The characteristics and spatial distributions of initially missed and rebiopsy-detected prostate cancers

Quantification of Multi-Parametric Magnetic Resonance Imaging Based on Radiomics Analysis for Differentiation of Benign and Malignant Lesions of Prostate

Background

The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers' opinions.

Objective

The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference.

Material and Methods

It is an analytical research that 27 patients underwent the mp-MRI examination, including T1- and T2- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used.

Results

An accuracy, sensitivity and specificity of 92.6%, 95.2% and 83.3%, respectively, were achieved from a subset of radiomics features obtained from T2-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions.

Conclusion

Quantification of mp-MRI (T2-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions.

Evaluation of MR imaging-targeted biopsies of the prostate in biopsy-naïve patients. A single centre study

PURPOSE

To evaluate the differences in prostate cancer detection rate and biopsy effectiveness between magnetic resonance imaging (MRI) target biopsy (TB) and transperineal standard biopsy (SB) in biopsy-naïve patients.

MATERIAL AND METHODS

Between October 2014 and April 2016, 60 men with a mean age of 64.1±6.7 (SD) years (range: 53-82 years) were prospectively enrolled. All patients underwent a prostate MRI study, evaluated by two radiologists, before undergoing the biopsy. A transperineal 12-core SB was carried out before TB, without the information from the MRI. The detection rate for all tumors and for clinically significant tumors (CS) was recorded. Sampling variables such as the proportion of cores positive for CS cancer (PCP-CS) and the maximum cancer core length (MCCL) were also calculated. The ability of MRI to predict the presence of a CS tumor at biopsy was studied using a sector analysis. Patients with negative biopsies were followed during a minimum of 12 months.

RESULTS

The detection rate for SB and TB was 53.3% (32/60) and 46.7% (28/60) respectively for all tumors (P=0.289) and 45% (27/60) in both techniques for CS tumors. TB obtained a larger PCP-CS (P<0.001) and MCCL (P=0.018). The sensitivity, specificity, positive predictive value, negative predictive value and cancer prevalence was 83.3%, 92.9%, 83.3%, 92.9% and 30% for peripheral zone sectors and 43.8%, 97.1%, 70.0%, 91.8% and 13,3% for transitional zone sectors. The proportion of patients that showed an increase of PSA faster than 0.75ng/mL/year after a negative biopsy was 26.1%.

CONCLUSION

Detection rate of prostate cancer did not show significant differences between a TB and a SB technique in biopsy-naïve patients. However, targeted prostate biopsies demonstrated a better sampling effectiveness thus reducing the cores needed to diagnose clinically significant tumors.