A structured template for PI-RADS may increase the diagnostic performance of prostate MRI for clinically significant prostate cancer.
A structured template with dropdown menus improved adherence to Prostate Imaging Reporting and Data System (PI-RADS), possibly increasing the diagnostic performance of prostate MRI for clinically significant prostate cancer (CS-PCa), according to a study published in the Journal of the American College of Radiology.
Researchers from Columbia University Medical Center in New York City sought to assess the impact of a structured reporting template on adherence to the PI-RADS version 2 lexicon and on the diagnostic performance of prostate MRI to detect CS-PCa.
The researchers searched an imaging database for consecutive patients who underwent prostate MRI followed by MRI-ultrasound fusion biopsy from October 2015 through October 2017. The initial MRI reporting template included only subheadings but in July 2016, the template was changed to a standardized PI-RADS-compliant structured template incorporating dropdown menus. The researchers extracted from the MRI reports and patient charts, the lesions, patient characteristics, pathology, and adherence to the PI-RADS. Diagnostic performance of prostate MRI to detect CS-PCa using combined ultrasound-MRI fusion and systematic biopsy as a reference standard was assessed.
A total of 324 lesions were found in 202 patients. Their average age was 67 years and average prostate-specific antigen level, 5.9 ng/mL. These results were analyzed, along with 217 MRI peripheral zone (PZ) lesions, 84 MRI non-PZ lesions, and 23 additional PZ lesions found on systematic biopsy but missed on MRI; 33 percent (106 of 324) were CS-PCa.
The researchers found that adherence to the PI-RADS lexicon improved from 32.9 percent (50 of 152) to 88.4 percent (152 of 172) after the structured template was introduced, and the sensitivity of prostate MRI for CS-PCa in the PZ increased from 53 percent to 70 percent. There was no significant change in specificity, with 60 percent versus 55 percent.
The researchers concluded that using a structured template with dropdown menus incorporating the PI-RADS lexicon and classification rules improved adherence to PI-RADS and may increase the diagnostic performance of prostate MRI for CS-PCa.