Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal characteristics after an MR examination, such as susceptibility-weighted imaging or gradient echo imaging (GRE). In this paper, an efficient method for CMB detection in GRE scans is presented. MATERIALS AND METHODS: The proposed framework consists of the following phases: (1) pre-processing (skull extraction), (2) the first training with the ground truth labeled using CMB, (3) the second training with the ground truth labeled with CMB mimicking the same subjects, and (4) post-processing (cerebrospinal fluid (CSF) filtering). The proposed technique was validated on a dataset of 1133 CBMs that consisted of 5284 images for training and 1737 images for testing. We applied a two-stage approach using a region-based CNN method based on You Only Look Once (YOLO) to investigate a novel CMB detection technique. RESULTS: The sensitivity, precision, F1-score and false positive per person (FPavg) were evaluated as 80.96, 60.98, 69.57 and 6.57, 59.69, 62.70, 61.16 and 4.5, 66.90, 79.75, 72.76 and 2.15 for YOLO with a single label, YOLO with double labels, and YOLO + CSF filtering, respectively, and YOLO + CSF filtering showed the highest precision performance, F1-score and lowest FPavg. CONCLUSIONS: Using proposed framework, we developed an optimized CMB learning model with low false positives and a balanced performance in clinical practice.

Multiple myeloma with intractable lumbar pain and diagnostic challenge with MRI: A case report.

We present a 63-year-old male patient with intractable bone pain and rapidly progressive osteoporosis, who was diagnosed with multiple myeloma (MM) by CT despite normal magnetic resonance imaging (MRI) findings. The gold standard diagnostic modality for MM is MRI as it can be used to sensitively evaluate bone marrow, however, the current case highlights that MRI is not always accurate in evaluating MM. CT in combination with MRI could be used for secondary osteoporosis with intractable bone pain in order to determine the diagnosis, treatment, and prognosis.

Parosteal Lipoma Associated with a Growing Osteochondroma of the Right Ilium.

Parosteal lipoma is a rare type of lipoma, the incidence being approximately 0.3% of all lipomas. Moreover, parosteal lipoma coexisting with osteochondroma is extremely rare. A few cases with coexistence of osteochondroma and parosteal lipoma have been reported and they were thought to be reactive changes of adjacent bone by parosteal lipoma. However, temporal relationship of these tumors could not be explained. Here, we report a case of parosteal lipoma associated with osteochondroma of the right ilium developed over 6 years, with follow-up radiographs.