Mucin-producing tumors of the ovary: MR imaging appearance

Salient magnetic resonance imaging findings in the differential diagnosis of benign, borderline and malignant ovarian mucinous tumors

PURPOSE

In mucinous ovarian tumors, preoperative prediction of histological subgroup is important for treatment approach. Therefore, we aimed to determine salient magnetic resonance imaging (MRI) findings and estimate optimal cut off values for quantitative features in differential diagnosis of benign, borderline and malignant mucinous ovarian tumors.

METHODS

Between January 2011 and December 2021, preoperative MRI scans of 50 patients with mucinous ovarian tumors (n = 54) were evaluated retrospectively. MRI findings [size, signal intensity, contrast pattern, features of loculation, wall, septa and mural nodule (MN), diffusion restriction] were investigated. There were benign, borderline, and malignant groups based on histopathological results. The relationship between radiological and histopathological results was analyzed by performing Kruskal Wallis test, Pearson's chi-squared test, receiver operating characteristic analysis.

RESULTS

In our study, there were 54 mucinous ovarian tumors in 50 patients. Of 54, 33 were benign, 13 borderline and eight malignant tumors. In comparison of three groups, tumor size, number of loculation, number and frequency of MN were higher and apparent diffusion coefficient (ADC) value were lower in malignant group (p < 0.05). Septa thickness was lower with optimal cut off value of 2.45 mm in benign group compared to borderline and malignant groups [sensitivity: 79%, specificity: 75%, AUC (Area under the curve): 0.861] (p < 0.05). T2-weighted (T2-w) signal intensity ratio (SIR) of MN was higher in borderline compared to malignant group, with a cut-off value of 3.9 (sensitivity: 85%, specificity: 83%, AUC: 0.943) (p < 0.05). Ascites was also significant in malignant group (p < 0.05).

CONCLUSION

T2-w SIR of MN with a cut off value of 3.9 is beneficial for differential diagnosis. By awareness of some salient MRI findings (size, septa thickness, number of loculation, number and T2-w SIR of MN, ADC value and ascites), preoperative prediction of histological subgroup of mucinous tumors for appropriate treatment planning is possible.

Evaluation of Selected MRI Parameters in the Differentiation of Mucinous Ovarian Carcinomas and Metastatic Ovarian Tumors

Introduction: Analysis of selected MRI parameters in initial MRI for the characterization of ovarian masses enables differentiation between mucinous ovarian carcinoma and metastatic ovarian tumors. Material and Methods: A prospective analysis of contrast-enhanced MRI of patients with suspected ovarian masses diagnosed in ultrasound and CT examination. Morphological criteria, such as the size of lesion, bilateral location, presence of "mille-feuille sign", so-called Seidman criteria, as well as the diffusion weighted imaging and dynamic contrast enhancement of each lesion, were evaluated. Patients were allocated into two groups; the first group contained patients with mucinous ovarian cancer, and the second group contained patients with metastatic ovarian tumors. Results: A total of 35 patients were enrolled into the study. Median age was 49 in the first group and 59 in the second group of patients (p = 0.04). In the first group, all patients (100%) had unilateral lesions, and in the second group, 94% had bilateral tumors (p < 0.000001). In the first group, a tumor size equal or greater than 10 cm was present in 80% of patients, and the same was true for 21% of patients in the second group. The mille-feuille sign was present in 30% of patients from the first group and in 64% of patients from the second group. In the first group of patients, TTP was 410 and Perf.Max Enhancement was 141; in the second group, they were, respectively, 154 and 167 (p = 0.0001 and p = 0.5). Median ADC values in the first group were significantly higher in the first group than in the second group (p < 0.01). Conclusions: Significant differences in TTP and ADC values as well as in Seidman criteria enable reliable differentiation between the analyzed groups of tumors.

Multimodal diagnostic strategies and precision medicine in mucinous ovarian carcinoma: a comprehensive approach

Mucinous ovarian carcinoma (MOC) represents a distinct entity within ovarian malignancies, characterized by diagnostic challenges due to its rarity and the potential overlap with other tumor types. The determination of tumor origin is important for precise postsurgical treatment. This article highlights the accurate diagnosis and management of MOC, including the use of imaging modalities, serological tumor markers, immunohistochemistry, and genomic analyses. Transabdominal and transvaginal ultrasonography, complemented by MRI and CT, plays a pivotal role in differentiating MOC from other mucinous tumors and in surgical planning, particularly for fertility preservation. Serological markers like CA19-9, CA-125, and CEA, though not definitive, provide valuable preoperative insights. Immunohistochemistry aids in distinguishing primary MOC from metastatic mucinous carcinomas, while genomic profiling offers the potential for precision medicine through the identification of specific molecular signatures and treatment susceptibilities. Despite advancements in diagnostic techniques, no single method conclusively differentiates between primary and metastatic tumors intraoperatively. The paper reviews the origins, diagnosis, and differential diagnosis of primary mucinous ovarian carcinoma highlights the need for a multimodal diagnostic approach and advocates for the inclusion of MOC patients in clinical trials for personalized therapies, recognizing the heterogeneity of the disease at the molecular level.

Management of borderline ovarian tumors: A tertiary referral center experience in Egypt

Background

In this retrospective study, we discuss our experience as a large tertiary referral center in Egypt in the management and follow-up of borderline tumors

Patients and methods

This is a retrospective cohort study where all patients diagnosed with a borderline ovarian tumor at Oncology Center Mansoura University from November 2014 to June 2020 were included. Demographics, preoperative, operative, postoperative, pathologic, and oncologic follow-up data were retrieved from a prospectively maintained electronic database. The included patients were followed until April 2022.

Results

We included 27 patients with borderline ovarian tumors. The mean age of the study patients was 47.67 ± 16.39 years. The median CA 125 was 33 (6–304 U/ml). Frozen section examination was utilized in 13 patients (48.14%), where a diagnosis of borderline ovarian tumors was revealed in 8 patients. Recurrence was reported in one patient with serous type after approximately 26 months. The most common pathological type in our cohort was the mucinous borderline type reported in 14 patients (51.9%), followed by the serous type reported in 11 patients (40.7%), and the seromucinous type in 1 patient only. Patients with mucinous borderline type were significantly younger (40.083 ± 18.47 vs. 53.73 ± 11.91 years, p = 0.028). Interestingly, Cancer Antigen 125 levels were significantly higher in mucinous than serous and seromucinous types [67(16–304) vs. 20(6–294.6) U/ml, p = 0.027]. On the other hand, the radiological tumor size of serous and seromucinous types was larger than that of the mucinous type [23(19–31) cm vs. 8(5–20) cm, p = 0.001]. Over a median follow-up period of 58.66 (54.16–63.16) months, only one postoperative mortality was reported, while only one recurrence was reported.

Conclusion

Borderline ovarian tumors still represent a dilemma either in diagnosis or management. A frozen section examination could help to reach a preliminary diagnosis. Total abdominal hysterectomy and bilateral salpingo-oophorectomy are the cornerstone of surgical management; however, fertility-sparing surgery could be a valid option for women desiring fertility.

Diagnosing Ovarian Cancer on MRI: A Preliminary Study Comparing Deep Learning and Radiologist Assessments

Simple Summary

As a preliminary experiment to explore the possibility of clinical application as a future reading assist, we present CNNs for the diagnosis of ovarian carcinomas and borderline tumors on MRI, including T2WI, DWI, ADC map, and CE-T1WI, and compare their diagnostic performance with interpretations by experienced radiologists. CNNs were trained using 1798 images from 146 patients and 1865 images from 219 patients with malignant tumors, including borderline tumors, and non-malignant lesions, respectively, for each MRI sequence and tested with 48 and 52 images of patients with malignant and non-malignant lesions. The CNN of each sequence had a sensitivity of 0.77–0.85, specificity of 0.77–0.92, accuracy of 0.81–0.87, and an AUC of 0.83–0.89, demonstrating diagnostic performances that were non-inferior to those of experienced radiologists, and the CNN showed the highest diagnostic performance on the ADC map for each sequence (specificity = 0.85; sensitivity = 0.77; accuracy = 0.81; AUC = 0.89).

Abstract

Background: This study aimed to compare deep learning with radiologists’ assessments for diagnosing ovarian carcinoma using MRI. Methods: This retrospective study included 194 patients with pathologically confirmed ovarian carcinomas or borderline tumors and 271 patients with non-malignant lesions who underwent MRI between January 2015 and December 2020. T2WI, DWI, ADC map, and fat-saturated contrast-enhanced T1WI were used for the analysis. A deep learning model based on a convolutional neural network (CNN) was trained using 1798 images from 146 patients with malignant tumors and 1865 images from 219 patients with non-malignant lesions for each sequence, and we tested with 48 and 52 images of patients with malignant and non-malignant lesions, respectively. The sensitivity, specificity, accuracy, and AUC were compared between the CNN and interpretations of three experienced radiologists. Results: The CNN of each sequence had a sensitivity of 0.77–0.85, specificity of 0.77–0.92, accuracy of 0.81–0.87, and an AUC of 0.83–0.89, and it achieved a diagnostic performance equivalent to the radiologists. The CNN showed the highest diagnostic performance on the ADC map among all sequences (specificity = 0.85; sensitivity = 0.77; accuracy = 0.81; AUC = 0.89). Conclusion: The CNNs provided a diagnostic performance that was non-inferior to the radiologists for diagnosing ovarian carcinomas on MRI.

Ovarian Collision Tumor, Massive Mucinous Cystadenoma, and Benign Mature Cystic Teratoma

Collision tumors are rare neoplasms defined by the presence of two distant tumors in the same organ without any histological intermixing. Ovarian tumors are often asymptomatic during the early stages and become symptomatic when increased in size causing vague abdominal pain, abdominal distention, vomiting, and frequent urination. We report here a case of a 28-year-old female who presented with a history of worsening abdominal pain and distension. An abdominopelvic ultrasound scan showed a huge complex mass occupying the pelvic area with non-visualization of the left ovary suggesting an ovarian origin; further characterization by cross-sectional imaging by both CT and MRI were performed confirming a left ovarian complex mass containing multiseptated cystic and fat component at the same time along with massive ascites. After surgical resection of the mass, histopathology revealed mucinous cystadenoma coexisting with cystic teratoma.

Clinical value of N-acetyl mucinous compounds and lipid peaks in differentiating benign and malignant ovarian mucinous tumors by MR spectroscopy

PURPOSE

To retrospectively evaluate the clinical significance of the peaks of N-acetyl mucinous compounds (NAMC) at 2 ppm and lipid at 1.3 ppm in in-vivo proton magnetic resonance (MR) spectroscopy for distinguishing benign and malignant mucinous tumors in patients with ovarian masses.

METHODS

MR spectroscopy was performed in patients with pathologically diagnosed mucinous ovarian tumors at 3 T MRI system. The peaks of NAMC, lipid, and total choline compounds (tCho) were classified into three classes in comparison with the noise level by visual estimation. The NAMC concentration was quantified relative to unsuppressed water by using LCModel analysis.

RESULTS

A total of 27 ovarian mucinous tumors in 27 patients were included in this study. The NAMC peak was observed in all 27 mucinous tumors, and the lipid peak was observed in 14 of 27 tumors: 1 of 9 benign tumors (11%), and 13 of 18 malignant tumors (11 borderline malignancies and 7 carcinomas) (72%). The presence of the lipid peak for the diagnosis of malignant mucinous tumor showed generally better diagnostic ability than MR imaging, with a sensitivity of 72%, specificity of 89%, accuracy of 78%, PPV of 93%, and NPV of 62%. The concentration of the NAMC in malignant mucinous tumors tended to be higher than that in benign mucinous tumors, but there was no statistically significant difference.

CONCLUSIONS

The bimodal peaks of NAMC and lipid are suggestive of malignant mucinous tumors, and the presence of the lipid peak may be useful in distinguishing benign from malignant ovarian mucinous tumors.

Adnexal masses characterized on 3 tesla magnetic resonance imaging - added value of diffusion techniques

Background

To assess different types of adnexal masses as identified by 3T MRI and to discuss the added value of diffusion techniques compared with conventional sequences.

Patients and methods

174 women age between 13 and 87 underwent an MRI examination of the pelvis for a period of three years. Patients were examined in two radiology departments – 135 of them on 3 Tesla MRI Siemens Verio and 39 on 3 Tesla MRI Philips Ingenia. At least one adnexal mass was diagnosed in 98 patients and they are subject to this study. Some of them were reviewed retrospectively. Data from patients’ history, physical examination and laboratory tests were reviewed as well.

Results

124 ovarian masses in 98 females’ group of average age 47.2 years were detected. Following the MRI criteria, 59.2% of the cases were considered benign, 30.6% malignant and 10.2% borderline. Out of all masses 58.1% were classified as cystic, 12.9% as solid and 29% as mixed. Оf histologically proven tumors 74.4% were benign and 25.6% were malignant. All of the malignant tumors had restricted diffusion. 64 out of all patients underwent contrast enhancement. (34 there were a subject of contraindications). 39 (61%) of the masses showed contrast enhancement.

Conclusions

Classifying adnexal masses is essential for the preoperative management of the patients. 3T MRI protocols, in particular diffusion techniques, increase significantly the accuracy of the diagnostic assessment.

Novel classification of ovarian metastases originating from colorectal cancer by radiological imaging and macroscopic appearance

BACKGROUND

Diagnosis of secondary ovarian tumors originating from colorectal cancer has previously been based upon history of malignancy and radiological findings of bilateral masses with a "stained glass appearance." The purpose of this study was to perform a detailed investigation of the radiological and macroscopic features of ovarian metastases originating from colorectal cancer, which remain to be fully characterized.

METHODS

Study participants were 48 consecutive patients with ovarian metastases from colorectal cancer who underwent resection of ovarian tumors at the National Cancer Center Hospital between August 1998 and January 2019. Ovarian tumors were classified into subgroups using computed tomography (CT), magnetic resonance imaging (MRI), and macroscopic appearance.

RESULTS

CT/MRI findings and macroscopic appearance were classified into the following four types: type 1 (oval, homogeneous-solid) (n = 5); type 2 (heterogeneous-solid, small in size with multinodular surface) (n = 3); type 3 (solid-cystic, predominantly solid) (n = 18); and type 4 (cystic-solid, multilocular with solid components) (n = 22). Type 1 mimics Krukenberg tumors, type 2 mimics ovarian metastases from breast cancer, type 3 mimics primary ovarian endometrioid cancer, and type 4 mimics primary ovarian mucinous cancer, with a "stained glass appearance". Twenty-eight (58%) patients had bilateral metastases. Eleven patients (23%) underwent hysterectomy and/or pelvic lymph node dissection in addition to ovarian resection.

CONCLUSION

We introduced a novel classification system for ovarian metastases originating from colorectal cancer, which may be beneficial for assessing ovarian metastases from colorectal cancer and avoiding unnecessary surgery due to misdiagnosis of primary ovarian tumors.

Mucinous Cancer of the Ovary: Overview and Current Status

Mucinous ovarian cancer (MOC) is a rare subtype of epithelial ovarian carcinoma (EOC). Whereas all EOC subtypes are addressed in the same way, MOC is a distinct entity. Appreciating the pathological features and genomic profile of MOC may result in the improvement in management and, hence, the prognosis. Distinguishing primary MOC from metastatic mucinous carcinoma can be challenging but is essential. Early-stage MOC carries an excellent prognosis, with advanced disease having a poor outcome. Surgical management plays an essential role in the early stage and in metastatic disease. Chemotherapy is usually administered for stage II MOC and beyond. The standard gynecology protocol is frequently used, but gastrointestinal regimens have also been administered. As MOC is associated with multiple molecular alterations, targeted therapy could be the answer to treat this disease.

Imaging findings for mucinous tumors of the abdomen and pelvis

This article aims to describe the imaging findings for mucinous tumors of the abdomen and pelvis, which have a similar appearance on imaging tests regardless of the organ in which they develop. Due to the high water content of mucus, the appearance of these tumors is generally similar to that of water on ultrasonography, computed tomography, and magnetic resonance imaging. Another common feature of mucin-producing tumors is that calcifications are often present. The rupture of these lesions and accumulation of mucinous material in the peritoneal cavity gives rise to pseudomyxoma peritonei. It is important to identify mucinous tumors because they have a different prognosis and clinical course than non-mucinous tumors and require different management. Depending on their anatomic location and their imaging characteristics, the treatment approach varies from follow-up to radical surgery together with chemotherapy or radiotherapy or both.

Imaging in secondary tumors of the ovary

Metastatic involvement of the ovaries is not rare. The most common tumor types metastasizing to the ovaries, from non-gynecological organs, are breast, colorectal, gastric, and appendix tumors. Lymphogenous, hematogenous, and transcoelomic pathways have all been proposed among potential pathways. Early diagnosis and treatment have an important potential to improve the patient outcome. Krukenberg tumors typically appear as complex semisolid masses with varying amounts of solid and cystic components. Ovarian metastases from the colon primaries are predominantly cystic in nature. Secondary lymphomatous involvement of ovary is mostly bilateral and solid with heterogeneous signal intensity on MRI. Metastatic breast cancer to the ovaries is typically bilateral and tends to be of small size. Among all the other imaging characteristics, bilateral involvement of secondary tumors of the ovary appears to be most potentially helpful finding in differentiating from primary ones.

Solidified mucinous tumor of the ovary presenting characteristic MRI finding

Mucinous tumors are a common ovarian cystic tumor, having a characteristic finding on MR imaging, the so-called stained glass appearance. We report a rare case of a solidified mucinous tumor of the ovary, which showed unique findings on MR images. The tumor demonstrated hypointensity on T2-weighted images, not stained glass appearance, mimicking ovarian fibrous tumor such as thecoma-fibroma. Histopathological examination confirmed solidified contents of the tumor with numerous septa and diagnosed mucinous borderline tumor/atypical proliferative tumor.