Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.

Background and Objectives: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the moment when treatment starts. The objective of the study is to predict the malignancy of a bone tumor from magnetic resonance imaging (MRI) using deep learning algorithms. Materials and Methods: The cohort contained 23 patients in the study (14 women and 9 men with ages between 15 and 80). Two pretrained ResNet50 image classifiers are used to classify T1 and T2 weighted MRI scans. To predict the malignancy of a tumor, a clinical model is used. The model is a feed forward neural network whose inputs are patient clinical data and the output values of T1 and T2 classifiers. Results: For the training step, the accuracies of 93.67% for the T1 classifier and 86.67% for the T2 classifier were obtained. In validation, both classifiers obtained 95.00% accuracy. The clinical model had an accuracy of 80.84% for training phase and 80.56% for validation. The receiver operating characteristic curve (ROC) of the clinical model shows that the algorithm can perform class separation. Conclusions: The proposed method is based on pretrained deep learning classifiers which do not require a manual segmentation of the MRI images. These algorithms can be used to predict the malignancy of a tumor and on the other hand can shorten the time of their diagnosis and treatment process. While the proposed method requires minimal intervention from an imagist, it needs to be tested on a larger cohort of patients.

Subchondral insufficiency fractures: overview of MRI findings from hip to ankle joint.

Subchondral insufficiency fracture (SIF) represents a potentially severe condition that can advance to osteoarthritis, with collapse of the articular surface. SIF manifests as a fracture in bone weakened by non-tumorous disease, precipitated by repetitive physiological stress, without a clear history of major trauma. It is observed along the central weight-bearing region of the femoral condyle, with a higher incidence in the medial femoral condyle, but also in other large weight-bearing synovial joints, such as the femoral head, tibial plateau, or talus.A review of the literature from the past six years was performed by searching PubMed and ScienceDirect databases, using the keywords "subchondral insufficiency fracture" and "spontaneous osteonecrosis of the knee". The inclusion criteria were scientific papers presented in the English language that reported on the magnetic resonance imaging (MRI) aspects of SIF of the lower limb.Detecting SIF at the level of the hip, knee, and ankle may present challenges both clinically and radiologically. The MRI appearance is dominated by a bone marrow edema-like signal and subchondral bone changes that can sometimes be subtle. Subchondral abnormalities are more specific than the pattern of bone marrow edema-like signal and are best shown on T2-weighted and proton-density-weighted MR images. MRI plays an important role in accurately depicting even subtle subchondral fractures at the onset of the disease and proves valuable in follow-up, prognosis, and the differentiation of SIF from other conditions. · Subchondral insufficiency fractures may affect the hip, knee, and ankle.. · Subchondral insufficiency fractures may heal spontaneously or progress to collapse.. · MRI is important for the detection, follow-up, and prognosis of subchondral insufficiency fractures.. · Differential diagnosis may include transient osteoporosis and osteonecrosis of systemic origin.. · Buturoiu MM, Ghiea S, Weber M. Subchondral insufficiency fractures: overview of MRI findings from hip to ankle joint. Fortschr Röntgenstr 2024; 196: 1143 - 1154.