Volumetría hipocampal: análisis comparativo de los métodos de evaluación en enfermedad de Alzheimer

Resumen

Objetivo La atrofia hipocampal es uno de los biomarcadores radiológicos más sensibles de la enfermedad de Alzheimer (EA) y existen diferentes métodos para evaluarla: análisis subjetivo visual (ASV), análisis objetivo manual (AOM) y análisis objetivo automático (AOA). Nos proponemos comparar esos métodos, y evaluar si el AOA presenta una confiabilidad cercana al AOM (método de referencia) y superior al ASV.

Materiales y Métodos Se seleccionaron retrospectivamente imágenes de resonancia magnética (RM) fast spoiled gradient-echo (FSPGR) de 28 sujetos (14 con deterioro cognitivo leve, 7 con EA y 7 controles). El ASV fue realizado por 10 radiólogos, clasificando la atrofia hipocampal en: nula, leve, moderada o severa. El AOM se basó en la segmentación manual de los hipocampos por dos operadores. El AOA fue realizada por medio del software FreeSurfer 5.3. Se calcularon coeficientes de correlación rho de Spearman para las variables discretas y coeficientes de correlación intraclase para las variables continuas.

Resultados Los coeficientes de correlación entre los dos operadores que realizaron el AOM fueron de 0,88 (p < 0,0001) para los hipocampos izquierdos y de 0,86 (p < 0,0001) para los hipocampos derechos. El coeficiente de correlación entre todos los ASV (promediados) y AOM fue de -0,81 (IC 95% -0,96- -0,66). Los coeficientes de correlación entre el AOA y el AOM fue de 0,54 (p < 0,0001) para los hipocampos izquierdos y de 0,61 (p < 0,0001) para los hipocampos derechos.

Conclusión Si bien el AOA tiene moderada correlación con el método de referencia, no es superior al ASV promedio y se deberían tomar recaudos antes de ser implementado en la práctica asistencial.

Abstract

Objective Hippocampal atrophy is one of the most sensible radiological biomarkers of Alzheimer's disease. There are different methods to evaluate atrophy: visual subjective analysis (VSA), manual objective analysis (MOA) and automatic objective analysis (AOA). We will compare these methods and evaluate if AOA has a confidence similar to MOA (gold standard), and better than VSA.

Materials and Methods We retrospectively selected 3D FSPGR MRI from 28 subjects of whom 14 had mild cognitive impairment, 7 Alzheimer's disease and 7 controls. VSA was performed by 10 radiologists who classified hippocampal atrophy in none, mild, moderate and severe. For MOA, two operators manually segmented both hippocampus from all subjects. AOA was performed by FreeSurfer 5.3. Spearman's rho correlation coefficient was calculated for discrete variables and intraclass correlation coefficient was calculated for continuous variables.

Results Correlation coefficients between the operators that performed MOA was 0.88 (p < 0.0001) for left hippocampi and 0.86 (p < 0,0001) for right hippocampi. Correlation coefficients between mean VSA and MOA was -0,81 (95% CI -0,96- -0,66). Correlation coefficients between AOA and AOM was 0.54 (p < 0.0001) for left hippocampi and 0.61 (p < 0.0001) for right hippocampi.

Conclusion Even though AOA has moderate correlation with the gold standard it is not superior to average VSA and should be implemented with care in clinical practice.

Palabras Clave

enfermedad de alzheimer - biomarcadores - imágenes de resonancia magnética - hipocampos

Keywords

alzheimer disease - biomarkers - magnetic resonance imaging - hippocampus

^Ω Actualmente no afiliado al Instituto de Investigaciones Neurológicas Dr. Raúl Carrea (FLENI).

Colaboradores

Tatiana Escobar, Laura Falcón, Romina Goñi, Gabriela Michelin, Pablo Pfister, Diego Pineda y Francisco Sepúlveda Hermosilla.

Responsabilidades Éticas

Protección de personas y animales. Los autores declaran que para esta investigación no se han realizado experimentos en seres humanos ni en animales.

Confidencialidad de los datos. Los autores declaran que en este artículo no aparecen datos de pacientes.

Derecho a la privacidad y consentimiento informado. Los autores declaran que en este artículo no aparecen datos de pacientes.

• Bibliografía

• 1 Dubois B, Feldman HH, Jacova C. , et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007; 6 (08) 734-746
• 2 van de Pol LA, Hensel A, Barkhof F, Gertz HJ, Scheltens P, van der Flier WM. Hippocampal atrophy in Alzheimer disease: age matters. Neurology 2006; 66 (02) 236-238
• 3 Scheltens P, Leys D, Barkhof F. , et al. Atrophy of medial temporal lobes on MRI in “probable” Alzheimer's disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 1992; 55 (10) 967-972
• 4 Bobinski M, de Leon MJ, Wegiel J. , et al. The histological validation of post mortem magnetic resonance imaging-determined hippocampal volume in Alzheimer's disease. Neuroscience 2000; 95 (03) 721-725
• 5 Boccardi M, Bocchetta M, Apostolova LG. , et al; EADC-ADNI Working Group on the Harmonized Protocol for Manual Hippocampal Segmentation. Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance. Alzheimers Dement 2015; 11 (02) 126-138
• 6 Bocchetta M, Boccardi M, Ganzola R. , et al; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and for the Alzheimer's Disease Neuroimaging Initiative. Harmonized benchmark labels of the hippocampus on magnetic resonance: the EADC-ADNI project. Alzheimers Dement 2015; 11 (02) 151-60.e5
• 7 Frisoni GB, Jack Jr CR, Bocchetta M. , et al; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Volumetry and for the Alzheimer's Disease Neuroimaging Initiative. The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity. Alzheimers Dement 2015; 11 (02) 111-125
• 8 Dill V, Franco AR, Pinho MS. Automated methods for hippocampus segmentation: the evolution and a review of the state of the art. Neuroinformatics 2015; 13 (02) 133-150
• 9 Morey RA, Petty CM, Xu Y. , et al. A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. Neuroimage 2009; 45 (03) 855-866
• 10 Chupin M, Hammers A, Liu RSN. , et al. Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: method and validation. Neuroimage 2009; 46 (03) 749-761
• 11 Russo MJ, Gustafson D, Vázquez S. , et al; Argentina-Alzheimer's Disease Neuroimaging Initiative. Creation of the Argentina-Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2014; 10 (1, Suppl): S84-S87
• 12 Duchesne S, Valdivia F, Robitaille N. , et al; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and for the Alzheimer's Disease Neuroimaging Initiative. Manual segmentation qualification platform for the EADC-ADNI harmonized protocol for hippocampal segmentation project. Alzheimers Dement 2015; 11 (02) 161-174
• 13 Bartsch T, Wulff P. The hippocampus in aging and disease: From plasticity to vulnerability. Neuroscience 2015; 309: 1-16
• 14 Schröder J, Pantel J. Neuroimaging of hippocampal atrophy in early recognition of Alzheimer's disease--a critical appraisal after two decades of research. Psychiatry Res 2016; 247: 71-78
• 15 Clerx L, van Rossum IA, Burns L. , et al. Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment. Neurobiol Aging 2013; 34 (08) 2003-2013
• 16 Yushkevich PA, Amaral RS, Augustinack JC. , et al; Hippocampal Subfields Group (HSG). Quantitative comparison of 21 protocols for labeling hippocampal subfields and parahippocampal subregions in in vivo MRI: towards a harmonized segmentation protocol. Neuroimage 2015; 111: 526-541
• 17 Clerx L, Gronenschild EH, Echavarri C, Verhey F, Aalten P, Jacobs HI. Can FreeSurfer Compete with Manual Volumetric Measurements in Alzheimer's Disease?. Curr Alzheimer Res 2015; 12 (04) 358-367
• 18 Berti V, Polito C, Lombardi G, Ferrari C, Sorbi S, Pupi A. Rethinking on the concept of biomarkers in preclinical Alzheimer's disease. Neurol Sci 2016; 37 (05) 663-672
• 19 Besson FL, La Joie R, Doeuvre L. , et al. Cognitive and Brain Profiles Associated with Current Neuroimaging Biomarkers of Preclinical Alzheimer's Disease. J Neurosci 2015; 35 (29) 10402-10411