{"paper_id":"07fc56eb-2203-4af9-9640-8ba28a719e4f","body_text":"Copyright © 2024 Korean Society of Magnetic Resonance in Medicine  1\nwww.i-mri.org\nINTRODUCTION\nEndometriosis occurs in 6%–10% of reproductive-age females [1,2]. Approximately \n30%–50% of females with endometriosis are infertile and 25%–50% of infertile females \nReceived: November 11, 2019\nRevised: January 17, 2020 \nAccepted: January 21, 2020\nCorrespondence\nHyun Jung Lee, MD, PhD\nDepartment of Obstetrics and \nGynecology, School of Medicine \nKyungpook National University, \n130 Dongdeok-ro, Jung-gu, \nDaegu 41944, Korea.\nE-mail: hyunjunglee@knu.ac.kr\nThis is an Open Access article distributed \nunder the terms of the Creative Commons \nAttribution Non-Commercial License \n(http://creativecommons.org/licenses/\nby-nc/4.0/) which permits unrestricted \nnon-commercial use, distribution, and \nreproduction in any medium, provided \nthe original work is properly cited.\nOriginal Article \neISSN 2384-1109\niMRI 2024;28(1);1-7\nhttps://doi.org/10.13104/imri.2019.1030\nHistographic Analysis of Magnetic \nResonance Imaging for the Evaluation \nof Ovarian Endometrial Invasion\nHyun Jung Lee\nDepartment of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, \nDaegu, Korea\nPurpose: The purpose of this study was to evaluate the effectiveness of histographic \nanalysis for the perfusion map of pelvic magnetic resonance imaging (MRI) in predicting \nremnant ovarian tissue in patients with ovarian endometriosis.\nMaterials and Methods: To generate the perfusion map, subtracted T1-weighted image \n(T1-WI) was divided by contrast enhanced T1-WI with using image analysis software Im-\nageJ. Each region of interest (ROI) was quantified by outlining of the affected ovaries \nwith endometrioma at the level with the largest area of normal ovary tissue and normal \ncontralateral ovaries using the measurement tool on the software. Consequently, the \nnumber of ratios per each pixel comprising the perfusion map was scored from 0 (not \nperfused) to 1 (totally perfused). The pixel information, including area within ROI, mean \nwith standard deviation of signal intensity, as well as integrated density of affected ovary \nwith endometrioma, were compared with that of the normal ovary. Additionally, we com-\npared the histogram according to the severity of the ovarian invasion. \nResults: In comparison between the affected ovary with endometrioma and the normal \novary, the perfusion ratio of the normal ovary was higher than that of the affected ovary \n(0.48 ± 0.07 vs. 0.20 ± 0.12, p < 0.001), whereas the area within the ROI and the perfusion \nratio was higher in the affected ovary. According to the severity of the endometrial inva-\nsion of the ovary based on the surgical findings, the area with the perfusion ratio between \n0.4 and 0.8 (199.17 ± 163.15 vs. 528.00 ± 154.43, p = 0.003), perfusion ratio (0.11 ± 0.07 vs. \n0.27 ± 0.11, p = 0.012), and, and integrated density (187.33 ± 106.32 vs. 427.125 ± 132.24, p = \n0.003) was lower in the group of severe invasion than those of the mild group and moderate \ninvasion group.\nConclusion: The histographic analysis for the perfusion map of the pelvic MRI could be \nvaluable in revealing the extent of the endometrial invasion and viable remnant ovarian \ntissue.\nKeywords: Endometriosis; Ovary; Histogram; Magnetic resonance imaging\n\n\n2\nwww.i-mri.org\nMR Histogram for Ovarian Endometriosis | Hyun Jung Lee\nhave endometriosis [3]. Recently, patients with the ovarian \nendometrioma want to preserve the ovarian function by min-\nimizing damage to the remnant healthy ovarian tissue during \novarian cystectomy for endometriosis. Thus, the surgeon must \nconsider the remnant ovarian tissue from invasion of endo -\nmetriosis to avoid its destruction with coagulation or disrup-\ntion of the ovarian blood supply during the appropriate surgi-\ncal approach [4]. However, it is difficult to determine the \ndegree of invasion of endometriosis from stretching of the sur-\nrounding tissues, because of the presence of cysts with inflam-\nmatory changes of endometriosis [5].\nRecently, clinical data have been used to develop a clinical \ntool to predict an infertile probability of pregnancy after sur-\ngery. The revised American Fertility Society classification (rAFS \nclassification), the most widely used staging system of endo-\nmetriosis, is used to predict the recurrence potential of endo-\nmetriosis after surgery [6,7]. As the rAFS classification has \nlimited predictive ability for pregnancy after surgery, the en-\ndometriosis fertility index (EFI) was proposed to predict fecun-\ndity after endometriosis surgery [8]. In addition to providing a \ndetailed score including fallopian tubes, fimbriae of fallopian \ntubes, and ovaries by calculating the least function scores, the \nEFI also combines conception related factors such as age, du-\nration of infertility, and gravidity history. However, it could \nonly be performed during surgery. Also, the reliability of the \nresults is presented in question as a subjective evaluation \nmethod according to the operator. Thus, the need for preoper-\native imaging to assess ovarian tissue around the endometrio-\nsis is raised to minimize damage to the ovarian reserve. \nTypical magnetic resonance imaging (MRI) features of ovari-\nan endometriosis include a high signal intensity on T1-weight-\ned images (T1-WIs) and T2-WIs [9,10]. However, chronic \nbleeding has led to high concentration of iron and protein in the \nendometrial cysts, resulting in gradual changes in signal intensi-\nty, making it difficult to identify ovarian tissue in hemorrhagic \nendometrial lesions [9,11,12]. However, it is mandatory for the \nsurgeon, who wants to perform ovary preserving surgery, to con-\nsider the remnant ovarian tissue and endometriosis involving \nthat area, to avoid its destruction with blood coagulation or \ndisruption of the ovarian vessel while using the appropriate sur-\ngical approach [4]. In this situation, the subtraction imaging \nmay be valuable in determination of displacing the ovarian \ntissue from the endometriosis. After subtraction, native T1 \nsignals disappear, and the remaining signals are from the en-\nhancement associated with the intravenous contrast adminis-\ntration mainly [13-15]. Also, analysis for the contrast enhance-\nment effect after the normalization of each image could \ncharacterize the different perfusion pattern between the endo-\nmetrial tissue and remnant ovarian tissue [16]. \nIn this study, a perfusion map was obtained by dividing the \nsubtracted T1-WI with contrast enhanced T1-WI to evaluate \nthe effect of contrast enhancement. In contrast to the poorly \nperfused endometrial cyst, regardless T1 high signal intensity, \nremnant ovarian tissue could show well perfused. Additionally, \nthe histographic analysis could estimate the extent of viable \nremnant tissue quantifiably. Consequently, the purpose of this \nstudy was to evaluate the effectiveness of the histographic \nanalysis for the perfusion map of the pelvic MRI in predicting \nremnant ovarian tissue in patients with ovarian endometriosis. \nMATERIALS AND METHODS\nRetrospective data collection and analysis were approved \nby the Institutional Review Board of Kyungpook National \nUniversity Hospital (KNUH 2017-06-012). The need for in -\nformed consent was waived due to the retrospective design \nof this study. Eight patients had stage III endometriosis, and \n6 patients had stage IV endometriosis. All of patients under-\nwent laparoscopic ovarian cystectomy. Endometriosis was \nclassified based on the revised American Society for Repro -\nductive Medicine classification [7]. The final diagnosis was \nobtained based on the pathological examination of the surgi-\ncally excised specimen of the lesion. \nBefore MRI examination, the patients underwent 6 hours of \nfasting, followed by an intramuscular administration of a peri-\nstaltic inhibitor. MRI examinations were performed on a 3.0-T \nmachine (Skyra; Siemens Health Care, Erlangen, Germany). We \nused a set of 8-channel phased array coils dedicated to different \nbody parts included in this study. MRI scans were interpreted on \na picture archiving and communications system workstation \n(PiViewStar; INFINITT, Seoul, Korea) to identify endometriosis. An \nauthor (HJL) qualitatively analyzed all MRI scans for ovarian en-\ndometriosis blinded to any information on clinical details. \nTo generate the subtracted T1-WI, T1-WI and contrast en-\nhanced T1-WI were performed with similar parameters, such as \nfield of view, slice thickness, repetition time, echo time, and fat \nsuppression. Subtraction images were obtained after intrave-\nnous contrast injection to assess the presence of enhancement \nfor adequate depiction of these lesions. To evaluate the effect \nof contrast enhancement, a perfusion map was obtained by di-\nviding subtracted T1-WI with contrast enhanced T1-WI using \nthe digital image analysis software ImageJ (version 1.47q; Na-\ntional Institutes of Health, Bethesda, MD, USA). Consequently, \nthe number of ratios per each pixel composing perfusion map \nwas scored from 0 (not perfused) to 1 (totally perfused) (Fig. 1).\nEach region of interest (ROI) was quantified by outlining of \naffected ovaries with endometrioma at the level with the larg-\nest area of normal ovary tissue and normal contralateral ova-\nries using the measurement tool on the software. Finally, the \n\n3\nwww.i-mri.org\nhttps://doi.org/10.13104/imri.2019.1030\nhistogram for the perfusion map was produced for the evalu-\nation of the enhancement effect of endometriosis and normal \novarian tissue (Bins = 100). The enhancement degree was \nclassified into poor (perfusion ratio lesser than 0.2), mild (per-\nfusion ratio between 0.2 and 0.4), moderate (perfusion ratio \nbetween 0.4 and 0.8), and high enhancement (perfusion ratio \ngreater than 0.8). The pixel information, including area, mean \nwith standard deviation of signal intensity, as well as integrated \ndensity of affected ovary with endometrioma, was compared \nwith that of the normal ovary. The integrated density, the sum \nof all the pixel intensities in the ROI, expect total amount of \ncontrast enhancement effect in this study. Additionally, we \ncompared histogram according to severity of ovarian invasion \nbased on EFI [8]. \nStatistical analyses were performed using SPSS version 13.0 \nfor Windows (SPSS Inc., Chicago, IL, USA). The Student’s t-test \nwas used to examine the difference in numerical variables. Sta-\ntistical significance was set at a p-value < 0.05.\nRESULTS\nDemographic, clinical, and laboratory characteristics of 14 \npatients with surgically confirmed ovarian endometriosis are \nsummarized in Table 1. The mean age was 28.21 ± 5.71 years. \nThere were no statistically significant differences between the \nrAFS classification III and IV with regards to age, birth history, \nbody mass index (BMI), C reactive protein, anti-Müllerian hor-\nmone, or least function score of ovary in EFT. EFI score was higher \nin rAFS classification III than IV (p = 0.008). \nThe normal ovary was defined in all patients. On T2-WI, the \nnormal ovary showed cysts of varying sizes surrounded by the \ndarker solid ovarian stromal tissue at the level of the maxi -\nmum ovarian diameter and bright cysts surrounded by the \nFig. 1. Analysis of the histogram of the normal ovary. A: The normal ovary shows bright cysts surrounded by the darker solid ovarian stroma \non T2-WI. B: Contrast enhanced T1-WI shows intense enhancement of stroma, which is a more prominent contrast to the subtracted follicular \ncyst. C: The contrast enhanced TI-WI is subtracted by the unenhanced T1-WI to yield the subtracted T1-WI. D: The perfusion map is obtained \nby dividing the subtracted T1-WI (C) with the contrast enhanced T1-WI (B). E: The histogram for the perfusion map for the normal ovary shows \nthe perfusion ratio of 0.40 to 0.80 of 70.3% ± 20% of included pixels. T1-WI, T1-weighted image; T2-WI, T2 weighted image.\n35\n30\n25\n20\n15\n10\n5\n0\nNo of pixels\n0                 0.2                 0.4                 0.6                 0.8                 1.0\nPerfusion ratio\nA\nC\nB\nD E\nTable 1. Demographic, clinical, and laboratory characteristics of study \nsubjects\nrAFS classification pIII (n = 8) IV (n = 6)\nAge (yr) 26.88 ± 4.49 30.00 ± 7.07 0.331 \nG + P + A ≥ 1, n (%) 1 (12.5) 1 (16.7) 0.692 \nBMI 20.00 ± 2.16 18.85 ± 2.32 0.357 \nCRP 0.47 ± 0.81 0.02 ± 0.02 0.159 \nAMH 11.12 ± 7.12 5.65 ± 2.39 0.074 \nDiameter of endometrioma 53.75 ± 33.83 48.33 ± 24.91 0.302 \nEFI 8.00 ± 0.76 6.33 ± 1.21 0.008 \nLeast function score for ovary 1.75 ± 1.04 1.50 ± 0.55 0.603 \nValues are presented as mean ± standard deviation unless otherwise indicat-\ned. G + P + A, gravidity, parity and abortion.  \nrAFS, revised American Fertility Society; III, stage III endometriosis; IV, stage \nIV endometriosis; BMI, body mass index; CRP, C-reactive protein; AMH, anti-\nmüllerian hormone; EFI, endometriosis fertility index.\n\n4\nwww.i-mri.org\nMR Histogram for Ovarian Endometriosis | Hyun Jung Lee\ndarker solid ovarian stroma. The histogram for the normal \novary was measured in all patients. At the level of largest area, \nthe normal ovary showed 350 mm2 of area and 0.48 ± 0.07 of \nperfusion rate. Perfusion rates in 70.3% ± 20% of pixels from \nnormal ovaries ranged from 0.40 to 0.80 (Fig. 1). \nAccording to the EFI classification, 1 case was classified into \nmild, 7 cases were into moderate, and 6 cases were classified \ninto severe, which was correlated with the MRI. Although the \nMRI of ovarian endometriosis showed variable signal intensi-\nties on T1-WI and T2-WI, the cystic lesion of endometriosis \nshowed lesser than 0.1 perfusion ratio (Fig. 2). In comparison \nbetween the affected ovary by endometriosis and the contra-\nlateral normal ovary, perfusion ratio of normal ovary was \nhigher than that of endometriosis (0.48 ± 0.07 vs. 0.20 ± 0.12, \np < 0.001), whereas area within the ROI and perfusion ratio \nwas higher in the affected ovary (Table 2). According to the \nseverity of the endometrial invasion of the ovary based on the \nsurgical findings, the area with perfusion ratio between 0.4 \nand 0.8 (199.17 ± 163.15 vs. 528.00 ± 154.43, p = 0.003), per-\nfusion ratio (0.11 ± 0.07 vs. 0.27 ± 0.11, p = 0.012), and integrat-\ned density (187.33 ± 106.32 vs. 427.125 ± 132.24, p = 0.003) \nwas lower in the endometriosis in group of severe invasion than \nthose of mild and moderate invasion group (Fig. 3 and Table 3).\nDISCUSSION \nAlthough ultrasonography (US) is the main modality of \nchoice for identifying and characterizing adnexal cystic le -\nsions, MRI is performed in selected patients according to the \nresults of US and the severity of symptoms [9,17,18]. MRI is \ngenerally performed to exclude malignancies in cases of in -\ntermediate US features of ovarian masses [10,19,20]. Typical \nMRI findings of endometriosis include a high signal intensity \non T1-WI and T2-WI [9,10]. As data are limited on gadolinium \nenhancement in the evaluation of endometriosis, contrast en-\nhancement could be recommended in the evaluation of inde-\nterminate adnexal endometriosis, such as for distinction from \nA B C\nTable 2. Comparison of histogram analysis between affected ovary by endometriosis and contralateral normal ovary\nAffected ovary by endometriosis Contralateral normal ovary p*\nArea (mm2) 2100.86 ± 1315.10 350.07 ± 138.08 < 0.001\n0 < perfusion ratio < 0.2 1402.57 ± 1288.86 30.93 ± 35.56 0.001\n0.2 < perfusion ratio < 0.4 141.14 ± 77.82 50.86 ± 30.58 0.001\n0.4 < perfusion ratio < 0.8 387.07 ± 227.15 246.79 ± 124.10 0.026\nPerfusion ratio 0.20 ± 0.12 0.48 ± 0.07 < 0.001\nIntegrated density 324.36 ± 170.08 167.21 ± 67.89 0.004\n*Paired t-test.\nFig. 2. The ROI (dashed line) for each stage of endometrial invasion of the ovary. A: Poorly perfused cystic endometriosis (e) is detected \nwithin the ovary, outlined by the ROI (dashed line), preserving the ovarian stroma regarded as minimal invasion. B: The enlarged endometrial \ncyst (e) displaced normal stroma (arrow) with structural distortion. C: Severe endometrial invasion stretches the normal ovarian stroma (arrow) \nwith volume loss. ROI, region of interest.\n\n5\nwww.i-mri.org\nhttps://doi.org/10.13104/imri.2019.1030\nother hemorrhagic adnexal lesions, luteal ovarian cysts, or tubo-\novarian abscesses. Additionally, gadolinium enhancement is cru-\ncial for depicting strongly enhanced mural nodules if atypical \nfeatures suggest potential malignancy on US or T2-WI [21,22]. \nHowever, this study highlighted the role of contrast enhance-\nment that revealed endometrial invasion of the adjacent \nhealthy ovarian tissue.\nThe ovaries are readily identified on MRI because they con-\ntain multiple various stages of ovarian follicles in the majority \nof females in their reproductive period [23,24]. T2-WI are the \nmost useful sequences in the diagnosis of ovaries and ovarian \nfollicles in females of reproductive age. In postmenopausal \nfemales, ovaries show more homogeneous low signal intensity \nin T2-WI, and are more difficult to identify because of atro -\nphic changes [25]. Ovarian stroma shows contrast enhancement \nsimilar to myometrium and contrast enhancement pattern also \ncorrelated with age and menopausal status on contrast en -\nhanced T1-WI [25]. Cystic follicles and functional ovarian cyst \nwere found frequently and had variable appearance. Most cysts \nshow discrete enhancement of the wall. In this study, the histo-\ngram for normal ovary shows narrow peak between 0 and 0.03 \nperfusion ratio, representative ovarian follicular cyst. Overall \nperfusion ratio of normal ovary was 0.48 ± 0.07, which was \nsignificantly different for endometrial invasion of the ovary. \nIn this study, the perfusion map showed the absence of en-\nhancement within the cystic lesions, regardless of the vari -\nable signal intensity of T1 or T2-WI. The perfusion map could \nbe valuable in differentiating complex cystic lesions with T1 \nhigh signal intensity such as ectopic pregnancy, borderline en-\ndometriosis or small malignant lesion within the cystic lesion \n[26]. The perfusion map can adequately determine the degree \nof contrast enhancement in the background of tissues that \n3000\n2500\n1000\n500\n0\n60\n50\n40\n30\n20\n10\n0\nNo of pixels\n0.2                            0.4                           0.6                          0.8\nSevere\nModerate\nNormal ovary\n0.4             0.6             0.8\nPerfusion ratio\nFig. 3. The histogram of the perfusion map for ovarian endometriosis with the normal ovary. The histogram showed increased peak (arrow) \ndue to the hemorrhagic cyst of severe endometriosis around zero perfusion. The area under the curve of the perfusion ratio between 0.4 \nand 0.8 highest in the group with moderate endometriosis followed by the normal ovary and severe endometriosis groups.\nTable 3. Comparison of histogram analysis according to severity of endometrial invasion to ovary\nMild and Moderate (LF score = 2 or 3) (n = 8) Severe (LF score = 1 or 0) (n =6) p*\nArea (mm2) 2102.88 ± 1499.05 2098.17 ± 1162.15 0.995\n0 < perfusion ratio < 0.2† 1389.13 ± 1453.11 1420.50 ± 1167.15 0.996\n0.2 < perfusion ratio < 0.4 173.00 ± 74.74 98.67 ± 64.31 0.070\n0.4 < perfusion ratio < 0.8 528.00 ± 154.43 199.17 ± 163.15 0.003\nPerfusion ratio 0.27 ± 0.11 0.11 ± 0.07 0.012\nIntegrated density 427.125 ± 132.24 187.33 ± 106.32 0.003\nLF score (least function score): 3 = mild dysfunction, 2 = moderate dysfunction, 1 = severe dysfunction, 0 = absent or nonfunctional.\n*Student t-test.\n\n6\nwww.i-mri.org\nMR Histogram for Ovarian Endometriosis | Hyun Jung Lee\nshowed a high signal intensity on contrast enhanced T1-WI \nsuch as adjacent uterus or inflammatory change related with \nendometriosis. Our results showed increased number of pixels \nbetween 0.4 to 0.8 perfusion ratios in moderate advanced en-\ndometriosis, suggesting increased volume of the inflammatory \nchange of endometriosis as well as cystic lesions. However, \nadvanced status endometriosis showed decreased or similar \nvolume of endometrial tissue between 0.2 to 0.8 perfusion \nratio suggestive ovarian invasion of endometriosis. \nThe perfusion map can aid in evaluation of the remnant \novarian tissue. Endometrial invasion of the ovarian tissue is as-\nsociated with the ovarian function. Also, bilateral invasion of \nthe ovarian tissue is associated with infertility. In this study, \nsevere invasion of endometriosis showed the lower area with \nmoderate perfusion ratio similar to that of the ovary, suggest-\ning the perfusion map could predict remnant ovarian preserve. \nSuch results support the assessment of the extent of ovarian \ninvolvement could be mandatory to determine the preopera-\ntive grade [6,27]. \nThe rAFS classification, the most widely used staging sys -\ntem of endometriosis, depends on the results of laparoscopic \nexamination and laparotomy. The staging of endometriosis \nrequires the detailed observation and recording of the site, \nnumber, size, and depth of the endometriosis lesions, as well \nas the degree of adhesions, to define the final score. However, \nseveral studies observed no association between the endome-\ntriosis stage or lesion type and lesion site and the cumulative \nprobability of pregnancy [28]. Fujishita et al. [29] modified the \nAFS classification of endometriosis by adding the TOP score \n(fallopian tubes, ovaries, peritoneum, and other factors), fo -\ncused on the ovaries. However, there are no definite MRI find-\nings suggestive of deep invasion of the ovary. In this study, we \nsuggested histogram analysis focused on the viable ovary. Al-\nthough further clinical studies are required, the value could be a \nmarker for remnant viable ovarian tissue. The presented tech-\nnique could be valuable in determining the surgical approach \nfor ovarian endometriosis.\nHowever, this study has several limitations. First, one en -\nrolled patient was too limiting to comprehensively understand \nthe relationship between the imaging result and clinical out-\ncome. Additionally, the case with unilateral ovarian involve-\nment was included. For the validation of the effectiveness of \nthe histographic analysis for prediction ability for pregnancy, \na larger population is mandatory. Second, the perfusion map \nusing subtraction technique requires strict adherence to a \nspecific protocol with a radiology staff, trained to ensure that \ncorrect images are obtained, and the post-acquisition analysis \nis appropriate, including matching the exact pre- and post-\ncontrast images to generate the subtracted image, which can \nbe hampered by patient movement [30,31].\nIn summary, the parameters of the perfusion map including \nthe area with perfusion ratio between 0.4 to 0.8, perfusion \nratio, and integral density were related with discriminating \nsevere endometrial invasion into the ovary from mild or mod-\nerate invasion, in addition to confirming the diagnosis of en-\ndometriosis showing the absence of enhancement. The appli-\ncation of the histographic analysis for the perfusion map of \nthe pelvic MRI could be promising for the preoperative evalu-\nation of remnant ovarian tissue in patients who desire ovarian \npreservation during the surgical treatment. In conclusion, the \nhistographic analysis for the perfusion map of the pelvic MRI \ncould be valuable in revealing the extent of the endometrial \ninvasion and viable remnant ovarian tissue.\nAvailability of Data and Material\nThe datasets generated or analyzed during the study are available \nfrom the corresponding author on reasonable request.\nConflicts of Interest\nThe author has no potential conflicts of interest to disclose.\nORCID iD\nHyun Jung Lee https://orcid.org/0000-0002-3942-405X\nFunding Statement\nNone\nAcknowledgments \nNone\nREFERENCES\n1. Yu JS, Rofsky NM. Dynamic subtraction MR imaging of the liver: \nadvantages and pitfalls. AJR Am J Roentgenol 2003;180:1351-\n1357.\n2. Hummelshoj L, Prentice A, Groothuis P. Update on endometriosis. \nWomens Health (Lond) 2006;2:53-56.\n3. Counseller VS, Crenshaw JL Jr. A clinical and surgical review of \nendometriosis. Am J Obstet Gynecol 1951;62:930-942.\n4. Working group of ESGE, ESHRE and WES; Saridogan E, Becker \nCM, et al. 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Acta Radiol 2015;56:1127-\n1134.","source_license":"CC0","license_restricted":false}