Abstract
PurposeTo investigate the performance of magnetic resonance imaging (MRI)-based radiomics models for benign and malignant prostate lesion discrimination and extracapsular extension (ECE) and positive surgical margins (PSM) prediction.Methods and materialsIn total, 459 patients who underwent multiparametric MRI (mpMRI) before prostate biopsy were included. Radiomic features were extracted from both T2-weighted imaging (T2WI) and the apparent diffusion coefficient (ADC). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. Radiomics signatures were built using radiomic features on the training set, and integrated models were built by adding clinical characteristics. The areas under the receiver operating characteristic curves (AUCs) were calculated to assess the classification performance on the testing sets.ResultsThe radiomics signatures for benign and malignant lesion discrimination achieved AUCs of 0.775 (T2WI), 0.863 (ADC) and 0.855 (ADC + T2WI). The corresponding integrated models improved the AUC to 0.851/0.912/0.905, respectively. The radiomics signatures for ECE achieved the highest AUC of 0.625 (ADC), and the corresponding integrated model achieved the highest AUC (0.728). The radiomics signatures for PSM prediction achieved AUCs of 0.614 (T2WI) and 0.733 (ADC). The corresponding integrated models reached AUCs of 0.680 and 0.766, respectively.ConclusionsThe MRI-based radiomics models, which took advantage of radiomic features on ADC and T2WI scans, showed good performance in discriminating benign and malignant prostate lesions and predicting ECE and PSM. Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment.
Highlights
Prostate cancer (PCa) is the second most common cancer in males worldwide [1]
Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment
According to the most recent cancer statistics estimated by the American Cancer Society, PCa alone accounted for nearly 20 % of new cancer diagnoses and 10 % of cancer deaths in males in 2019 [2]
Summary
Prostate cancer (PCa) is the second most common cancer in males worldwide [1]. According to the most recent cancer statistics estimated by the American Cancer Society, PCa alone accounted for nearly 20 % of new cancer diagnoses and 10 % of cancer deaths in males in 2019 [2].The clinical gold standard for PCa diagnosis is prostate biopsy, but biopsy may lead to complications such as pain, bleeding, inflammation and dysuria [3,4,5]. Prostate cancer (PCa) is the second most common cancer in males worldwide [1]. Prostatespecific antigen (PSA) tests and digital rectal examinations (DREs) are widely used as non-invasive methods to detect PCa [6]. PSA tests and DREs have high sensitivity but low specificity [7]. After PCa is detected, staging is an important task that significantly influences management of the disease. The evaluation of extracapsular extension (ECE), which indicates that PCa has reached stage T3, is of significance because ECE is associated with cancer-specific survival and can affect the positive surgical margins (PSM) [8]. PSM is regarded as a negative prognostic factor in PCa patients [9]. The presence of PSM within a radical prostatectomy (RP) specimen has a negative effect on prognosis and is linked to a 3.7-fold increase in the risk of biochemical recurrence [10]
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