0000000000586642
AUTHOR
Maria Cristina Cortese
Multicentric, multifocal, and recurrent osteoid osteoma of the hip: first case report.
Abstract Background Osteoid osteoma is a benign bone-forming tumour, which very unfrequently has multifocal or multicentric presentation. We report the first known case of a multicentric, multifocal and recurrent osteoid osteoma treated using radiofrequency ablation. Case presentation A 39-year-old man with two-year history of left hip pain was admitted at our Institution. The pain was more intense during the night and partially relieved by salicylates. Pelvis CT demonstrated two lytic lesions (8 and 7 mm, respectively) with surrounding sclerotic reactive bone, both with a central focal area of high attenuation, located in the femoral neck and along the anterior portion of the acetabulum, r…
Predictive role of ankle MRI for tendon graft choice and surgical reconstruction.
Purpose: Tendon transfers have become a common surgical procedure around the ankle. In this study, we sought to evaluate the existence of a correlation between specific anthropometric parameters and the size of some ankle tendons measured on MRI, in particular those mostly used as graft in ankle surgery. Methods: We recorded gender, height, weight, and body mass index (BMI) of 113 patients (57 females; mean age: 42 ± 18) who underwent ankle MRI. MRI measurements performed by a radiologist were: axial shortest diameter of Achilles (AT), posterior tibialis (PTT), flexor digitorum longus (FDLT), flexor hallucis longus (FHLT), peroneus longus (PLT), and anterior tibialis (ATT) tendons, intermal…
Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study
Purpose: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine learning (ML) have proven useful even in absence of a standardized data mining pipeline. We aimed to assess ML diagnostic performance in spinal lesion differential diagnosis, employing radiomic data extracted by different software. Methods: Patients undergoing MRI for a vertebral lesion were retrospectively analyzed (n = 146, 67 males, 79 females; mean age 63 ± 16 years, range 8-89 years) and constituted the train (n = 100) and internal test cohorts (n = 46). Part of the latter had additional prior exams which constituted a multi-scanner, external test cohort (n = 35). Lesions were la…
MRI radiomics-based machine-learning classification of bone chondrosarcoma.
Abstract Purpose To evaluate the diagnostic performance of machine learning for discrimination between low-grade and high-grade cartilaginous bone tumors based on radiomic parameters extracted from unenhanced magnetic resonance imaging (MRI). Methods We retrospectively enrolled 58 patients with histologically-proven low-grade/atypical cartilaginous tumor of the appendicular skeleton (n = 26) or higher-grade chondrosarcoma (n = 32, including 16 appendicular and 16 axial lesions). They were randomly divided into training (n = 42) and test (n = 16) groups for model tuning and testing, respectively. All tumors were manually segmented on T1-weighted and T2-weighted images by drawing bidimensiona…