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Updated: Dec 31, 2025
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
Published on: June 10, 2025
A comparison of virtual touch tissue quantification and digital rectal examination for discrimination between
Xiaozhi Zheng1, Ping Ji, Hongwei Mao
1Department of Ultrasound, The Fourth Affiliated Hospital of Nantong University, China.
Background:
Virtual touch tissue quantification (VTTQ) is a new, promising technique for detecting the stiffness of tissues. The aim of this study is to compare the performance of VTTQ and digital rectal examination (DRE) in discrimination between prostate cancer and benign prostatic hyperplasia (BPH).
Patients And Methods:
VTTQ was performed in 209 prostate nodular lesions of 107 patients with BPH and suspected prostate cancer before the prostate histopathologic examination. The shear wave velocity (SWV) at each nodular lesion was quantified by implementing an acoustic radiation force impulse (ARFI). The performance of VTTQ and DRE in discrimination between prostate cancer and BPH was compared. The diagnostic value of VTTQ and DRE for prostate cancer was evaluated in terms of the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy.
Results:
Prostate cancer was detected in 57 prostate nodular lesions by histopathologic examination. The SWV values (m/s) were significantly greater in prostate cancer and BPH than in normal prostate (2.37 ± 0.94, 1.98 ± 0.82 vs. 1.34 ± 0.47). The area under the receiver operating characteristic curve (AUC) for VTTQ (SWV>2.5m/s) to differentiate prostate nodules as benign hyperplasia or malignancy was 0.86, while it was 0.67 for DRE. The diagnostic sensitivity, specificity, PPV, NPV and accuracy were 71.93 %, 87.5 %, 68.33 %, 89.26 %, 83.25 %, respectively for VTTQ (SWV>2.5m/s), whereas they were 33.33 %, 81.57 %, 40.43 %, 76.54 %, 68.42 % respectively for DRE.
Conclusions:
VTTQ can effectively detect the stiffness of prostate nodular lesions, which has a significantly higher performance than DRE in discrimination between prostate cancer and BPH.
