MR Imaging of the Prostate Gland

Integration of Deep Learning and Active Shape Models for More Accurate Prostate Segmentation in 3D MR Images

Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorithms for prostate segmentation allows us to bypass the huge workload of physicians. In this work, we propose a fully automated hybrid approach for prostate gland segmentation in MR images using an initial segmentation of prostate volumes using a custom-made 3D deep network (VNet-T2), followed by refinement using an Active Shape Model (ASM). While the deep network focuses on three-dimensional spatial coherence of the shape, the ASM relies on local image information and this joint effort allows for improved segmentation of the organ contours. Our method is developed and tested on a dataset composed of T2-weighted (T2w) MRI prostatic volumes of 60 male patients. In the test set, the proposed method shows excellent segmentation performance, achieving a mean dice score and Hausdorff distance of 0.851 and 7.55 mm, respectively. In the future, this algorithm could serve as an enabling technology for the development of computer-aided systems for prostate cancer characterization in MR imaging.

Etiologic classification, evaluation, and management of hematospermia

Hematospermia is defined by the presence of blood in the semen typically occurring in men younger than 40 years of age. Symptoms can occur due to a multitude of reasons, but are usually benign and self-limiting, requiring no additional treatment or evaluation. Despite this, the condition often impairs quality of life due to associated anxiety and must be taken seriously by the patient and the physician, particularly if recurrent, refractory, and painful. The etiology of hematospermia can be classified into inflammatory, infectious, lithiasis, cystic, obstructive, tumoral, vascular, traumatic, iatrogenic, and systemic origin. Alternatively, it can also be divided into subcategories based on anatomical origins such as prostate, bladder, spermatic cord, seminal vesicles, or epididymis. A complete history and physician examination, laboratory testing, and a variety of invasive and non-invasive imaging and instrumentation modalities can help to identify and treat the underlying pathology promptly.