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image of Integrative Profiling of the Ovarian Reserve Using Ultrasound and MRI Data by Comparative Analysis: A Systematic Review

Abstract

Background

Ovarian reserve reflects the functional capacity of a woman’s ovaries, encompassing factors such as follicle quantity, egg quality, and fertilization potential. Assessment of ovarian reserve is essential in reproductive medicine, particularly for fertility evaluation and assisted reproductive technologies (ART). While traditional biochemical markers such as anti-Müllerian hormone (AMH) and follicle-stimulating hormone (FSH) are commonly used, instrumental diagnostic methods like ultrasound and magnetic resonance imaging (MRI) provide valuable morphological and functional insights. This systematic review without a comprehensive meta-analysis evaluates the role of ultrasound and MRI in assessing ovarian reserve and their potential applications in clinical and research settings.

Methods

A comprehensive literature search was conducted across multiple databases to identify relevant studies evaluating ovarian reserve using ultrasound and MRI. Studies were screened based on predefined inclusion criteria, focusing on imaging parameters such as ovarian volume, follicular count, stromal characteristics, and vascularization. The effectiveness of these imaging techniques was analyzed in comparison to established biochemical markers. Due to heterogeneity in the included studies, a systematic review was performed without a formal meta-analysis.

Results

Ultrasound, particularly transvaginal ultrasound (TVUS), remains the gold standard for ovarian reserve assessment, allowing real-time visualization of antral follicle count (AFC), ovarian volume, and follicular morphology. Doppler ultrasound provides additional insights into ovarian blood flow, which correlates with follicular development and ovarian function. MRI offers high-resolution, three-dimensional imaging, enabling detailed assessment of ovarian structure, follicular density, and stromal composition. While MRI provides superior soft-tissue contrast, its role in routine ovarian reserve assessment is limited due to cost and accessibility. The findings indicate that although both modalities are valuable for ovarian reserve evaluation, there is no consensus on standardized imaging parameters for defining ovarian functional viability. The available literature also presents inconsistencies in the correlation between imaging findings and ovarian function.

Conclusion

Ultrasound and MRI are essential tools for assessing ovarian reserve, providing complementary morphological and functional data. However, the lack of standardized imaging parameters limits their ability to definitively determine ovarian functional viability. Further research is needed to establish validated diagnostic criteria and integrate imaging techniques with biochemical markers to enhance the accuracy of ovarian reserve assessment in clinical practice and reproductive research.

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2025-07-22
2025-11-04

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References

  1. Deadmond A. Koch C.A. Parry J.P. Ovarian reserve testing. 2022 Available from: https://my.clevelandclinic.org/health/diagnostics/25142-ovarian-reserve-testing
  2. Penzias A. Azziz R. Bendikson K. Falcone T. Hansen K. Hill M. Hurd W. Jindal S. Kalra S. Mersereau J. Racowsky C. Rebar R. Reindollar R. Shannon C.N. Steiner A. Stovall D. Tanrikut C. Taylor H. Yauger B. Testing and interpreting measures of ovarian reserve: A committee opinion. Fertil. Steril. 2020 114 6 1151 1157 10.1016/j.fertnstert.2020.09.134 33280722
    [Google Scholar]
  3. Greenlee RT Kessel B Williams CR Riley TL Ragard LR Hartge P Buys SS Partridge EE Reding DJ Prevalence, incidence, and natural history of simple ovarian cysts among women> 55 years old in a large cancer screening trial. American J. Obstet. Gynecol. 2010 202 4 373.e1-9 373.e379 10.1016/j.ajog.2009.11.029
    [Google Scholar]
  4. Méduri G. Massin N. Guibourdenche J. Bachelot A. Fiori O. Kuttenn F. Misrahi M. Touraine P. Serum anti-Müllerian hormone expression in women with premature ovarian failure. Hum. Reprod. 2007 22 1 117 123 10.1093/humrep/del346 16954410
    [Google Scholar]
  5. Soules M.R. Sherman S. Parrott E. Rebar R. Santoro N. Utian W. Woods N. Executive summary: Stages of reproductive aging workshop (STRAW). Climacteric 2001 4 4 267 272 10.1080/cmt.4.4.267.272 11770182
    [Google Scholar]
  6. Caroppo E. Matteo M. Schonauer L.M. Vizziello G. Pasquadibisceglie A. Vitti A. D’Amato G. Basal FSH concentration as a predictor of IVF outcome in older women undergoing stimulation with GnRH antagonist. Reprod. Biomed. Online 2006 13 6 815 820 10.1016/S1472‑6483(10)61029‑2 17169202
    [Google Scholar]
  7. Abdalla H. Thum M.Y. An elevated basal FSH reflects a quantitative rather than qualitative decline of the ovarian reserve. Hum. Reprod. 2004 19 4 893 898 10.1093/humrep/deh141 15016786
    [Google Scholar]
  8. Broer S.L. Disseldorp V.J. Broeze K.A. Dolleman M. Opmeer B.C. Bossuyt P. Eijkemans M.J.C. Mol B.W.J. Broekmans F.J.M. Broer S.L. Disseldorp V.J. Broeze K.A. Dolleman M. Opmeer B.C. Anderson R.A. Ashrafi M. Bancsi L. Caroppo L.E. Copperman A. Ebner T. Geva E.M. Erdem M. Greenblatt E.M. Jayaprakasan K. Fenning R. Klinkert E.R. Kwee J. Lambalk C.B. Marca L.A. McIlveen M. Merce L.T. Muttukrishna S. Nelson S.M. Ng H.Y. Popovic-Todorovic B. Smeenk J.M.J. Tomás C. Linden D.V.P.J.Q. Rooij V.I.A. Vladimirov I.K. Bossuyt P.B. Eijkemans M.J.C. Mol B.W. Frank B. Added value of ovarian reserve testing on patient characteristics in the prediction of ovarian response and ongoing pregnancy: An individual patient data approach. Hum. Reprod. Update 2013 19 1 26 36 10.1093/humupd/dms041 23188168
    [Google Scholar]
  9. Leader B. Hegde A. Baca Q. Stone K. Lannon B. Seifer D.B. Broekmans F. Baker V.L. High frequency of discordance between antimüllerian hormone and follicle-stimulating hormone levels in serum from estradiol-confirmed days 2 to 4 of the menstrual cycle from 5,354 women in U.S. fertility centers. Fertil. Steril. 2012 98 4 1037 1042 10.1016/j.fertnstert.2012.06.006 22771028
    [Google Scholar]
  10. Tobler K.J. Shoham G. Christianson M.S. Zhao Y. Leong M. Shoham Z. Use of anti-mullerian hormone for testing ovarian reserve: A survey of 796 infertility clinics worldwide. J. Assist. Reprod. Genet. 2015 32 10 1441 1448 10.1007/s10815‑015‑0562‑7 26347341
    [Google Scholar]
  11. Broer S.L. Dólleman M. Opmeer B.C. Fauser B.C. Mol B.W. Broekmans F.J.M. AMH and AFC as predictors of excessive response in controlled ovarian hyperstimulation: A meta-analysis. Hum. Reprod. Update 2011 17 1 46 54 10.1093/humupd/dmq034 20667894
    [Google Scholar]
  12. Anitha J. Agnes S.A. Appraisal of deep-learning techniques on computer-aided lung cancer diagnosis with computed tomography screening. J. Med. Phys. 2020 45 2 98 106 10.4103/jmp.JMP_101_19 32831492
    [Google Scholar]
  13. Moiseeva A.V. Kudryavtseva V.A. Nikolenko V.N. Gevorgyan M.M. Unanyan A.L. Bakhmet A.A. Sinelnikov M.Y. Genetic determination of the ovarian reserve: A literature review. J. Ovarian Res. 2021 14 1 102 10.1186/s13048‑021‑00850‑9 34362406
    [Google Scholar]
  14. Chakrabarti S. Ovarian reserve analysis in subfertile women based on physical, ultrasound and hormonal parameters. Gynecol. Endocrinol. 2023 39 1 2214616 10.1080/09513590.2023.2214616 37439005
    [Google Scholar]
  15. Rodrigues O.A.R.D. Sá D.R.A. Velarde G.C. Valle M.P. Nóbrega B.N. Roque M. Júnior E.A. Comparing two-and three-dimensional antral follicle count in patients with endometriosis. J. Med. Ultrasound 2022 30 4 282 286 10.4103/jmu.jmu_204_21 36844767
    [Google Scholar]
  16. Bourdon M. Santulli P. Bordonne C. Millisher A.E. Maitrot-Mantelet L. Maignien C. Marcellin L. Melka L. Chapron C. Presence of adenomyosis at MRI reduces live birth rates in ART cycles for endometriosis. Hum. Reprod. 2022 37 7 1470 1479 10.1093/humrep/deac083 35460419
    [Google Scholar]
  17. Zheng S. Rong Y. Zhu H. Zhang X. Liu X. Wu Y. Zhao M. Role of magnetic resonance-high intensity focused ultrasound (MR-HIFU) in uterine fibroids management: An updated systematic review and meta-analysis. Wideochir. Inne Tech. Malo Inwazyjne 2022 17 1 83 94 35251392
    [Google Scholar]
  18. Balachandren N. Kastora S. Yasmin E. Saridogan E. Jurkovic D. Learner H. Mavrelos D. An age-related nomogram for antral follicle counts as a reference guide for reproductive decision making: An observational study of 7573 women. Reprod. Biomed. Online 2024 104295 10.1016/j.rbmo.2024.104295 39288480
    [Google Scholar]
  19. Wang Y. Lu W. Chen Z.H. Xiao Y. Wang Y. Gao W. Wang Z. Song R. Fang Z. Hu W. Molecular imaging of ovarian follicles and tumors with near-infrared II bioconjugates. Adv. Mater. 2024 37 7 2414129 10.1002/adma.202414129 39696888
    [Google Scholar]
  20. Osman N.A. Morgham A.E. Update on assessment of ovarian reserve testing. Obstet. Gynecol. Surv. 2024 79 7 429 435 10.1097/OGX.0000000000001284 39026444
    [Google Scholar]
  21. Andreu A. Flores L. Méndez M. Ibarzabal A. Casals G. Mercadé I. Borrás A. Barral Y. Agustí I. Manau D. Vidal J. Casals G. Impact of bariatric surgery on ovarian reserve markers and its correlation with nutritional parameters and adipokines. Front. Endocrinol. 2024 15 1284576 10.3389/fendo.2024.1284576 38559698
    [Google Scholar]
  22. Maldonado-Cárceles A.B. Souter I. Li M.C. Mitsunami M. Dimitriadis I. Ford J.B. Mínguez-Alarcón L. Chavarro J.E. Antioxidant intake and ovarian reserve in women attending a fertility center. Nutrients 2025 17 3 554 10.3390/nu17030554 39940413
    [Google Scholar]
  23. Bareghamyan H. Chopikyan A. Petrosyan M. Shahverdyan N. Harutyunyan A. Influence of ovarian cysts on ovarian reserve and fertility: A case–control study. Int. J. Gynaecol. Obstet. 2024 165 2 424 430 10.1002/ijgo.15284 38059670
    [Google Scholar]
  24. Zhang Y. Xu Y. Zhang X. Zheng B. Hu W. Yuan G. Si G. 8Spheres conformal microspheres as embolic agents for symptomatic uterine leiomyoma therapy in uterine artery embolization (UAE): A prospective clinical trial. Medicine 2023 102 9 e33099 10.1097/MD.0000000000033099 36862859
    [Google Scholar]
  25. Otonkoski S. Sainio T. Mattila S. Sequieros B.R. Perheentupa A. Komar G. Joronen K. Magnetic resonance guided high intensity focused ultrasound for uterine fibroids and adenomyosis has no effect on ovarian reserve. Int. J. Hyperthermia 2023 40 1 2154575 10.1080/02656736.2022.2154575 36535925
    [Google Scholar]
  26. Buyuk E. Seifer D.B. Illions E. Grazi R.V. Lieman H. Elevated body mass index is associated with lower serum anti-mullerian hormone levels in infertile women with diminished ovarian reserve but not with normal ovarian reserve. Fertil. Steril. 2011 95 7 2364 2368 10.1016/j.fertnstert.2011.03.081 21529798
    [Google Scholar]
  27. Steiner A.Z. Herring A.H. Kesner J.S. Meadows J.W. Stanczyk F.Z. Hoberman S. Baird D.D. Antimüllerian hormone as a predictor of natural fecundability in women aged 30-42 years. Obstet. Gynecol. 2011 117 4 798 804 10.1097/AOG.0b013e3182116bc8 21422850
    [Google Scholar]
  28. Gibreel A. Maheshwari A. Bhattacharya S. Johnson N.P. Ultrasound tests of ovarian reserve; A systematic review of accuracy in predicting fertility outcomes. Hum. Fertil. 2009 12 2 95 106 10.1080/14647270902896256 19802960
    [Google Scholar]
  29. Mutliu M.F. Erdem M. Erdem A. Yildiz S. Mutlu I. Arisoy O. Oktem M. Antral follicle count determines poor ovarian response better than anti-müllerian hormone but age is the only predictor for live birth in in vitro fertilization cycles. J. Assist. Reprod. Genet. 2013 30 5 657 665 10.1007/s10815‑013‑9975‑3 23508679
    [Google Scholar]
  30. Sabek E.A.S. Saleh O.I. Ahmed H.A. Ultrasound in evaluating ovarian reserve, is it reliable? Egypt. J. Radiol. Nucl. Med. 2015 46 4 1343 1348 10.1016/j.ejrnm.2015.08.008
    [Google Scholar]
  31. Jayaprakasan K. Deb S. Batcha M. Hopkisson J. Johnson I. Campbell B. Raine-Fenning N. The cohort of antral follicles measuring 2–6 mm reflects the quantitative status of ovarian reserve as assessed by serum levels of anti-Müllerian hormone and response to controlled ovarian stimulation. Fertil. Steril. 2010 94 5 1775 1781 10.1016/j.fertnstert.2009.10.022 19931077
    [Google Scholar]
  32. Tkachenko L.V. Gritsenko I.A. Tikhaeva K.Y. Sviridova N.I. Gavrilova I.S. Dolgova V.A. Assessing an ovarian reserve and risk factors for premature ovarian failure as part of pre-abortion counseling for women under 40 planning to terminate own first pregnancy. Obstet. Gynecol. Reprod. 2023 17 2 244 251 10.17749/2313‑7347/ob.gyn.rep.2023.369
    [Google Scholar]
  33. McIlveen M. Skull J.D. Ledger W.L. Evaluation of the utility of multiple endocrine and ultrasound measures of ovarian reserve in the prediction of cycle cancellation in a high-risk IVF population. Hum. Reprod. 2007 22 3 778 785 10.1093/humrep/del435 17114197
    [Google Scholar]
  34. Chen W.H. Huang K.H. Kung F.T. Effects of uterine artery occlusion during myomectomy on ovarian reserve: Serial follow-up of sex hormone levels, ultrasound parameters and Doppler characteristics. J. Obstet. Gynaecol. Res. 2020 46 5 752 758 10.1111/jog.14236 32153076
    [Google Scholar]
  35. Arya S. Plavsic K.S. Preimplantation 3D ultrasound: Current uses and challenges. J. Perinat. Med. 2017 45 6 745 758 10.1515/jpm‑2016‑0361 28063264
    [Google Scholar]
  36. Singh V.K. Kalafi Y.E. Cheah E. Wang S. Wang J. Ozturk A. Li Q. Eldar Y.C. Samir A.E. Kumar V. HaTU-Net: Harmonic attention network for automated ovarian ultrasound quantification in assisted pregnancy. Diagnostics 2022 12 12 3213 10.3390/diagnostics12123213 36553220
    [Google Scholar]
  37. Zhao Q. Lyu S. Bai W. Cai L. Liu B. Wu M. Sang X. Yang M. Chen L. A multi-modality ovarian tumor ultrasound image dataset for unsupervised cross-domain semantic segmentation. arXiv:2207.06799 2022 1 6 10.48550/arXiv.2207.06799
    [Google Scholar]
  38. Laputin F. Sidorov I. Moshkin A. Computer vision methods for assessing ovarian reserve. 2024 International Russian Smart Industry Conference (SmartIndustryCon) 2024, pp. 656-661. 10.1109/SmartIndustryCon61328.2024.10515730
    [Google Scholar]
  39. Lee H.J. Usefulness of subtraction pelvic magnetic resonance imaging for detection of ovarian endometriosis. Yeungnam Univ. J. Med. 2020 37 2 90 97 10.12701/yujm.2019.00353 31661751
    [Google Scholar]
  40. Vash-Margita A. Szymanska-Vandendriessche K. Gunther K. Rodriguez-Buritica D.F. Christison-Lagay E. Saluja S. Oktay K.H. Laparoscopic ovarian tissue harvesting for cryopreservation from a child with galactosemia. Fertil. Steril. 2022 118 5 982 984 10.1016/j.fertnstert.2022.08.005 36154768
    [Google Scholar]
  41. Wang S.J. Zhang M.M. Duan N. Hu X.Y. Ren S. Cao Y.Y. Zhang Y.P. Wang Z.Q. Using transvaginal ultrasonography and MRI to evaluate ovarian volume and follicle count of infertile women: A comparative study. Clin. Radiol. 2022 77 8 621 627 10.1016/j.crad.2022.04.016 35636975
    [Google Scholar]
  42. Wang S.J. Duan N. Hu X.Y. Yin Y.Y. Guo Y.H. Wang Y.J. Chen X. Wang Z.Q. Characteristics of magnetic resonance imaging and clinical etiology of ovarian infertility. Zhonghua Yi Xue Za Zhi 2021 101 35 2798 2803 34551497
    [Google Scholar]
  43. Aiyappan S.K. Karpagam B. Vadanika V. Chidambaram P.K. Vinayagam S. Saravanan K.C. Age-related normogram for ovarian antral follicle count in women with polycystic ovary syndrome and comparison with age matched controls using magnetic resonance imaging. J. Clin. Diagn. Res. 2016 10 1 TC11 TC13 10.7860/JCDR/2016/17334.7136 26894142
    [Google Scholar]
  44. Hagen C.P. Fischer M.B. Wohlfahrt-Veje C. Assens M. Busch A.S. Pedersen A.T. Juul A. Main K.M. AMH concentrations in infancy and mid-childhood predict ovarian activity in adolescence: A long-term longitudinal study of healthy girls. EClinicalMedicine 2023 55 101742 10.1016/j.eclinm.2022.101742 36386030
    [Google Scholar]
  45. Pace C. Argirò R. Casadei L. Cesareni M. Orlacchio A. Comparison between X-ray-hysterosalpingography and 3 Tesla magnetic resonance-hysterosalpingography in the assessment of the tubal patency in the cause of female infertility. Radiol. Med. 2022 127 12 1373 1382 10.1007/s11547‑022‑01556‑8 36167884
    [Google Scholar]
  46. Barbosa M.Z. Zylbersztejn D.S. Mattos D.L.A. Carvalho L.F. Three-dimensionally-printed models in reproductive surgery: Systematic review and clinical applications. Minerva Ginecol. 2019 71 3 235 244 10.23736/S0026‑4784.19.04319‑3 30756546
    [Google Scholar]
  47. Nelson S.M. Shaw M. Ewing B.J. McLean K. Vechery A. Briggs S.F. Antimüllerian hormone levels are associated with time to pregnancy in a cohort study of 3,150 women. Fertil. Steril. 2024 122 6 1114 1123 10.1016/j.fertnstert.2024.06.024 38964587
    [Google Scholar]
  48. Kotlyar A.M. Seifer D.B. Ethnicity/race and age-specific variations of serum AMH in women—a review. Front. Endocrinol. 2021 11 593216 10.3389/fendo.2020.593216 33633682
    [Google Scholar]
  49. Bleil M.E. Gregorich S.E. Adler N.E. Sternfeld B. Rosen M.P. Cedars M.I. Race/ethnic disparities in reproductive age: An examination of ovarian reserve estimates across four race/ethnic groups of healthy, regularly cycling women. Fertil. Steril. 2014 101 1 199 207 10.1016/j.fertnstert.2013.09.015 24182412
    [Google Scholar]
  50. Kwee J. Elting M.E. Schats R. McDonnell J. Lambalk C.B. Ovarian volume and antral follicle count for the prediction of low and hyper responders with in vitro fertilization. Reprod. Biol. Endocrinol. 2007 5 1 9 10.1186/1477‑7827‑5‑9 17362511
    [Google Scholar]
  51. Ulrich N.D. Marsh E. Ovarian reserve testing: A review of the options, their applications, and their limitations. Clin. Obstet. Gynecol. 2019 62 2 228 237 10.1097/GRF.0000000000000445 30998601
    [Google Scholar]
  52. Hassan M.H. Reiter E. Razzaq M. Automatic ovarian follicle detection using object detection models. Sci. Rep. 2024 14 1 31856 10.1038/s41598‑024‑82904‑8 39738599
    [Google Scholar]
  53. Yin H. Feng R. Wang S. Rui X. Ye M. Hu Y. Zhong O. Huang J. Wang W. Huo R. Automated follicle counting system(AFCS) using YOLO-based object detection algorithm and its application in the POI model. Biomed. Signal Process. Control 2025 103 107423 10.1016/j.bspc.2024.107423
    [Google Scholar]
  54. Li Y. Jian J. Pickhardt P.J. Ma F. Xia W. Li H. Zhang R. Zhao S. Cai S. Zhao X. Zhang J. Zhang G. Jiang J. Zhang Y. Wang K. Lin G. Feng F. Lu J. Deng L. Wu X. Qiang J. Gao X. MRI-based machine learning for differentiating borderline from malignant epithelial ovarian tumors: A multicenter study. J. Magn. Reson. Imaging 2020 52 3 897 904 10.1002/jmri.27084 32045064
    [Google Scholar]
  55. Jian J. Li Y. Xia W. He Z. Zhang R. Li H. Zhao X. Zhao S. Zhang J. Cai S. Wu X. Gao X. Qiang J. MRI-based multiple instance convolutional neural network for increased accuracy in the differentiation of borderline and malignant epithelial ovarian tumors. J. Magn. Reson. Imaging 2022 56 1 173 181 10.1002/jmri.28008 34842320
    [Google Scholar]
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Integrative Profiling of the Ovarian Reserve Using Ultrasound and MRI Data by Comparative Analysis: A Systematic Review
Bentham Science Publishers ; https://doi.org/10.2174/0109298673377087250624142331
/content/journals/cmc/10.2174/0109298673377087250624142331
/content/journals/cmc/10.2174/0109298673377087250624142331
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  • Article Type:     Review Article
Keywords: Ovarian reserve ; ultrasound female fertility parameters ; MRI ; antral follicles ; follicle characteristics ; ovarian characteristics

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