Ultraschall Med 2018; 39(02): 206-212
DOI: 10.1055/s-0041-111065
Original Article
© Georg Thieme Verlag KG Stuttgart · New York

Power Doppler Quantification in Assessing Gestational Trophoblastic Neoplasia

Powerdoppler-Quantifizierung zur Beurteilung der gestationsbedingten trophoblastischen Neoplasie
Yuanwei Li
1   Bioengineering, Imperial College London, United Kingdom of Great Britain and Northern Ireland
,
Meng Xing Tang
1   Bioengineering, Imperial College London, United Kingdom of Great Britain and Northern Ireland
,
Roshan Agarwal
2   Medical Oncology, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Daksha Patel
3   Imaging, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Robert J. Eckersley
1   Bioengineering, Imperial College London, United Kingdom of Great Britain and Northern Ireland
,
Guillaume Barrois
1   Bioengineering, Imperial College London, United Kingdom of Great Britain and Northern Ireland
,
Mary E. Roddie
3   Imaging, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Linda Dayal
2   Medical Oncology, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Philip M. Savage
2   Medical Oncology, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Michael J. Seckl
2   Medical Oncology, Charing Cross Hospital, London, United Kingdom of Great Britain and Northern Ireland
,
Adrian Lim
4   Imaging, Imperial College, London, United Kingdom of Great Britain and Northern Ireland
› Author Affiliations
Further Information

Publication History

01 June 2015

28 October 2015

Publication Date:
16 August 2016 (online)

Abstract

Purpose The FIGO score cannot accurately stratify low-risk gestational trophoblastic neoplasia (GTN) patients who develop chemoresistance to single agent methotrexate chemotherapy. Tumour vascularisation is a key risk factor and its quantification may provide non-invasive way of complementing risk assessment.

Materials and Methods 187 FIGO-staged, low-risk GTN patients were prospectively recruited. Power Doppler ultrasound was analysed using a quantification program. Four diagnostic indicators were obtained comprising the number of colour pixels (NCP), mean dB, power Doppler quantification (PDQ), and percentage of colour pixels (%CP). Each indicator performance was assessed to determine if they could distinguish the subset of low-risk patients who became chemoresistant.

Results There were 111 non-resistant and 76 resistant patients. NCP performed best at distinguishing these two groups where the non-resistant group had an average 3435 (± 2060) pixels and the resistant group 6151 (± 3192) pixels (p < 0.001). PDQ and %CP showed significant differences (p < 0.001) but had poorer performance (area under ROC curves were 72 % and 67 % respectively compared with 75 % for NCP). The mean dB index was not significantly different (p = 0.133).

Conclusion Power Doppler ultrasound quantification shows potential for non-invasive assessment of tumour vascularity and can distinguish low-risk GTN patients who become chemoresistant from those who have an uncomplicated course with first line treatment.

Zusammenfassung

Ziel Der FIGO-Score kann Patienten mit gestationsbedingter trophoblastischer Niedrig-Risiko-Neoplasie (GTN), die eine Chemoresistenz gegenüber einer Methotrexat-Monotherapie entwickeln, nicht exakt stratifizieren. Die Vaskularisierung des Tumors ist ein entscheidender Faktor und dessen Quantifizierung kann als nicht-invasive Methode für die ergänzende Risikoabschätzung dienen.

Material und Methoden 187 FIGO-eingeteilte Niedrigrisiko-GNT-Patienten wurden prospektiv aufgenommen. Die Power-Dopplersonografie wurde mittels eines Quantifizierungsprogramms analysiert. Ermittelt wurden vier diagnostische Marker, die aus der Zahl der Farbpixel (NCP), der mittleren dB, der Powerdoppler-Quantifizierung (PDQ) und dem Prozent der Farbpixel (%CP) bestanden. Die Leistung jedes Markers in Bezug auf die Erkennung der Untergruppe von Niedrigrisiko-Patienten, die eine Chemoresistenz entwickelten, wurde bewertet.

Ergebnisse Es gab 111 nicht-resistente und 76 resistente Patienten. NCP konnte am besten zwischen den beiden Gruppen differenzieren, wobei die nicht-resistente Gruppe durchschnittlich 3435 (± 2060) Pixel und resistente Gruppe 6151 (± 3192) Pixel aufwies (p < 0,001). PDQ und %CP zeigten signifikante Unterschiede (p < 0,001), aber hatten eine schlechtere Leistung („Area under ROC curve“ 72 % für PDQ und 67 % für %CP im Vergleich zu 75 % für NCP). Der mittlere dB-Index wies keine signifikanten Unterschiede auf (p = 0,133).

Schlussfolgerung Die Powerdoppler-Quantifizierung ermöglicht die nicht-invasive Beurteilung der Tumorvaskularität und kann zwischen Niedrigrisiko-GTN-Patienten mit Chemoresistenz und denen mit unkompliziertem Verlauf unter einer First-Line-Therapie differenzieren.

 
  • References

  • 1 Seckl MJ, Sebire NJ, Berkowitz RS. Gestational trophoblastic disease. The Lancet 2010; 376: 717-729
  • 2 Shih IM. Gestational trophoblastic neoplasia—pathogenesis and potential therapeutic targets. Lancet Oncol 2007; 8: 642-650
  • 3 Kajii T, Ohama K. Androgenetic origin of hydatidiform mole. Nature 1977; 268: 633-634
  • 4 Savage PM, Sita-Lumsden A, Dickson S. et al. The relationship of maternal age to molar pregnancy incidence, risks for chemotherapy and subsequent pregnancy outcome. J Obstet Gynaecol 2013; 33: 406-411
  • 5 Agarwal R, Harding V, Short D. et al. Uterine artery pulsatility index: a predictor of methotrexate resistance in gestational trophoblastic neoplasia. Br J Cancer 2012; 106: 1089-1094
  • 6 Kohorn EI. The new FIGO 2000 staging and risk factor scoring system for gestational trophoblastic disease: Description and critical assessment. Int J Gynecol Cancer 2001; 11: 73-77
  • 7 Aghajanian C. Treatment of Low-Risk Gestational Trophoblastic Neoplasia. J Clin Oncol 2011; 29: 786-788
  • 8 Bower M, Newlands ES, Holden L. et al. EMA/CO for high-risk gestational trophoblastic tumors: results from a cohort of 272 patients. J Clin Oncol Off J Am Soc Clin Oncol 1997; 15: 2636-2643
  • 9 McNeish IA, Strickland S, Holden L. et al. Low-Risk Persistent Gestational Trophoblastic Disease: Outcome After Initial Treatment With Low-Dose Methotrexate and Folinic Acid From 1992 to 2000. J Clin Oncol 2002; 20: 1838-1844
  • 10 Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011; 144: 646-674
  • 11 Weber G, Merz E, Bahlmann F. et al. Ultrasound assessment of ovarian tumors – comparison between transvaginal 3D technique and conventional 2-dimensional vaginal ultrasonography]. Ultraschall in Med Stuttg Ger 1980 1997; 18: 26-30
  • 12 Acharya UR, Mookiah MRK, Vinitha Sree S. et al. Evolutionary algorithm-based classifier parameter tuning for automatic ovarian cancer tissue characterization and classification. Ultraschall in Med Stuttg Ger 1980 2014; 35: 237-245
  • 13 Agarwal R, Strickland S, McNeish IA. et al. Doppler ultrasonography of the uterine artery and the response to chemotherapy in patients with gestational trophoblastic tumors. Clin Cancer Res Off J Am Assoc Cancer Res 2002; 8: 1142-1147
  • 14 Weidner N. Tumor angiogenesis: review of current applications in tumor prognostication. Semin Diagn Pathol 1993; 10: 302-313
  • 15 Allen SD, Lim AK, Seckl MJ. et al. Radiology of gestational trophoblastic neoplasia. Clin Radiol 2006; 61: 301-313
  • 16 Lim AKP, Patel D, Patel N. et al. Pelvic imaging in gestational trophoblastic neoplasia. J Reprod Med 2008; 53: 575-578