Characteristics and Diagnostic Value of Apparent Diffusion Coefficient (ADC) Values in Pediatric Soft Tissue Tumor Malignancy
Abstract
Background: Pediatric soft tissue tumors are a heterogeneous group of lesions that include benign and malignant tumors, with the prevalence of malignant tumors such as rhabdomyosarcoma (RMS) reaching 7% of pediatric cancers. Early diagnosis is essential to prevent disease progression, but conventional MRI often makes it difficult to distinguish benign and malignant tumors without invasive biopsy. The Apparent Diffusion Coefficient (ADC) value of Diffusion-Weighted Imaging (DWI) offers a non-invasive approach by measuring the diffusion of water molecules, which correlates with the cellular density of the tumor. Objective: To describe the demographic characteristics of pediatric patients with soft tissue tumors undergoing MRI examination and to evaluate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of ADC value in distinguishing benign and malignant tumors. Methods: This retrospective study involved 50 pediatric patients (aged 0–18 years) with soft tissue tumors who underwent MRI and histopathology examinations at Prof. Dr. I.G.N.G. Ngoerah Hospital, Denpasar, for the period 2019–2024. ADC values are measured using the region of interest (ROI) on DWI, with histopathology as the gold standard. Statistical analysis included frequency distribution, ROC analysis, and diagnostic tests to determine sensitivity, specificity, PPV, NPV, and accuracy at the ADC threshold value ? 0.940. Results: The majority of pediatric patients with soft tissue tumors undergoing MRI examination were male (54.0%) with a balanced age distribution between >9.5 years and 1–9.5 years (50% each), and most tumors were benign (74.0%). More than half of the tumors were
Fields of Study & Subjects
MRI in cancer diagnosis
Radiomics and Machine Learning in Medical Imaging
Sarcoma Diagnosis and Treatment
Publication details
- Journal / source
- Asian Journal of Engineering Social and Health
- Volume
- 5
- Issue
- 1
- Pages
- 18–27
- Publication date
- 6 January 2026