{"paper_id":"e8a64aac-fb80-4849-8c1f-e89b8dbb5844","body_text":"© 2025 Acta Medica International | Published by Parsvnath Publishing House \n \n811 \n \n  \n \n \nEvaluating the Correlation Between Pelvic Magnetic Resonance Imaging \nand Intra- Operative/Histopathological Findings in Female Infertility at a \nTertiary Care Centre \nVineet Mishra1, Harish Meena2, Neha Gulia3, Gargi Singh3, Paresh Kumar Sukhani4, Neha Sharma2 \n1Associate Professor, Department of Radio -Diagnosis, Mahatma Gandhi Hospital, Jaipur , Rajasthan, India. 23rd Year Resident, Department of Radio -\nDiagnosis, Mahatma Gandhi Hospital, Jaipur , Rajasthan, India. 32nd Year Resident, Department of Radio -Diagnosis, Mahatma Gandhi Hospital, Jaipur , \nRajasthan, India. 4Professor and Head of Department of Radio -Diagnosis, Mahatma Gandhi Hospital, Jaipur , Rajasthan, India. \n \n \n \nBackground: Female infertility has multifactorial pelvic causes, including Müllerian duct anomalies, endometriosis, uterine fibroids, ade nomyosis, and tubal-\nperitoneal disease. Accurate preoperative characterisation  is critical for selecting appropriate management and counselling. Pelvic magnetic resonance imaging \n(MRI) offers high soft-tissue contrast, multiplanar capability, and comprehensive assessment of uterine, ovarian, and adnexal pathology. This study is designed to \nevaluate how well pelvic MRI findings align with intra -operative and/or histopathological (IO/HP) findings in women with infertility at a tertiary care cent re. \nMaterial and Methods: Setting and design: Prospective observational study at Mahatma Gandhi Medical College and Hospital, Jaipur, following institutional \nethics approval and written informed consent. Population: All women meeting the WHO criteria for infertility referred for MRI  work-up. Study period: October \n2021 to October 2024. Imaging protocol: Pelvic MRI on a 3.0 T Siemens Vida (S.No. 175971). Core sequences included axial T1 -weighted, axial T2-weighted, \naxial STIR, sagittal T2-weighted, coronal T1-weighted, and diffusion-weighted imaging (DWI) with corresponding ADC maps, per standardised pelvic protocols. \nClinical data collection: Detailed history and relevant laboratory/clinical parameters were recorded. Reference standards: IO findings and/or histopathology, where \navailable, served as the gold standard for correlation. Outcomes: Diagnostic concordance measures (e.g., sensitivity, specificity, accuracy, and agreement) for key \netiologies of infertility were planned.  Results: MRI evaluation of 50 patients revealed a total of 66 pathologies, with the most common findings being \nMüllerian duct anomalies (31.82%), fibroids (27.27%), polycystic ovarian syndrome (10.61%), hydrosalpinx (7.58%), and both endometrial polyps and \nendometriosis (9.09% each). When correlated with operative findings, MRI demonstrated excellent diagnostic accuracy. For fibroids, the sensitivity was \n100%, specificity 88.9%, and overall accuracy 92%. In endometriosis, MRI achieved a sensitivity of 83%, specificity of 100%, and accuracy of 98%, while \nin polycystic ovarian syndrome, sensitivity reached 87.5% with 100% specific ity and 98% accuracy. Remarkably, for Müllerian duct anomalies, \nendometrial polyps, and hydrosalpinx, MRI showed perfect diagnostic performance with 100% sensitivity, specificity, and accur acy. Conclusion: MRI \nshould be prioritised in complex or inconclusive infertility evaluations. It excels in soft tissue resolution and multiplanar anatomical detail. MRI exhibits exceptional \ndiagnostic accuracy and agreement with operative and histopathological findings in evaluating primary female infertility. \nKeywords: Infertility, Pelvic MRI, Histopathology, Female, Correlation. \n \nReceived: 18 August 2025 Revised: 22 September 2025 Accepted: 30 October 2025 Published: 17 November 2025  \n \nINTRODUCTION  \nWHO defines infertility as a disease of the male or female \nreproductive system, marked by failure to achieve pregnancy \nafter ≥12 months of regular, unprotected intercourse. [1] \nCauses include fallopian tube damage, ovulatory or \nfertilisation problems, and hormonal disorders. For many \nwomen, difficulty conceiving causes significant physical and \npsychological distress.[2] \nInfertility is classified as primary or secondary. Primary \ninfertility is the inability of a couple to conceive after at least \none year of regular, unprotected intercourse, with no prior \npregnancies or live births. Secondary infertility is the \ninability to conceive after one year of unprotected intercourse \ndespite a previous pregnancy, with some studies extending \nthis to two years. \nFemale infertility has several causes, with ovulatory \ndisorders being the most common. Polycystic ovarian \nsyndrome (PCOS) leads to irregular or absent ovulation and \nis linked to insulin resistance and metabolic syndrome. [3] \nOvarian insufficiency (prem ature ovarian failure) causes \nearly loss of ovarian function before age 40, while luteal \nphase deficiency results from hormonal imbalances that impair \nimplantation.[4] \nFallopian tube obstruction, often due to infections or \ninflammation, prevents egg and sperm from meeting or embryo \ntransport.[5] Endometriosis, where endometrial tissue grows \noutside the uterus, causes pelvic pain and infertility by disrupting \novulation and implantation.[6] Uterine abnormalities like fibroids, \npolyps, adenomyosis, or intrauterine adhesions can block \nimplantation or cause pregnancy loss. \nMagnetic Resonance Imaging (MRI) effectively delineates \npelvic morphology and orientation. It is non -invasive and \n \n \nAddress for correspondence: Dr. Harish Meena, \n3rd Year Resident, Department of Radio-Daignosis, Mahatma Gandhi Hospital, \nJaipur, Rajasthan, India. \nE‑mail: harish.meena.24@gmail.com  \n \nDOI: \n10.21276/amit.2025.v12.i3.182 \n \nHow to cite this article:  Mishra V, Meena  H, Gulia  N, Sukhani  PK, Sharma  N. \nEvaluating the Correlation Between Pelvic Magnetic Resonance Imaging and Intra - \nOperative/Histopathological Findings in Female Infertility at a Tertiary Care Centre . \nActa Med Int. 2025;12(3):811-815. \n\nActa Medica International ¦ Volume 12 ¦ Issue 3 ¦ September-December 2025 \n \n812 \n Vineet Mishra et al; Correlation of Pelvic MRI with Intraoperative and Histopathological Findings in \nFemale Infertility \n \n \nradiation-free, but limited by high cost, restricted \navailability, and long examination time, making repeat \nstudies difficult. Limitations include poor detection of sub -\ncentimetre uterine lesions and difficulty characterising \nendometriomas at certain stages. MRI is  contraindicated in \npatients with pacemakers or cochlear implants. Despite these \ndrawbacks, MRI is valuable in detecting pathological \nconditions such as tubal lesions and pituitary adenomas. It \nalso aids in assessing prognosis and treatment planning in \nconservatively managed cases of leiomyoma, adenomyosis, \nand endometriosis.[7] \n \nMATERIALS AND METHODS \nThis is a retrospective and prospective observational study \ncomprising all female patients who came to Mahatma Gandhi \nHospital, Jaipur, for infertility evaluation and underwent \ndiagnostic/therapeutic operative procedures from October \n2021 to October 2024. They were evaluated using MRI \npelvis, and the findings were correlated with intraoperative \nand histological findings wherever possible. \nPatients were ma de aware of the purpose of the study and \nwere selected only after their written consent. Symptoms \nsuch as pelvic pain, dysmenorrhoea, etc., were noted. A \nserum HCG test was done before the examinations. MRI \npelvis was performed on a 3.0 T (Siemens Vida S.n o \n175971). [Table 1] \nInclusion criteria & Exclusion criteria: \nA female patient with infertility was referred to our \ndepartment for an MRI of the pelvis and underwent a \ndiagnostic/therapeutic operative procedure with or without \nproviding a histopathological sample for the same. Patients \nwho do not give consent and patients with contraindications \nfor MRI were excluded. \nInstitute ethical committee approval was obtained before \nstarting of study. Approval \nNo./MGMC&H/IEC/JPR/2023/1421. \nMethodology \nMRI: MRI Pelvis was performed on a 3.0 T (Siemens Vida \nS.no 175971). \n \nRESULTS \nThis study aimed to evaluate the diagnostic accuracy of \npelvic MRI in comparison with intra -operative or \nhistopathological findings among female patients with \ninfertility. \nDescriptive Profile: Most patients were between 21 and 35 \nyears, with the highest proportion (36%) in the 31 -35 age \ngroup. \nPelvic MRI findings showed Mullerian duct anomalies in 21 \ncases (31.82%), Fibroids in 18 cases (27.27%), PCOS in 7 \ncases (10.61%), En dometrial polyps in 6 cases (9.09%), \nEndometriosis in 6 cases (9.09%), Hydrosalpinx in 5 cases \n(7.58%), and Adenomyosis in 3 cases (4.55%). Note: \nFindings/pathology overlapped in 15 cases. [Table 2] \nAnomaly distribution : Mullerian agenesis was seen in 11 \ncases (22%), bicornuate uterus was seen in 4 cases (8%), septate \nuterus was seen in 4 cases (8%), hypoplastic uterus was seen in \n1 case (2%), absent uterus was seen in 1 case (2%), and 29 cases \nwere normal. [Table 3] \nHormonal Profiles and Reproductive Characteristics \n• Most patients showed luteal phase dominance in progesterone \nprofiles. \n• Patients with PCOS showed increased AMH levels. Prolactin \nand androgen levels varied widely. \n• 54% of patients had diabetes, and thyroid abnormalities were \nseen in 44% of cases. \n• Vaginal discharge (64%) was frequently observed. \nMenstrual and Infertility Patterns \n• 54% of patients had irregular cycles. Cycle lengths most \ncommonly ranged from 28 to 35 days. \n• The d uration of infertility was most frequently between 16 \nand 25 months. \n• Heavy (32%) and light (34%) menstrual flow were more \ncommon than normal. \nCompartmental Involvement: \n• Middle compartment (uterus): Highest involvement \n• Posterior compartment (rectouterine pouch): Often in \nendometriosis \n• Anterior compartment: Least affected \nDiagnostic Accuracy: \n1. Müllerian Duct Anomalies (MDA): Out of 21 cases, only 8 \nrequired surgical intervention, while the rest were medically \nmanaged. Operative and histopathology findings were in line \nwith MRI findings in all 8 cases. [Figure 1a & 4b, 2a,b &c, & \n3a &b] \n2. Fibroid: Out of 18 cases, 14 were confirmed postoperatively; \nin the rest of the cases, the findings were not in line with MRI. \n[Figures 4 & 5] \n3. PCOS: Out of 7 cases, only 2 needed surgical intervention \nrest were medically managed. Operative and histopathology \nfindings were in line with MRI findings in both cases. \n4. Endometrial Polyp:  In all 6 cases, the MRI findings were \nconfirmed postoperatively, with histopathology also \nconfirming the diagnoses of endometrial polyps. \n5. Endometriosis: Out of 6 cases , 5 were confirmed \npostoperatively; in the rest of the cases, the findings were not \nin line with MRI. [Figure 6] \n6. Adenomyosis: In all 3 cases, the MRI findings were \nconfirmed postoperatively, with histopathology also \nconfirming the diagnoses of Adenomyosis. [Figure 7] \n7. Hydrosalpinx: In all 5 cases, the MRI findings were \nconfirmed laparoscopically.  \nMRI showed outstanding performance with: \n• MDA, Polyps, Hydrosalpinx:  All 100% in sensitivity, \nspecificity, and accuracy \n• Fibroids: Sensitivity 100%, Specificity 88.9%, Accuracy \n92% \n• PCOS: Sensitivity 87.5%, Specificity 100%, Accuracy 98% \n• Endometriosis: Sensitivity 83%, Specificity 100%, \nAccuracy 98%. \n \n\nActa Medica International ¦ Volume 12 ¦ Issue 3 ¦ September-December 2025 \n \n813 \n Vineet Mishra et al; Correlation of Pelvic MRI with Intraoperative and Histopathological Findings in \nFemale Infertility \n \n \nTable 1: MRI Sequences \nAxial T2 and T1 TSE AXIAL 6 MM LARGE FOV \nT2 TSE AXIAL OBLIQUE 3MM SFOV OF UTERUS \nT1 TSE FAT SAT AXIAL OBLIQUE 3MM SFOV OF UTERUS \nDWI EPI3SCAN TRACE AXIAL 3MM SFOV \nSagittal:  T2 TSE SAGITTAL 3MM SFOV \nT1 VIBE DIXON 3D SAGITTAL DYNAMIC 1 PRE & POST \nCoronal:  T2 STIR CORONAL 5 MM LARGE FOV \nT2 TSE CORONAL OBLIQUE 3MM SFOV OF UTERUS \n \nTable 2: MRI pathologies \nType of MRI Pathology Frequency (n) Percentage (%) \nAdenomyosis 3 4.55 \nEndometrial polyp 6 9.09 \nFibroids 18 27.27 \nHydrosalpinx 5 7.58 \nPCOS 7 10.61 \nMullerian duct anomaly 21 31.82 \nEndometriosis  6 9.09 \nGrand Total 66 100 \n \nTable 3: Anomalies Distribution \nAnomalies  Frequency(n) Percentage(%) \nAbsent Uterus 1 2 \nBicornuate 4 8 \nHypoplastic uterus 1 2 \nMüllerian agenesis 11 22 \nNormal 29 58 \nSeptate 4 8 \nGrand Total 50 100 \n \n \nFigure 1: Axial T2W MRI Images reveal – non-visualization of \nuterus with rudimentary uterine buds and fibrous tissue (red \narrows). Bilateral ovaries are high located in the bilateral iliac \nfossa regions (blue arrows). \n \n \nFigure 2: Imaging findings suggestive of a bicornuate bicollis \nuterus with obstructed right hemi -vagina and ipsilateral right \nrenal agenesis—Obstructed hemi-vagina with ipsilateral renal \nagenesis (OHVIRA syndrome) \n \n \nFigure 3: a  & b-Axial T2W section sho ws left unicornuate uterus \n(arrow showing left horn). Axial T2W image with absent right \nkidney and empty right renal fossa and maldescended right ovary \nin the right lumbar region posterior to the fossa (yellow arrow) \n\n\nActa Medica International ¦ Volume 12 ¦ Issue 3 ¦ September-December 2025 \n \n814 \n Vineet Mishra et al; Correlation of Pelvic MRI with Intraoperative and Histopathological Findings in \nFemale Infertility \n \n \n \nFigure 4: T2W sagittal and axial sections showing \nheterogeneous signal intensity mass in the anterior body and \nfundus of the uterus, showing few STIR hyperintense cystic \nareas within the mass, which is displacing the endometrium \nposteriorly. It is reaching till the serosal surface, causin g its \nbulge- [likely FIGO 2-5] \n \n \nFigure 5: Laparoscopic view of multiple uterine fibroids. \n \n \nFigure 6: T2W Axial and Sagittal images showing a hypointense \nlesion in the right ovary, which is closely abutting the torus \nuterinus and showing T2 shading suggestive of deep pelvic \nendometriosis (blue arrow). T1FS axial image showing a T1 \nhypointense focus in the left ovary (yellow arrow) -Suggestive of \ndeposits \n \nFigure 7: Post-operative section of an Adenomyotic uterus. \n \nDISCUSSION \nThis study explores the diagnostic utility of MRI pelvis in \nevaluating primary female infertility by comparing its findings \nwith intraoperative, histopathological, and hormonal data. \nMRI has evolved into a highly valuable diagnostic modality. It \noffers no n-invasive, radiation -free imaging, an important \nadvantage for women of reproductive age. With advances such \nas phased-array coils, MRI achieves excellent spatial resolution, \nsuperior tissue contrast, and multiplanar imaging, making it ideal \nfor assessing pelvic anatomy, particularly the morphology and \norientation of reproductive structures. \nVictoria Wu et al. (2022) in their study concluded that Pelvic \nMRI can be helpful in the workup of female infertility, \nparticularly in cases of Müllerian duct anomalies , fibroids, \nadenomyosis, endometriosis, and tubal disease.[8] \nNa Liu et al. (2021) conducted a study to explore the diagnostic \nvalue of MRI image features based on a convolutional neural \nnetwork for tubal unobstructed infertility in 30 infertile female \npatients. They found that the accuracy of MR -HSG was 33.33% \nand the accuracy of MRI was 46.67%. [9] \nGrover SB et al  (2020) in their study stated that Uterine filling \ndefects and contour abnormalities may be discovered at HSG but \nusually require further char acterization with pelvic ultrasound \n(US), sono-hysterography or pelvic magnetic resonance imaging \n(MRI), when US remains inconclusive. The major limitation of \nhysterographic US is its inability to visuali ze extraluminal \npathologies, which pelvic we and MRI better evaluate. Although \npelvic US is a valuable modality in diagnosing entities \ncomprising the garden variety, extensive pelvic inflammatory \ndisease, complex tubo -ovarian pathologies, deep -seated \nendometriosis deposits with its related complications, Mu llerian \nduct anomalies, uterine synechiae, and adenomyosis often \nremain unresolved by both transabdominal and transvaginal \nUS.[10] \nThe study highlights MRI as a robust diagnostic modality for \nidentifying fibroids, Müllerian duct anomalies (MDA), polyps, \n\n\nActa Medica International ¦ Volume 12 ¦ Issue 3 ¦ September-December 2025 \n \n815 \n Vineet Mishra et al; Correlation of Pelvic MRI with Intraoperative and Histopathological Findings in \nFemale Infertility \n \n \nendometriosis, polycystic ovary syndrome (PCOS), and \nhydrosalpinx. MRI demonstrated 100% accuracy in \ndiagnosing MDA, endometrial polyps, and hydrosalpinx, \nwith over 92% accuracy for all other pathologies. Hormonal \nprofiles confirmed luteal phase hormone elev ation, elevated \nandrogens, and variable prolactin levels, which are \ncommonly observed in PCOS cases. MRI showed strong \nagreement with intraoperative findings in diagnostic \naccuracy. Socioeconomic and lifestyle variables did not have \na statistically significant impact on the duration of infertility. \nCompartmental MRI analysis enabled precise anatomical \nmapping, facilitating targeted clinical or surgical \nmanagement. Notably, 46% of patients proceeded to surgery \nbased on MRI findings, underscoring its valuable role in pre-\nintervention planning. Overall, the study confirms MRI as a \nmulti-utility diagnostic tool capable of simultaneously \nassessing uterine, tubal, ovarian, and anatomical \ncompartments in a single, non-invasive scan. \n \nCONCLUSION \nMRI should be priori tised in complex or inconclusive \ninfertility evaluations. It excels in soft tissue resolution and \nmultiplanar anatomical detail. MRI exhibits exceptional \ndiagnostic accuracy and agreement with operative and \nhistopathological findings in evaluating primary female \ninfertility. Its ability to detect fibroids, PCOS, hydrosalpinx, \nendometrial polyps, and Müllerian duct anomalies makes it \nan indispensable tool in modern infertility workups. Given its \nnon-invasive nature, superior tissue resolution, and high \nnegative predictive value, MRI should be considered a \nfrontline modality, particularly in complex or inconclusive \ninfertility cases. \n \nFinancial support and sponsorship \nNil.  \n \nConflicts of interest  \nThere are no conflicts of interest. \n \nREFERENCES \n1. WHO. Infertility definition and prevalence. World Health \nOrganization; 2020. \n2. Zegers-Hochschild F, Adamson GD, Dyer S, et al. The International \nGlossary on Infertility and Fertility Care, 2017. Hum Reprod. \n2017;32(9):1786–1801. \n3. Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES, Yildiz \nBO. The prevalence and features of the polycystic ovary syndrome \nin an unselected population. J Clin Endocrinol Metab. \n2004;89(6):2745–2749. \n4. Coulam CB. Premature ovarian failure. Fertil Steril. \n1982;38(6):645–655. Guideline No. 17. 2011. \n5. Shokeir T. Structures of the uterus and fallopian tubes. In: Clinical \nGynecology. Elsevier; 2015. \n6. Vercellini P, Viganò P, Somigliana E, Fedele L. Endometriosis: \npathogenesis and treatment. Nat Rev Endocrinol. 2014; 10(5):261–\n275. \n7. Dueholm M. Transvaginal sonography and MRI for diagnosing \nadenomyosis: a review. Fertil Steril. 2006;95(8):2194–2201. \n8. Wu V, Hong W, Suh B, et al. Pelvic MRI in infertility workup. AJR \nAm J Roentgenol. 2022;219(3):627–638. \n9. Liu N, Zhang Y, Wan g J, et al. CNN -based MR -HSG for tubal \ninfertility. Biomed Eng Online. 2021;20(1):51. \n10. Grover SB, Shankar S, Godara R, et al. MR in pelvic infertility \nevaluation. J Clin Imaging Sci. 2020;10:41.","source_license":"CC0","license_restricted":false}