Mucınous Endometrial Cancer: Clinical Study of Eleven Cases

Duzguner, Soner; Türkmen, Osman; Kimyon, Gunsu; Duzguner, Ipek Nur Balin; Karalök, Alper; Başaran, Derman; Taşçı, Tolga; Üreyen, Işın; Turan, Taner

doi:10.14744/nci.2019.17048

Cited by 5 publications

(14 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 7 shows the "histomics" features with significant alterations between LNM+ and LNM− patients in top-value tiles, enhanced texture, voluminous extracellular mucin, cleft-like structures and elongated angular glandular lumen, which distinguish LNM+ from LNM− patients well. These suggested features from the red subregions appear to be highly consistent with pathologists' experience and previous studies (23)(24)(25). Feature visualization demonstrated that output results of our model have realistic interpretability.…”

Section: Discussionsupporting

confidence: 86%

“…Enhanced texture, voluminous extracellular mucin, cleftlike structures and elongated angular glandular lumen were "histomics" features with significant alterations between LNM+ and LNM− WSIs, indicating an increased rate of lymph node involvement. These features were consistent with previous studies (23)(24)(25) and provide an interpretative reliability to the predictive results of the AI-model.…”

Section: Interpretation Of Predictive Performance Of the Mil Modelsupporting

confidence: 91%

See 1 more Smart Citation

A deep learning model for lymph node metastasis prediction based on digital histopathological images of primary endometrial cancer

Feng¹,

Zhao²,

Chen³

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

Background: The current study aimed to develop a deep learning (DL) model for prediction of lymph node metastasis (LNM) based on hematoxylin and eosin (HE)-stained histopathological images of endometrial cancer (EC). The model was validated using external data.Methods: A total of 2,104 whole slide image (WSI) from 564 patients with pathologically confirmed LNM status were collated from West China Second University Hospital. An artificial intelligence (AI) model was built on the multiple instance-learning (MIL) framework for automatic prediction of the probability of LNM and its performance compared with "Mayo criteria". An additional external data source comprising 533 WSI was collected from two independent medical institutions to validate the model's robustness. Heatmaps were generated to demonstrate regions of the WSI that made the greatest contributions to the DL network output to improve understanding of these processes. Results:The proposed MIL model achieved an area under the curve (AUC) of 0.938, a sensitivity of 0.830 and a specificity of 0.911 for LNM prediction to EC. The AUC according to Mayo criteria was 0.666 for the same test dataset. For types I, II and mixed EC, AUCs were 0.927, 0.979 and 0.929, respectively. The predictive performance of the MIL model also achieved an AUC of 0.921 for early staging. In external validation data, the proposed model achieved an AUC of 0.770, a sensitivity of 0.814 and a specificity of 0.520 for LNM prediction. AUCs were 0.783 for type I and 0.818 for early stage EC. Conclusions:The proposed MIL model generated from histopathological images of EC has a much better LNM predictive performance than that of Mayo criteria. A novel DL-based biomarker trained on different histological subtypes of EC slides was revealed to predict metastatic status with improved accuracy, especially for early staging patients. The current study proves the concept of MIL-based prediction of LNM in EC for the first time, and brought a new sight to improve the accuracy of LNM prediction. Multicenter prospective validation data is required to further confirm the clinical utility.

show abstract

Section: Discussionsupporting

confidence: 86%

Section: Interpretation Of Predictive Performance Of the Mil Modelsupporting

confidence: 91%

A deep learning model for lymph node metastasis prediction based on digital histopathological images of primary endometrial cancer

Feng¹,

Zhao²,

Chen³

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

show abstract

“…One reason for the high serum CA19-9 level was the marked mucin production from carcinoma cells. Although our patient underwent intravenous chemotherapy for the recurrent tumor in the pelvis, the treatment option might be radiotherapy in a case of recurrent mucinous carcinoma [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Mucinous carcinoma originating from uterine adenomyosis: a case report

et al. 2023

View full text Add to dashboard Cite

Background Uterine adenomyosis is rarely a precursor of malignant tumors, but the most frequent histological subtype is endometrioid carcinoma. We observed a rare case of mucinous carcinoma originating from uterine adenomyosis. Case presentation A 63-year-old Japanese woman presented to our hospital with lower abdominal pain. She had no atypical genital bleeding. Ultrasound demonstrated thickening of the entire uterine wall, but the endometrium was not thick. Magnetic resonance imaging demonstrated an enlarged uterus with thickening of the entire uterine wall, suggesting adenomyosis. On the basis of the specimen of endocervical curettage, adenocarcinoma originating from the endometrium was suspected. Total abdominal hysterectomy and bilateral salpingo-oophorectomy were performed to confirm the diagnosis. Macroscopically, the resected enlarged uterus had no nodules and exudation of mucin was observed from the cut surface of the thickened myometrium. The surface of the endometrium was smooth. On histological examination, mucinous carcinoma invaded almost the entire myometrium. Adenomyotic lesions were distributed focally in the uterine wall, and transition from adenomyotic glandular epithelium to mucinous carcinoma was detected within several foci. Although adenocarcinoma cells proliferated adjacent to the endometrium, the primary endometrial epithelium was atrophic without atypia. Throughout the myometrium, the mucinous carcinoma cells proliferated and floated in dilated lymph vessels with abundant mucin pools. We diagnosed this case as mucinous carcinoma originating from adenomyosis. Although the patient received 11 courses of intravenous adjuvant chemotherapy, she died of disease 18 months after the first operation. Conclusion As only one case of mucinous carcinoma originating from adenomyosis has been reported to date, this is the second case report of mucinous carcinoma. Moreover, an abnormal manner of proliferation with marked lymphatic permeation of the tumor cells throughout the myometrium was observed.

show abstract

“…61 Other analyses that have mostly used the International Federation of Gynecology and Obstetrics (FIGO) grading schemes found the grade distribution to be as follows: grade I (average: 69.6%; range: 58% to 80%); grade 2 (average 25.1%; range: 17% to 36.6%); grade 3 (average 7.1%; range: 0% to 11%). 53,54,57,59 The mitotic index for mucinous carcinoma is typically low, with only 29% of cases reaching a maximal mitotic index of 1 mitotic figure/high power field in the Ross et al series. 17 Cells with eosinophilic cells are often admixed, and indeed, there is a possibility that eosinophilic and mucinous change are related in this context, since both display comparably high frequencies of MUC5AC expression.…”

Section: Mucinous Carcinomamentioning

confidence: 97%

“…For the analyses below, unless specifically stated otherwise, reports of mucinous carcinoma before 2020 are presumed to represent MCU. 27,[53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68] Mucinous Carcinomas of the Usual Type (1) Frequency: Ross et al 17 53,54,[57][58][59] Most patients presented with postmenopausal bleeding or abdominal pain. 57 Eighty three percent to 100% of patients were Caucasian.…”

Section: Mucinous Carcinomamentioning

confidence: 99%

Mucinous Proliferations of the Uterine Corpus: Comprehensive Appraisal of an Evolving Spectrum of Neoplasms

Fadare¹

2022

Advances in Anatomic Pathology

View full text Add to dashboard Cite

A variety of endometrial lesions may contain mucinous cells. Herein, the author reviews the literature on the classification and clinicopathologic significance of uterine corpus proliferations with a significant mucinous component, assesses the 2020 World Health Organization classification of such lesions, and presents a diagnostic framework. The key epithelial mucinous lesions include mucinous metaplasia, atypical mucinous glandular proliferation and mucinous carcinoma. Each of these categories are classifiable into "usual" and gastrointestinal subtypes, the latter being indicative of intestinal (presence of goblet cells) and/or gastric-type (abundant, pale eosinophilic or clear cytoplasm and well-defined cell borders) morphology. It has been proposed that at least focal expression of gastrointestinal immunohistochemical markers be required for all gastrointestinal type lesions, and for gastrointestinal type atypical mucinous glandular proliferation and carcinoma, minimality or absence of estrogen receptor expression, and the absence of an endometrioid component. Mucinous carcinomas of the usual type, in which > 50% of the tumor is comprised of a mucinous component, are the most common. Morphologic subtypes include mucinous carcinoma with microglandular features and mucinous carcinoma with signet rings (signet ring carcinoma). Endometrioid carcinomas with a less than a 50% mucinous component are classified as endometrioid carcinoma with mucinous differentiation. Several studies have directly compared endometrioid and mucinous carcinomas, the latter presumably of the usual type, with respect to patient outcomes after treatment. All have found no difference in overall and disease free survival between these groups. However, three major studies have found mucinous carcinomas to be associated with a higher risk of lymph node metastases. Nineteen cases of mucinous carcinoma of the gastrointestinal type have been reported, and the limited data on their follow-up after primary treatment suggests that this subtype is more clinically aggressive and should accordingly be classified separately from mucinous carcinomas of the usual type. The morphologic spectrum of mucinous carcinoma of the gastrointestinal type is unclear and continues to evolve. Mucinous change, which may sometimes be extensive, may also be associated with papillary proliferation of the endometrium, adenomyoma of the endocervical type, atypical, and typical adenomyomas. In a curettage or biopsy, intestinal type mucinous epithelium may be indicative of any of the gastrointestinal lesions mentioned above, but may also represent samplings of uterine teratomas, yolk sac tumors, genital and extragenital adenocarcinomas with intestinal differentiation, or lowgrade appendiceal mucinous neoplasms that secondarily involve the endometrium.

show abstract

Mucınous Endometrial Cancer: Clinical Study of Eleven Cases

Cited by 5 publications

References 18 publications

A deep learning model for lymph node metastasis prediction based on digital histopathological images of primary endometrial cancer

A deep learning model for lymph node metastasis prediction based on digital histopathological images of primary endometrial cancer

Mucinous carcinoma originating from uterine adenomyosis: a case report

Mucinous Proliferations of the Uterine Corpus: Comprehensive Appraisal of an Evolving Spectrum of Neoplasms

Contact Info

Product

Resources

About