pooled correlation coefficients ranging from 0.53 to 0.59. The olfactory function was gauged using either TDI or UPSIT in the studies considered, and the olfactory functional score exhibited a modest correlation with olfactory bulb volume. Age and olfactory functional score were modest predictors of olfactory bulb volume, with nearly the same correlation coefficient. Age-related shrinkage was also investigated in relation to Parkinsonism and AD, where the reduction in the volume of the olfactory bulbs was 0.9 to 0.93 SD and 1 to 1.05 SD, respectively. Meta-regression indicated that the age-related degeneration accounted for 43.3% of the decline in Parkinsonism. Similar findings were not evaluated due to the limited number of studies in AD. Based on these observations, we could assert that at least 40% shrinkage of olfactory bulb volume in healthy and PD is age-related.

 

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Comparison with Previous Literature

The volumetric reduction of OB was also observed in histological studies. Bhatnagar et al evaluated the volume at different age groups in 16 cadaveric samples and reported 50.02 mm³ (38.25–61.80), 43.35 mm³ (36.64–50.06), and 36.68 mm³ (26.62–46.74) at ages 25, 60, and 95 years, respectively.[41] They are also unable to capture laterality differences. They did not comment on the sex difference as their samples were female only. Haehner et al measured the olfactory bulb volume by 1.5T MRI, which was 57.7 mm³ (95% CI: 50–64) in posttraumatic adults.[6] The confidence interval (95%) of the present estimation of olfactory bulb volume is almost similar, and the difference is attributed to the lower sample size and sample variances, as the older female population had more representation in the sample. Bhatnagar et al also estimated the shrinkage of the olfactory bulb by histometric evaluation and they claimed that the olfactory bulb undergoes a shrinkage difference attributed to a lower sample size by 0.19 mm³ per year.[41] Yousem et al and Meisami et al recorded similar findings along with loss of olfactory function.[7] [42] Bontempi et al examined the age-related shrinkage of olfactory bulb volume in mice model and reported significant shrinkage (−1.83 SD, p < 0.001) in elderly mice.[43]

 

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Anatomical Basis of Olfactory Bulb Shrinkage

Aging results in significant degeneration of the human olfactory system, particularly in the olfactory epithelium and bulb. Studies by Liss and Gomez, Naessen, and Nakashima et al suggested that prolonged exposure to environmental and biological hazards contributes to receptor neuron loss, leading to structural and functional decline in OB. MRI studies confirm a notable reduction in bulb size and laminae in elderly individuals, although the overall cytoarchitecture remains intact.[44] [45] [46]

Glomeruli and mitral cells, essential for sensory integration and odor discrimination, show a marked decline with age. Research by Bhatnagar et al demonstrated that mitral cell numbers decrease from ∼50,935 in young adults (at 25 years) to 32,718 in middle age (at 60 years) and further to 14,501 in the elderly (at 95 years), representing a 70% reduction over time at a rate of 520 mitral cells per year.[41] Similarly, the number of glomeruli declines from around 7,800 in young adults to 4,900 in middle-aged individuals and further to ∼2,100 in old age. These reductions correspond to an estimated 10% loss per decade. While neuronal loss is expected with aging, the extent of mitral cell and glomeruli depletion is unusually high compared with other sensory or brain regions.

Studies on the rat olfactory system by Meisami et al highlighted the complexity of olfactory processing, where millions of receptor neurons connect to thousands of glomeruli and mitral cells, forming intricate synaptic networks.[42] In humans, the substantial loss of these structures likely impacts olfactory processing, contributing to diminished olfactory sensitivity and discrimination, as observed in psychophysical and perceptual studies. However, this decline is not always evident in middle-aged individuals. Two possible explanations are the brain's compensatory mechanisms maintaining function despite structural losses or the insensitivity of current perceptual tests in detecting mild deficits.

Despite these degenerative changes, in vitro studies suggest that surviving receptor neurons in elderly individuals remain responsive to odorants, although their response patterns vary from those in younger adults. This indicates that the remaining 30% of glomeruli and mitral cells may provide a minimal but functional neural framework that sustains basic olfactory abilities in old age. While olfactory decline is a natural consequence of aging, the resilience of the remaining neural structures helps maintain limited olfactory function throughout life.

This study has various strengths that contribute to its significance in understanding age-related OB degeneration and its association with neurodegenerative diseases. First, it utilizes a comprehensive meta-analytical approach, pooling data from multiple high-quality MRI-based studies, which enhances the reliability and generalizability of the findings. The inclusion of healthy, PD, and AD subjects provides valuable insight into the spectrum of OB atrophy, distinguishing between normal aging and disease-related degeneration. Additionally, the study employs robust statistical methods, including meta-regression and subgroup analyses, to explore the potential influence of age, sex, laterality, and disease duration on OBV. The strong correlation between OBV and olfactory function further supports the potential role of OB atrophy as an early biomarker for neurodegenerative disorders.

Even with these strengths, it is important to be aware of observed limitations. The study relies on cross-sectional data, which limits the ability to establish causality between OB shrinkage and olfactory dysfunction over time. Longitudinal studies are needed to determine the progression of OB atrophy and its predictive value in neurodegenerative diseases. Additionally, the sample size for meta-regression in AD was insufficient to draw definitive conclusions about the extent of age-related OB shrinkage in this population. Variability in MRI protocols, field strengths, and segmentation methods across included studies may also introduce inconsistencies in volumetric measurements. Moreover, potential confounding factors such as genetic predisposition, environmental influences, and comorbidities were not extensively explored, which could impact the observed associations. Lastly, while olfactory function was assessed using TDI and UPSIT scores, variations in testing methodologies and subjectivity in self-reported olfactory impairment may influence the accuracy of functional correlations with OBV.

The study underscores the need for further longitudinal investigations to explore the predictive value of OBV in neurodegenerative disorders. Future research should also examine the underlying mechanisms driving OB degeneration, including environmental and genetic factors. Incorporating olfactory function testing and OB volumetric analysis into routine clinical assessments could improve early disease detection, potentially enabling timely interventions and better management of age-related and neurodegenerative conditions.

The current study aimed to assess age-related degeneration of OB in both healthy and neurodegenerative conditions, focusing on its volumetric changes and correlation with olfactory function. The results demonstrate a significant association between aging and OBV reduction, with a moderate correlation (r = 0.53–0.59). Olfactory function, measured using TDI or UPSIT scores also showed a moderate correlation with OBV (r = 0.48). Notably, individuals with PD and AD exhibited a greater degree of OBV shrinkage (0.9–1.05 SD), indicating that neurodegenerative processes further accelerate age-related OB atrophy. Meta-regression analysis suggested that ∼43% of OBV reduction in PD could be attributed to aging, highlighting the interplay between natural aging and disease pathology.

In conclusion, these findings reinforce previous research, which has shown that OB degeneration occurs both as a consequence of normal aging and as an early indicator of neurodegenerative diseases. While sex and laterality did not significantly impact OBV, the consistent volume reduction observed across studies suggests that OB degeneration may serve as a potential biomarker for early disease detection. We emphasized the need for larger, longitudinal studies with standardized MRI protocols and complete covariate reporting to overcome current limitations in subgroup analyses.

 

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Conflict of Interest

None declared.

Data Availability Statement

All available data have been included in the manuscript.

Ethical Approval

Not applicable.

Patients' Consent

Patient consent is not required.

• References

• 1 Çullu N, Yeniçeri İÖ, Güney B, Özdemir MY, Koşar İ. Evaluation of olfactory bulbus volume and olfactory sulcus depth by 3 T MR. Surg Radiol Anat 2020; 42 (09) 1113-1118
• 2 Standring S. Gray's Anatomy: The Anatomical Basis of Clinical Practice. 42nd ed.. Elsevier; 2020: 1149-1155
• 3 Marlier L, Gaugler C, Messer J. Olfactory stimulation prevents apnea in premature newborns. Pediatrics 2005; 115 (01) 83-88
• 4 Hummel T, Smitka M, Puschmann S, Gerber JC, Schaal B, Buschhüter D. Correlation between olfactory bulb volume and olfactory function in children and adolescents. Exp Brain Res 2011; 214 (02) 285-291
• 5 Schneider JF, Floemer F. Maturation of the olfactory bulbs: MR imaging findings. AJNR Am J Neuroradiol 2009; 30 (06) 1149-1152
• 6 Haehner A, Rodewald A, Gerber JC, Hummel T. Correlation of olfactory function with changes in the volume of the human olfactory bulb. Arch Otolaryngol Head Neck Surg 2008; 134 (06) 621-624
• 7 Yousem DM, Geckle RJ, Bilker WB, Doty RL. Olfactory bulb and tract and temporal lobe volumes. Normative data across decades. Ann N Y Acad Sci 1998; 855: 546-555
• 8 Brodoehl S, Klingner C, Volk GF, Bitter T, Witte OW, Redecker C. Decreased olfactory bulb volume in idiopathic Parkinson's disease detected by 3.0-tesla magnetic resonance imaging. Mov Disord 2012; 27 (08) 1019-1025
• 9 Dutta D, Karthik K, Holla VV. et al. Olfactory bulb volume, olfactory sulcus depth in Parkinson's disease, atypical Parkinsonism. Mov Disord Clin Pract 2023; 10 (05) 794-801
• 10 Servello A, Fioretti A, Gualdi G. et al. Olfactory dysfunction, olfactory bulb volume and Alzheimer's disease: is there a correlation? A pilot study. J Alzheimers Dis 2015; 48 (02) 395-402
• 11 Thomann PA, Dos Santos V, Seidl U, Toro P, Essig M, Schröder J. MRI-derived atrophy of the olfactory bulb and tract in mild cognitive impairment and Alzheimer's disease. J Alzheimers Dis 2009; 17 (01) 213-221
• 12 Dan X, Wechter N, Gray S, Mohanty JG, Croteau DL, Bohr VA. Olfactory dysfunction in aging and neurodegenerative diseases. Ageing Res Rev 2021; 70: 101416
• 13 Yi JS, Hura N, Roxbury CR, Lin SY. Magnetic resonance imaging findings among individuals with olfactory and cognitive impairment. Laryngoscope 2022; 132 (01) 177-187
• 14 Rombaux P, Potier H, Markessis E, Duprez T, Hummel T. Olfactory bulb volume and depth of olfactory sulcus in patients with idiopathic olfactory loss. Eur Arch Otorhinolaryngol 2010; 267 (10) 1551-1556
• 15 Attems J, Walker L, Jellinger KA. Olfaction and aging: a mini-review. Gerontology 2015; 61 (06) 485-490
• 16 Schubert C, Schulz K, Träger S. et al. Neuronal adenosine A1 receptor is critical for olfactory function but unable to attenuate olfactory dysfunction in neuroinflammation. Front Cell Neurosci 2022; 16: 912030
• 17 Peterson J, Welch V, Losos M. et al. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-analyses. Ottawa Hospital Research Institute; 2011
• 18 Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 2014; 14: 135
• 19 Mueller A, Abolmaali ND, Hakimi AR. et al. Olfactory bulb volumes in patients with idiopathic Parkinson's disease: a pilot study. J Neural Transm (Vienna) 2005; 112 (10) 1363-1370
• 20 Buschhüter D, Smitka M, Puschmann S. et al. Correlation between olfactory bulb volume and olfactory function. Neuroimage 2008; 42 (02) 498-502
• 21 Thomann PA, Dos Santos V, Toro P, Schönknecht P, Essig M, Schröder J. Reduced olfactory bulb and tract volume in early Alzheimer's disease – a MRI study. Neurobiol Aging 2009; 30 (05) 838-841
• 22 Wang J, You H, Liu JF, Ni DF, Zhang ZX, Guan J. Association of olfactory bulb volume and olfactory sulcus depth with olfactory function in patients with Parkinson disease. AJNR Am J Neuroradiol 2011; 32 (04) 677-681
• 23 Hakyemez HA, Veyseller B, Ozer F. et al. Relationship of olfactory function with olfactory bulbus volume, disease duration and Unified Parkinson's disease rating scale scores in patients with early stage of idiopathic Parkinson's disease. J Clin Neurosci 2013; 20 (10) 1469-1470
• 24 Chen B, Zhong X, Mai N. et al. Cognitive impairment and structural abnormalities in late life depression with olfactory identification impairment: an Alzheimer's disease-like pattern. Int J Neuropsychopharmacol 2018; 21 (07) 640-648
• 25 Altinayar S, Oner S, Can S, Kizilay A, Kamisli S, Sarac K. Olfactory disfunction and its relation olfactory bulb volume in Parkinson's disease. Eur Rev Med Pharmacol Sci 2014; 18 (23) 3659-3664
• 26 Yu H, Hang W, Zhang J, Liu G. Olfactory function in patients with Alzheimer' disease [in Chinese]. Lin Chuang Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2015; 29 (05) 444-447
• 27 Paschen L, Schmidt N, Wolff S. et al. The olfactory bulb volume in patients with idiopathic Parkinson's disease. Eur J Neurol 2015; 22 (07) 1068-1073
• 28 Tanik N, Serin HI, Celikbilek A, Inan LE, Gundogdu F. Associations of olfactory bulb and depth of olfactory sulcus with basal ganglia and hippocampus in patients with Parkinson's disease. Neurosci Lett 2016; 620: 111-114
• 29 Campabadal A, Uribe C, Segura B. et al. Brain correlates of progressive olfactory loss in Parkinson's disease. Parkinsonism Relat Disord 2017; 41: 44-50
• 30 Chen S, Tan HY, Wu ZH. et al. Imaging of olfactory bulb and gray matter volumes in brain areas associated with olfactory function in patients with Parkinson's disease and multiple system atrophy. Eur J Radiol 2014; 83 (03) 564-570
• 31 Maghsoudi S, Treimo E. The correlation between olfactory function, olfactory bulb volume, and olfactory sulcus depth in healthy subjects. Master's Thesis. Oslo, Norway: University of Oslo. 2019
• 32 Karaoglan M, Colakoglu Er H. Radiological evidence to changes in the olfactory bulb volume depending on body mass index in the childhood. Int J Pediatr Otorhinolaryngol 2020; 139: 110415
• 33 Poessel M, Breuer N, Joshi A. et al. Reduced olfactory bulb volume in obesity and its relation to metabolic health status. Front Hum Neurosci 2020; 14: 586998
• 34 Sahin S, Baykan AH, Altunisik E, Vural CA, Sahin FD, Inan I. Quantitative analysis of healthy olfactory sulcus depth, olfactory tract length and olfactory bulb volume in the paediatric population: a magnetic resonance study. Folia Morphol (Warsz) 2021; 80 (01) 33-39
• 35 Tremblay C, Mei J, Frasnelli J. Olfactory bulb surroundings can help to distinguish Parkinson's disease from non-parkinsonian olfactory dysfunction. Neuroimage Clin 2020; 28: 102457
• 36 Petekkaya E, Kaptan Z, Unalmis D. et al. An investigation of olfactory bulb and entorhinal cortex volumes in both patients with Alzheimer's disease and healthy individuals, and a comparative analysis of neuropeptides. Med Sci 2020; 9 (04) 866
• 37 Yildirim D, Altundag A, Tekcan Sanli DE. et al. A new perspective on imaging of olfactory dysfunction: Does size matter?. Eur J Radiol 2020; 132: 109290
• 38 Lu R, Aziz NA, Reuter M, Stöcker T, Breteler MMB. Evaluation of the neuroanatomical basis of olfactory dysfunction in the general population. JAMA Otolaryngol Head Neck Surg 2021; 147 (10) 855-863
• 39 Güney B, Çullu N, Özdemir MY. Evaluation of olfactory bulbus volume and olfactory sulcus depth development with 3 Tesla magnetic resonance imaging in childhood. Folia Morphol (Warsz) 2022; 81 (02) 307-313
• 40 Carnemolla SE, Kumfor F, Liang CT, Foxe D, Ahmed RM, Piguet O. Olfactory bulb integrity in frontotemporal dementia and Alzheimer's disease. J Alzheimers Dis 2022; 89 (01) 51-66
• 41 Bhatnagar KP, Kennedy RC, Baron G, Greenberg RA. Number of mitral cells and the bulb volume in the aging human olfactory bulb: a quantitative morphological study. Anat Rec 1987; 218 (01) 73-87
• 42 Meisami E, Mikhail L, Baim D, Bhatnagar KP. Human olfactory bulb: aging of glomeruli and mitral cells and a search for the accessory olfactory bulb. Ann N Y Acad Sci 1998; 855: 708-715
• 43 Bontempi P, Ricatti MJ, Sandri M, Nicolato E, Mucignat-Caretta C, Zancanaro C. Age-related in vivo structural changes in the male mouse olfactory bulb and their correlation with olfactory-driven behavior. Biology (Basel) 2023; 12 (03) 381
• 44 Liss L, Gomez F. The nature of senile changes of the human olfactory bulb and tract. AMA Arch Otolaryngol 1958; 67 (02) 167-171
• 45 Naessen R. An enquiry on the morphological characteristics and possible changes with age in the olfactory region of man. Acta Otolaryngol 1971; 71 (01) 49-62
• 46 Nakashima T, Kimmelman CP, Snow Jr JB. Structure of human fetal and adult olfactory neuroepithelium. Arch Otolaryngol 1984; 110 (10) 641-646

Publikationsverlauf

Artikel online veröffentlicht:
16. September 2025