Total Tumor Diameter and Unilateral Multifocality as Independent Predictor Factors for Metastatic Papillary Thyroid Microcarcinoma.

The purpose of this study was to assess whether total tumor diameter (TTD) and multifocality are predictors for metastatic disease in papillary thyroid microcarcinomas (PTMC). Eighty-two patients with histologically proven PTMC were retrospectively included. Patients were divided according to the presence of metastatic disease in the metastatic (n = 41) and non-metastatic (n = 41) demographic-matched group. The morphological features of PTMCs (primary tumor diameter, multifocality, TTD, number of foci, and tumor site) were compared between groups using univariate, multivariate, and receiver operating characteristic analyses. TTD (p = 0.026), TTD > 10 mm (p = 0.036), and Unilateral Multifocality (UM) (p = 0.019) statistically differed between the groups. The combination of the two independent predictors (TTD and UM) was able to assess metastatic risk with 60.98% sensitivity and 75.61% specificity. TTD and UM can be used to predict metastatic disease in PTMC, which may help to better adapt the RAI therapy decision. We believe that TTD and multifocality are tumor features that should be considered in future guidelines.

Ultrasonography in the Differentiation of Endometriomas from Hemorrhagic Ovarian Cysts: The Role of Texture Analysis.

The ultrasonographic (US) features of endometriomas and hemorrhagic ovarian cysts (HOCs) are often overlapping. With the emergence of new computer-aided diagnosis techniques, this is the first study to investigate whether texture analysis (TA) could improve the discrimination between the two lesions in comparison with classic US evaluation. Fifty-six ovarian cysts (endometriomas, 30; HOCs, 26) were retrospectively included. Four classic US features of endometriomas (low-level internal echoes, perceptible walls, no solid components, and less than five locules) and 275 texture parameters were assessed for every lesion, and the ability to identify endometriomas was evaluated through univariate, multivariate, and receiver operating characteristics analyses. The sensitivity (Se) and specificity (Sp) were calculated with 95% confidence intervals (CIs). The texture model, consisting of seven independent predictors (five variations of difference of variance, image contrast, and the 10th percentile; 100% Se and 100% Sp), was able to outperform the ultrasound model composed of three independent features (low-level internal echoes, perceptible walls, and less than five locules; 74.19% Se and 84.62% Sp) in the diagnosis of endometriomas. The TA showed statistically significant differences between the groups and high diagnostic value, but it remains unclear if the textures reflect the intrinsic histological characteristics of the two lesions.

Ultrasonography in the Diagnosis of Adnexal Lesions: The Role of Texture Analysis.

The classic ultrasonographic differentiation between benign and malignant adnexal masses encounters several limitations. Ultrasonography-based texture analysis (USTA) offers a new perspective, but its role has been incompletely evaluated. This study aimed to further investigate USTA's capacity in differentiating benign from malignant adnexal tumors, as well as comparing the workflow and the results with previously-published research. A total of 123 adnexal lesions (benign, 88; malignant, 35) were retrospectively included. The USTA was performed on dedicated software. By applying three reduction techniques, 23 features with the highest discriminatory potential were selected. The features' ability to identify ovarian malignancies was evaluated through univariate, multivariate, and receiver operating characteristics analyses, and also by the use of the k-nearest neighbor (KNN) classifier. Three parameters were independent predictors for ovarian neoplasms (sum variance, and two variations of the sum of squares). Benign and malignant lesions were differentiated with 90.48% sensitivity and 93.1% specificity by the prediction model (which included the three independent predictors), and with 71.43-80% sensitivity and 87.5-89.77% specificity by the KNN classifier. The USTA shows statistically significant differences between the textures of the two groups, but it is unclear whether the parameters can reflect the true histopathological characteristics of adnexal lesions.

Does Surgical Margin Width Remain a Challenge for Triple-Negative Breast Cancer? A Retrospective Analysis.

Background and Objectives: Local and distant relapse (LR, DR) in breast cancer vary according to its molecular subtypes, with triple-negative breast cancer (TNBC) being the most aggressive. The surgical resection margin width (SRMW) for breast-conserving surgery (BCS) has been intensely debated, especially for the aforementioned subtype. The aim of this study was to examine the impact of SRMW on LR following BCS in TNBC patients. Materials and Methods: We conducted a retrospective study including all patients with TNBC for whom BCS was performed between 2005 and 2014. Results: Final analysis included a total of 92 patients, with a median tumor size of 2.5 cm (range 0-5 cm) and no distant metastasis at the time of diagnosis. A total of 87 patients had received neoadjuvant and/or adjuvant chemotherapy, and all patients had received adjuvant whole-breast radiotherapy. After a median follow-up of 110.7 months (95% CI, 95.23-126.166), there were 5 local recurrences and 8 regional/distant recurrences with an overall LR rate of 5.4%. The risk of LR and DR was similar between groups of patients with several SRMW cut-off values. Conclusions: Our study supports a safe "no ink on tumor" approach for TNBC patients treated with BCS.