Clinical and ultrasound characteristics of surgically removed adnexal lesions with largest diameter ≤ 2.5 cm: a pictorial essay

Legge, A. Di; Pollastri, Paola; Mancari, Rosanna; Ludovisi, M.; Mascilini, F.; Franchi, D.; Coccia, Maria Elisabetta; Timmerman, Dirk; Scambia, Giovanni; Testa, Antonia Carla; Valentin, Lil

doi:10.1002/uog.17392

Cited by 18 publications

(15 citation statements)

References 23 publications

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“…In postmenopausal women, often small (<4–5 mm) cysts are detected. Such small cystic ovarian lesions were studied by Di Legge et al, Hu et al, as well as Ferrazzi et al, with their works containing similar findings. On the basis of the unique US features of CAFs demonstrated in this study, it is possible to predict their probable histologic characteristics with reasonably high accuracy…”

Section: Discussionsupporting

confidence: 58%

“…In postmenopausal women, often small (<4-5 mm) cysts are detected. Such small cystic ovarian lesions were studied by Di Legge et al, 13 Hu et al, 14 as well as Ferrazzi et al, 15 with their works containing similar findings. On the basis of the unique US features of CAFs demonstrated in this study, it is possible to predict their probable histologic characteristics with reasonably high accuracy It our view that an accurate US diagnosis can be enhanced by applying pathognomonic US signs unique to a specific condition and that, supported by histopathologic findings, it can help sonographers and sonologists recognize this entity clearly and thereby diagnose this adnexal structure more accurately.…”

Section: Discussionsupporting

confidence: 54%

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Ultrasound and Histopathologic Correlation of Ovarian Cystadenofibromas: Diagnostic Value of the “Shadow Sign”

Timor‐Tritsch

Yoon

Monteagudo³

et al. 2019

J of Ultrasound Medicine

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Objectives Cystadenofibromas (CAFs) are rare benign ovarian tumors without a widely accepted ultrasound (US) pattern. They are usually described by as thin‐walled, unilocular or multilocular, and at times septated cysts with scant blood flow and no solid components. We describe a unique US feature, the “shadow sign,” seen in prospectively diagnosed benign CAFs. We also provide the histopathologic basis for this typical US appearance. Methods Ultrasound (US) examinations were performed in our obstetric and gynecologic US unit. Pathologic examinations were performed by a dedicated gynecologic pathology team. The US and pathology department's database was searched for the diagnosis of a CAF between 2010 and 2017. Results We identified 20 patients who underwent transvaginal US examinations with a sole US diagnosis of a CAF, and the tumors were surgically removed. The common US feature across the 20 cases was the presence of hyperechoic avascular shadowing nodules. The correlating histologic features were unilocular or multilocular cysts with a smooth internal wall surface lined by a simple epithelium and occasional robust polypoid fibrous stroma. Conclusions This US marker helps in differentiating CAFs from borderline ovarian tumors, which do not show this US feature. We hope that recognizing the suggested shadow sign as an additional descriptor of CAFs will lead to minimizing their unnecessary removal and eliminating additional and unnecessary imaging by computed tomography and magnetic resonance imaging.

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Section: Discussionsupporting

confidence: 58%

Section: Discussionsupporting

confidence: 54%

Ultrasound and Histopathologic Correlation of Ovarian Cystadenofibromas: Diagnostic Value of the “Shadow Sign”

Timor‐Tritsch

Yoon

Monteagudo³

et al. 2019

J of Ultrasound Medicine

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“…To confirm the novelty and importance of our findings, we carried out a PubMed search of the English-language literature published between 2010 and 2018, seeking to determine if this microcystic tissue pattern of papillary projections, solid component(s) and/or septa has been described previously. Figure S3 is a composite of images found on review of 23 articles 6,[16][17][18][22][23][24][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] identifying 163 individual sonographic pictures of ovarian cysts labeled as BOT by the authors. Although the quality of these images is variable, on close examination it is clear that almost all of them feature a 'bubbly' microcystic nature of papillae or solid component(s).…”

Section: Discussionmentioning

confidence: 99%

“… Figure S3 Composite image of 163 individual figures and ultrasound images of borderline ovarian tumor (BOT), published in 23 articles identified by literature search, which included microcystic pattern without mention or description of it. LMP, low malignant potential.…”

mentioning

confidence: 99%

New sonographic marker of borderline ovarian tumor: microcystic pattern of papillae and solid components

Timor‐Tritsch

Foley

Brandon

et al. 2019

Ultrasound in Obstet & Gyne

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Objective To describe and evaluate the utility of a new sonographic microcystic pattern, which is typical of borderline ovarian tumor (BOT) papillary projections, solid component(s) and/or septa, as a new ultrasound marker that is capable of distinguishing BOT from other adnexal masses, and to present/obtain histologic confirmation. Methods In this retrospective study, we identified women with a histologic diagnosis of BOT following surgical resection who had undergone preoperative transvaginal ultrasound (TVS) examination. All images were reviewed for presence or absence of thin-walled, fluid-filled cluster(s) of 1-3-mm cystic formations, associated with solid component(s), papillary projections and/or septa. From the same cases, histopathologic slides of each BOT were examined for presence of any of these microcystic features which had been identified on TVS. To confirm that the microcystic TVS pattern is unique to BOTs, we also selected randomly from our ultrasound and surgical database 20 cases of epithelial ovarian cancer and 20 cases of benign cystadenoma, for review by the same pathologists. To confirm the novelty of our findings, we searched PubMed for literature published in the English language between 2010 and 2018 to determine whether the association between microcystic tissue pattern and BOT has been described previously. Results Included in the final analysis were 62 patients (67 ovaries) with preoperative TVS and surgically confirmed BOT on pathologic examination. The mean patient age at surgery was 39.8 years. The mean BOT size at TVS was 60.7 mm. Of the 67 BOTs, 47 (70.1%) were

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“…To date, US-based examinations were considered the primary imaging technique for preoperative prediction of ovarian tumors. ( Di Legge et al, 2017 ). Benign serous ovarian tumors are typically simple smooth-walled unilocular or multilocular cystic masses, ( Virgilio et al, 2019 ), whereas serous borderline ovarian tumors tend to form cystic masses with profuse papillary projections.…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of Ovarian Neoplasms Using Nomogram in Combination With Ultrasound Image-Based Radiomics Signature and Clinical Factors

Chen

et al. 2021

Front. Genet.

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Objectives: To establish and validate a nomogram integrating radiomics signatures from ultrasound and clinical factors to discriminate between benign, borderline, and malignant serous ovarian tumors.Materials and methods: In this study, a total of 279 pathology-confirmed serous ovarian tumors collected from 265 patients between March 2013 and December 2016 were used. The training cohort was generated by randomly selecting 70% of each of the three types (benign, borderline, and malignant) of tumors, while the remaining 30% was included in the validation cohort. From the transabdominal ultrasound scanning of ovarian tumors, the radiomics features were extracted, and a score was calculated. The ability of radiomics to differentiate between the grades of ovarian tumors was tested by comparing benign vs borderline and malignant (task 1) and borderline vs malignant (task 2). These results were compared with the diagnostic performance and subjective assessment by junior and senior sonographers. Finally, a clinical-feature alone model and a combined clinical-radiomics (CCR) model were built using predictive nomograms for the two tasks. Receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA) were performed to evaluate the model performance.Results: The US-based radiomics models performed satisfactorily in both the tasks, showing especially higher accuracy in the second task by successfully discriminating borderline and malignant ovarian serous tumors compared to the evaluations by senior sonographers (AUC = 0.789 for seniors and 0.877 for radiomics models in task one; AUC = 0.612 for senior and 0.839 for radiomics model in task 2). We showed that the CCR model, comprising CA125 level, lesion location, ascites, and radiomics signatures, performed the best (AUC = 0.937, 95%CI 0.905–0.969 in task 1, AUC = 0.924, 95%CI 0.876–0.971 in task 2) in the training as well as in the validation cohorts (AUC = 0.914, 95%CI 0.851–0.976 in task 1, AUC = 0.890, 95%CI 0.794–0.987 in task 2). The calibration curve and DCA analysis of the CCR model more accurately predicted the classification of the tumors than the clinical features alone.Conclusion: This study integrates novel radiomics signatures from ultrasound and clinical factors to create a nomogram to provide preoperative diagnostic information for differentiating between benign, borderline, and malignant ovarian serous tumors, thereby reducing unnecessary and risky biopsies and surgeries.

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Clinical and ultrasound characteristics of surgically removed adnexal lesions with largest diameter ≤ 2.5 cm: a pictorial essay

Cited by 18 publications

References 23 publications

Ultrasound and Histopathologic Correlation of Ovarian Cystadenofibromas: Diagnostic Value of the “Shadow Sign”

Ultrasound and Histopathologic Correlation of Ovarian Cystadenofibromas: Diagnostic Value of the “Shadow Sign”

New sonographic marker of borderline ovarian tumor: microcystic pattern of papillae and solid components

Diagnosis of Ovarian Neoplasms Using Nomogram in Combination With Ultrasound Image-Based Radiomics Signature and Clinical Factors

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