Ultrasonography (US) is noninvasive and offers real-time, low-cost, and portable imaging that facilitates the rapid and dynamic assessment of musculoskeletal components. Significant technological improvements have contributed to the increasing adoption of US for musculoskeletal assessments, as artificial intelligence (AI)-based computer-aided detection and computer-aided diagnosis are being utilized to improve the quality, efficiency, and cost of US imaging. This review provides an overview of classical machine learning techniques and modern deep learning approaches for musculoskeletal US, with a focus on the key categories of detection and diagnosis of musculoskeletal disorders, predictive analysis with classification and regression, and automated image segmentation. Moreover, we outline challenges and a range of opportunities for AI in musculoskeletal US practice.

Translocation between chromosomes 1 and 19 is well documented in ALL. Here, we report a case of refractory anemia with ring sideroblasts associated with marked thrombocytosis with der(19)t(1;19). A 67-yr-old man was admitted to our hospital with anemia and thrombocytosis. The aspirated bone marrow showed erythroid and megakaryocytic hyperplasia and dyspoiesis. Iron staining showed that the ring sideroblasts increased in number. Bone-marrow cell karyotyping showed 46,XY,der(19)t(1;19)(q23;p13)[9]/46,XY,del(5)(q21)[2]/46,XY[9]. PCR analysis showed the absence of the TCF3-PBX1 rearrangement. The patient was treated with hydroxyurea and intermittent blood transfusion. It is known that t(1;19)(q23;p13) leads to a TCF3-PBX1 fusion gene, whose product is a powerful transcriptional activator that plays a key role in the development of ALL. However, t(1;19) has rarely been reported in myeloid neoplasms and the TCF3-PBX1 fusion gene has not been detected. This implies that other genes might be involved in the TCF3-PBX1 rearrangement, or an alternative TCF3-PBX1 fusion transcript with a different breakpoint has not been detected to date. Further research and case studies, including the use of molecular analysis techniques, are required to evaluate the clinical and prognostic significance of t(1;19) in the development of myeloid neoplasms.
Anemia ; Anemia, Refractory ; Blood Transfusion ; Bone Marrow ; Humans ; Hydroxyurea ; Hyperplasia ; Iron ; Karyotyping ; Polymerase Chain Reaction ; Thrombocytosis

Purpose: (1) To evaluate the trabecular pattern at the femoral attachment of the posterior cruciate ligament (PCL) in patients with a PCL injury; (2) to analyze bone microarchitecture by applying gray level co-occurrence matrix (GLCM)-based texture analysis; and (3) to determine if there is a significant relationship between bone microarchitecture and posterior instability. Materials and Methods: The study included 96 patients with PCL tears. Trabecular patterns were evaluated on T2-weighted MRI qualitatively, and were evaluated by GLCM texture analysis quantitatively. The grades of posterior drawer test (PDT) and the degrees of posterior displacement on stress radiographs were recorded. The 96 patients were classified into two groups: acute and chronic injury. And 27 patients with no PCL injury were enrolled for control. Pearson’s correlation coefficient and one-way ANOVA with Bonferroni test were conducted for statistical analyses. This protocol was approved by the Institutional Review Board. Results: A thick and anisotropic trabecular bone pattern was apparent in normal or acute injury (n = 57/61;93.4%), but was not prominent in chronic injury and posterior instability (n = 31/35;88.6%). Grades of PDT and degrees of posterior displacement on stress radiograph were not correlated with texture parameters. However, the texture analysis parameters of chronic injury were significantly different from those of acute injury and control groups (P < 0.05). Conclusion The trabecular pattern and texture analysis parameters are useful in predicting posterior instability in patients with PCL injury. Evaluation of the bone microarchitecture resulting from altered biomechanics could advance the understanding of PCL function and improve the detection of PCL injury.

Purpose: (1) To evaluate the trabecular pattern at the femoral attachment of the posterior cruciate ligament (PCL) in patients with a PCL injury; (2) to analyze bone microarchitecture by applying gray level co-occurrence matrix (GLCM)-based texture analysis; and (3) to determine if there is a significant relationship between bone microarchitecture and posterior instability. Materials and Methods: The study included 96 patients with PCL tears. Trabecular patterns were evaluated on T2-weighted MRI qualitatively, and were evaluated by GLCM texture analysis quantitatively. The grades of posterior drawer test (PDT) and the degrees of posterior displacement on stress radiographs were recorded. The 96 patients were classified into two groups: acute and chronic injury. And 27 patients with no PCL injury were enrolled for control. Pearson’s correlation coefficient and one-way ANOVA with Bonferroni test were conducted for statistical analyses. This protocol was approved by the Institutional Review Board. Results: A thick and anisotropic trabecular bone pattern was apparent in normal or acute injury (n = 57/61;93.4%), but was not prominent in chronic injury and posterior instability (n = 31/35;88.6%). Grades of PDT and degrees of posterior displacement on stress radiograph were not correlated with texture parameters. However, the texture analysis parameters of chronic injury were significantly different from those of acute injury and control groups (P < 0.05). Conclusion The trabecular pattern and texture analysis parameters are useful in predicting posterior instability in patients with PCL injury. Evaluation of the bone microarchitecture resulting from altered biomechanics could advance the understanding of PCL function and improve the detection of PCL injury.