RESUMO
Introduction: Ovarian fibroma is an uncommon, benign, stromal neoplasm that is a mixture of collagen-producing mesenchymal cells. There are varying sonographic and computed tomography features described in literature of smaller scale studies. Case Report: We describe a case of an ovarian fibroma presenting as a midline pelvic mass mimicking a vaginal cuff tumour in a 67-year-old patient with surgical history of a hysterectomy. Computed tomography and ultrasound were utilised to evaluate the mass and guide management of the patient. The mass was initially suspected on CT-guided biopsy as a vaginal spindle cell epithelioma amongst other potential differential considerations. With robot-assisted laparoscopic surgery and histologic analysis, the true diagnosis of an ovarian fibroma was reached. Discussion: An ovarian fibroma is an uncommon, benign, stromal ovarian tumour, representing just 1-4% of all ovarian tumours. Its widely varying imaging features present a challenge when radiologically evaluating ovarian fibromas or pelvic tumours, as the differential diagnoses are extensive and ovarian fibromas are often misdiagnosed until surgical resection. We highlight the features of ovarian fibromas and the potential value of pelvic/transvaginal ultrasonography in management of ovarian fibroma and other pelvic masses. Conclusion: The use of computed tomography and ultrasound aided in the diagnostic and treatment pathway of this patient with a pelvic mass. There is high utility of sonography in evaluating such tumours to elucidate salient features, expedite diagnosis, and guide further management.
RESUMO
BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive pancreatic precursor lesions that can potentially develop into invasive pancreatic ductal adenocarcinoma. Currently, the International Consensus Guidelines (ICG) for IPMNs provides the basis for evaluating suspected IPMNs on computed tomography (CT) imaging. Despite using the ICG, it remains challenging to accurately predict whether IPMNs harbor high grade or invasive disease which would warrant surgical resection. A supplementary quantitative radiological tool, radiomics, may improve diagnostic accuracy of radiological evaluation of IPMNs. We hypothesized that using CT whole lesion radiomics features in conjunction with the ICG could improve the diagnostic accuracy of predicting IPMN histology. AIM: To evaluate whole lesion CT radiomic analysis of IPMNs for predicting malignant histology compared to International Consensus Guidelines. METHODS: Fifty-one subjects who had pancreatic surgical resection at our institution with histology demonstrating IPMN and available preoperative CT imaging were included in this retrospective cohort. Whole lesion semi-automated segmentation was performed on each preoperative CT using Healthmyne software (Healthmyne, Madison, WI). Thirty-nine relevant radiomic features were extracted from each lesion on each available contrast phase. Univariate analysis of the 39 radiomics features was performed for each contrast phase and values were compared between malignant and benign IPMN groups using logistic regression. Conventional quantitative and qualitative CT measurements were also compared between groups, via χ 2 (categorical) and Mann Whitney U (continuous) variables. RESULTS: Twenty-nine subjects (15 males, age 71 ± 9 years) with high grade or invasive tumor histology comprised the "malignant" cohort, while 22 subjects (11 males, age 70 ± 7 years) with low grade tumor histology were included in the "benign" cohort. Radiomic analysis showed 18/39 precontrast, 19/39 arterial phase, and 21/39 venous phase features differentiated malignant from benign IPMNs (P < 0.05). Multivariate analysis including only ICG criteria yielded two significant variables: thickened and enhancing cyst wall and enhancing mural nodule < 5 mm with an AUC (95%CI) of 0.817 (0.709-0.926). Multivariable post contrast radiomics achieved an AUC (95%CI) of 0.87 (0.767-0.974) for a model including arterial phase radiomics features and 0.834 (0.716-0.953) for a model including venous phase radiomics features. Combined multivariable model including conventional variables and arterial phase radiomics features achieved an AUC (95%CI) of 0.93 (0.85-1.0) with a 5-fold cross validation AUC of 0.90. CONCLUSION: Multi-phase CT radiomics evaluation could play a role in improving predictive capability in diagnosing malignancy in IPMNs. Future larger studies may help determine the clinical significance of our findings.