CT-based deep learning segmentation of ovarian cancer and the stability of the extracted radiomics features.

Background: Radiomics analysis could provide complementary tissue characterization in ovarian cancer (OC). However, OC segmentation required in radiomics analysis is time-consuming and labour-intensive. In this study, we aim to evaluate the performance of deep learning-based segmentation of OC on contrast-enhanced CT images and the stability of radiomics features extracted from the automated segmentation.

Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma.

Importance: Epithelial ovarian carcinoma is heterogeneous and classified according to the World Health Organization Tumour Classification, which is based on histologic features and molecular alterations. Preoperative prediction of the histologic subtypes could aid in clinical management and disease prognostication.

Objective: To assess the value of radiomics based on contrast-enhanced computed tomography (CT) in differentiating histologic subtypes of epithelial ovarian carcinoma in multicenter data sets.

CT texture analysis in histological classification of epithelial ovarian carcinoma.

Objectives: The study aimed to compare the ability of morphological and texture features derived from contrast-enhanced CT in histological subtyping of epithelial ovarian carcinoma (EOC).

Methods: Consecutive 205 patients with newly diagnosed EOC who underwent contrast-enhanced CT were included and dichotomised into high-grade serous carcinoma (HGSC) and non-HGSC. Clinical information including age and cancer antigen 125 (CA-125) was documented.

Diffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes.

Background: Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients.

Methods: Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist.

Introducing point-of-care ultrasound through structured multifaceted ultrasound module in the undergraduate medical curriculum at the University of Hong Kong.

Incorporation of point-of-care ultrasound in the undergraduate medical curriculum is of great importance to ensure early exposure and safe use of the modality. We aimed to assess the students' learning experiences following implementing an ultrasound module in the medical curriculum at the University of Hong Kong. Medical students in semester 6 (n = 221) were enrolled in the module in 2018.

Limitation of radiological T3 subclassification of rectal cancer due to paucity of mesorectal fat in Chinese patients.

Objectives: To describe the thickness of mesorectal fat in local Chinese population and its impact on rectal cancer staging.

Design: Case series.

Setting: Two local regional hospitals in Hong Kong.