Staging MRI of uterine malignant mixed Müllerian tumors versus endometrial carcinomas with emphasis on dynamic enhancement characteristics

Garza, Alheli; Elsherif, Sherif; Faria, Silvana C.; Sagebiel, Tara; Sun, Jia; Ma, Jingfei; Bhosale, Priya

doi:10.1007/s00261-019-02096-y

Cited by 7 publications

(6 citation statements)

References 52 publications

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“…A washout curve was defined as a steep initial increase and peak in signal followed by a decrease of at least 5-10%. 13 The degree of tumor enhancement in the late phase was compared with enhancement of normal myometrium and classified as mild, moderate, or strong. Decisions were reached by consensus.…”

Section: Imaging Analysismentioning

confidence: 99%

Characteristics of MR Imaging for Staging and Survival Analysis of Neuroendocrine Carcinoma of the Endometrium: A Multicenter Study in Japan

Kitajima

Kihara

Kawanaka

et al. 2021

MRMS

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This study aimed to examine MRI features and staging of neuroendocrine carcinoma (NEC) of the endometrium and evaluate survival. Materials and Methods: Clinical data, pathological, and preoperative pelvic MRI findings in 22 patients with histologically surgery-proven endometrial NEC were retrospectively reviewed. Tumors were pure NEC (n = 10) or mixed histotype (n = 12), with 13 large and nine small cell type. Results: International Federation of Gynecology and Obstetrics (FIGO) staging was I, II, III, and IV in 6, 2, 12, and 2 patients, respectively. In 13 (76.4%) of 17 patients with pathological deep myometrial invasion, MRI showed abnormal diffusely infiltrative high T 2 signal intensity throughout the myometrium with loss of normal uterine architecture. All tumors had restricted diffusion (apparent diffusion coefficient map low signal intensity, diffusion weighted imaging high signal intensity). Accuracy of T staging by MRI for all cases was 81.8%, with reference to pathology staging, while patient-based sensitivity, specificity, and accuracy for detecting metastatic pelvic lymph nodes was 60.0%, 100%, and 77.8%, respectively. Two intrapelvic peritoneal dissemination cases were detected by MRI. During follow-up (mean 30.4, range 3.3-138.4 months), 16 patients (72.7%) experienced recurrence and 12 (54.5%) died of disease. Two-year disease-free and overall survival rates for FIGO I, II, III, and IV were 66.7% and 83.3%, 50% and 100%, 10% and 33.3%, and 0% and 0%, respectively. Conclusion: Abnormal diffusely infiltrative high T 2 signal intensity throughout the myometrium with normal uterine architecture loss and obvious restricted diffusion throughout the tumor are suggestive features of endometrial NEC. Pelvic MRI is reliable for intrapelvic staging of affected patients.

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Section: Imaging Analysismentioning

confidence: 99%

Characteristics of MR Imaging for Staging and Survival Analysis of Neuroendocrine Carcinoma of the Endometrium: A Multicenter Study in Japan

Kitajima

Kihara

Kawanaka

et al. 2021

MRMS

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“…In CE-T1WI, the tumour enhancing effect was poorer than that in the myometrium (arrow), and no enhancing effect was observed in the necrotic area. It is presumed that all readers diagnosed EC because the tumour enhancing effect was poor on CE-T1WI ADC -apparent diffusion coefficient, CE-T1WI -contrast-enhanced fat-saturated T1-weighted imaging, CNN -convolutional neural network, CS -carcinosarcoma, ECendometrial carcinoma, T2WI -T2-weighted imaging threshold SER ≤ 125 predicted CS with 90% sensitivity, 50% specificity, and 0.72 AUC; however, tumour MSI did not significantly differ between the disease groups [24]. It has been reported that there was no significant difference between the mean and minimum ADC values of CS and EC, although the mean ADC of CS was significantly higher than that of higher grade (Grade 2 and 3) EC [25], and CS demonstrated heterogenous signal intensities on DWI and ADC map reflecting complicated tissue components [26].…”

Section: Discussionmentioning

confidence: 94%

Differentiation of carcinosarcoma from endometrial carcinoma on magnetic resonance imaging using deep learning

Mori¹,

Hoshiai²,

Sakai³

et al. 2022

Pol J Radiol

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Purpose:To verify whether deep learning can be used to differentiate between carcinosarcomas (CSs) and endometrial carcinomas (ECs) using several magnetic resonance imaging (MRI) sequences. Material and methods:This retrospective study included 52 patients with CS and 279 patients with EC. A deep-learning model that uses convolutional neural networks (CNN) was trained with 572 T2-weighted images (T2WI) from 42 patients, 488 apparent diffusion coefficient of water maps from 33 patients, and 539 fat-saturated contrast-enhanced T1-weighted images from 40 patients with CS, as well as 1612 images from 223 patients with EC for each sequence. These were tested with 9-10 images of 9-10 patients with CS and 56 images of 56 patients with EC for each sequence, respectively. Three experienced radiologists independently interpreted these test images. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for each sequence were compared between the CNN models and the radiologists. Results:The CNN model of each sequence had sensitivity 0.89-0.93, specificity 0.44-0.70, accuracy 0.83-0.89, and AUC 0.80-0.94. It also showed an equivalent or better diagnostic performance than the 3 readers (sensitivity 0.43-0.91, specificity 0.30-0.78, accuracy 0.45-0.88, and AUC 0.49-0.92). The CNN model displayed the highest diagnostic performance on T2WI (sensitivity 0.93, specificity 0.70, accuracy 0.89, and AUC 0.94). Conclusions:Deep learning provided diagnostic performance comparable to or better than experienced radiologists when distinguishing between CS and EC on MRI.

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“…A negative endometrial biopsy does not rule out diagnosis as it does not obtain sufficient tissue ( 16 ). The use of early tumor imaging is of benefit for suspected patients with uterine cavities not readily accessible for biopsy but can be nonspecific in differentiating one tumor from another ( 17 ). Exfoliative cytology may provide confirmation if a biopsy is not available or appropriate.…”

Section: Discussionmentioning

confidence: 99%

“…Exfoliative cytology may provide confirmation if a biopsy is not available or appropriate. However, this method has variable and limited sensitivity, with 60% of tests correctly detecting some form of malignancy and only 8.6% of cytology specimens correctly detecting MMMTs specifically, as opposed to mistaking MMMTs for adenocarcinoma ( 17 , 18 ). Therefore, histopathological confirmation is important even in those that are not surgical candidates as correct diagnosis has significant implication on prognosis and management.…”

Section: Discussionmentioning

confidence: 99%

Malignant mixed mullerian tumors: a SEER database review of rurality and treatment modalities on disease outcome

Zadeh,

Bhatt,

Sripiparu

et al. 2024

Front. Oncol.

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IntroductionMalignant Mixed Mullerian Tumors (MMMT) are rare and poorly understood sarcomas with limited research on risk factors, pathogenesis, and optimal treatments. This study aimed to address this knowledge gap and explore the impact of community size, patient characteristics, disease characteristics, and treatment modalities on MMMT outcomes.MethodsUsing the Surveillance, Epidemiology, and End Results database (SEER), the largest SEER cohort to date of 3,352 MMMT patients was analyzed for demographic factors, treatment modalities, and histologic characteristics. Data was processed, including the removal of incomplete entries, and analyzed in Python 3.1 using packages scikit-learn, lifelines, and torch; log-rank analysis and Cox proportional hazards models were used to evaluate a number of demographic characteristics and disease characteristics for significance in regard to survival.ResultsOur study found adjuvant radiotherapy and chemotherapy significantly improved survival, with modest benefits from neoadjuvant chemotherapy. Our findings also suggest age at diagnosis, disease grade, and suburban versus rural geographic locations may play key roles in patient prognosis. On multivariable analysis both disease Grade and surgical treatment were significant factors.DiscussionMMMTs remain challenging, but appropriate treatment appears to enhance survival. The present findings suggest opportunities for improved outcomes and treatment strategies for patients with MMMTs.

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Staging MRI of uterine malignant mixed Müllerian tumors versus endometrial carcinomas with emphasis on dynamic enhancement characteristics

Cited by 7 publications

References 52 publications

Characteristics of MR Imaging for Staging and Survival Analysis of Neuroendocrine Carcinoma of the Endometrium: A Multicenter Study in Japan

Characteristics of MR Imaging for Staging and Survival Analysis of Neuroendocrine Carcinoma of the Endometrium: A Multicenter Study in Japan

Differentiation of carcinosarcoma from endometrial carcinoma on magnetic resonance imaging using deep learning

Malignant mixed mullerian tumors: a SEER database review of rurality and treatment modalities on disease outcome

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