Use of a Quality Improvement Initiative to Achieve Consistent Reporting of Level of Suspicion for Tumor on Multiparametric Prostate MRI

Standardized Reporting on the Preoperative CT Assessment of Potential Living Renal Transplant Donors: Can We Create a Universal Report Standard to Meet the Needs of Transplant Urologists?

Purpose: Determine whether standardized template reporting for the preoperative assessment of potential living renal transplant donors improves the comprehensiveness of radiology reports to meet the needs of urologists performing renal transplants. Methods: Urologist and radiologist stakeholders from renal transplant centres in our province ratified a standardized reporting template for evaluation of potential renal donors. Three centres (A, B, and C) were designated "intervention" groups. Centre D was the control group, given employment of a site-specific standardized template prior to study commencement. Up to 100 consecutive CT scan reports per centre, pre- and post-implementation of standardized reporting, were evaluated for reporting specific outcome measures. Results: At baseline, all intervention groups demonstrated poor reporting of urologist-desired outcome measures. Centre A discussed 5/13 variables (38%), Centre B discussed 6/13 variables (46%), and Centre C only discussed 1/13 variables (8%) with ≥90% reliability. The control group exhibited consistent reporting, with 11/13 variables (85%) reported at ≥90% reliability. All institutions in the intervention group exhibited excellent compliance to structured reporting post-template implementation (Centres A = 95%, B = 100%, and C = 77%, respectively). Additionally, all intervention centres demonstrated a significant improvement in the comprehensiveness of reports post-template implementation, with statistically significant increases in the reporting of all variables under-reported at baseline (P > .01). Conclusion: Standardized templates across our province for CT scans of potential renal donors promote completeness of reports. Radiologists can reliably provide our surgical colleagues with needed preoperative anatomy and incidental findings, helping to determine suitable transplant donors and reduce potential complications associated with organ retrieval.

Utility of a Rule-Based Algorithm in the Assessment of Standardized Reporting in PI-RADS

RATIONALE AND OBJECTIVES

Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expression (RegEx) matching can be used to automatically categorize prostate mpMRI reports into categories as a means by which to assess for opportunities for quality improvement.

MATERIALS AND METHODS

All prostate mpMRIs performed in the Duke University Health System from January 2, 2015, to January 29, 2021, were analyzed. Exclusion criteria were applied, for a total of 5343 male patients and 6264 prostate mpMRI reports. These reports were then analyzed by our RegEx algorithm to be categorized as PI-RADS 1 through PI-RADS 5, Recurrent Disease, or "No Information Available." A stratified, random sample of 502 mpMRI reports was reviewed by a blinded clinical team to assess performance of the RegEx algorithm.

RESULTS

Compared to manual review, the RegEx algorithm achieved overall accuracy of 92.6%, average precision of 88.8%, average recall of 85.6%, and F1 score of 0.871. The clinical team also reviewed 344 cases that were classified as "No Information Available," and found that in 150 instances, no numerical PI-RADS score for any lesion was included in the impression section of the mpMRI report.

CONCLUSION

Rule-based processing is an accurate method for the large-scale, automated extraction of PI-RADS scores from the text of radiology reports. These natural language processing approaches can be used for future initiatives in quality improvement in prostate mpMRI reporting with PI-RADS.

New RANZCR clinical radiology written report guidelines

The Royal Australian and New Zealand College of Radiologists (RANZCR) Radiology Written Report Guideline was first issued in 2011. A survey-based consultation of clinical radiology members of the college in 2015 found that the vast majority of 235 respondents supported all components of the guideline. Since the original guideline was developed, considerable new research has been published about radiology reporting, particularly regarding structured/template reports. In 2016/17 a RANZCR working group used the consultation results, stakeholder feedback and recent research to develop revised guidelines. This article outlines the consultation survey results and guideline revision process as well as some of the supporting evidence from the literature.

The Institutional Learning Curve of Magnetic Resonance Imaging-Ultrasound Fusion Targeted Prostate Biopsy: Temporal Improvements in Cancer Detection in 4 Years

PURPOSE

While magnetic resonance imaging-ultrasound fusion targeted biopsy allows for improved detection of clinically significant prostate cancer, a concerning amount of clinically significant disease is still missed. We hypothesized that a number of these misses are due to the learning curve associated with magnetic resonance imaging-ultrasound fusion targeted biopsy. We report the results of repeat magnetic resonance imaging-ultrasound fusion targeted biopsy in men with continued suspicion for cancer and the institutional learning curve in the detection of clinically significant prostate cancer with time.

MATERIALS AND METHODS

We analyzed the records of 1,813 prostate biopsies in a prospectively acquired cohort of men who presented for prostate biopsy in a 4-year period. All men were offered prebiopsy magnetic resonance imaging and were assigned a maximum PI-RADS™ (Prostate Imaging Reporting and Data System version 2) score. Biopsy outcomes in men with a suspicious region of interest were compared. The relationship between time and clinically significant prostate cancer detection was analyzed.

RESULTS

The clinically significant prostate cancer detection rate increased 26% with time in men with a PI-RADS 4/5 region of interest. On repeat magnetic resonance imaging-ultrasound fusion targeted biopsy in men with continued suspicion for cancer 53% of those with a PI-RADS 4/5 region of interest demonstrated clinically significant discordance from the initial magnetic resonance imaging-ultrasound fusion targeted biopsy compared to only 23% with a PI-RADS 1/2 region of interest. Significantly less clinically significant prostate cancer was missed or under graded in the most recent biopsies compared to the earliest biopsies.

CONCLUSIONS

The high upgrade rate on repeat magnetic resonance imaging-ultrasound fusion targeted biopsy and the increasing cancer detection rate with time show the significant learning curve associated with magnetic resonance imaging-ultrasound fusion targeted biopsy. Men with low risk or negative biopsies with a persistent, concerning region of interest should be promptly rebiopsied. Improved targeting accuracy with operator experience can help decrease the number of missed cases of clinically significant prostate cancer.

Perception of radiology reporting efficacy by neurologists in general and university hospitals

AIM

To investigate how neurologists perceive the value of the radiology report and to analyse the relation with the neurologists own expertise in radiology and the level of subspecialisation of radiologists.

MATERIALS AND METHODS

A web-based survey was distributed to neurologists. The level of subspecialisation was assessed by the percentage of fellowship-trained radiologists and the percentage of radiologists that were members of the Dutch Society of Neuroradiology.

RESULTS

Most neurologists interpret all computed tomography (CT) and magnetic resonance imaging (MRI) studies themselves, and their self-confidence in making correct interpretations is high. Residents gave higher scores than neurologists for "Radiologist report answers the question" (p=0.039) and for "Radiologist reports give helpful advice" (p=0.001). Neurologists from university hospitals stated more frequently that the report answered their questions than neurologists from general hospitals (p=0.008). The general appreciation for radiology reports was higher for neurologists from university hospitals than from general hospitals (8.2 versus 7.2; p=0.003). Radiologists at university hospitals have a higher level of subspecialisation than those at general hospitals.

CONCLUSION

Subspecialisation of radiologists leads to higher quality of radiology reporting as perceived by neurologists. Because of their expertise in radiology, neurologists are valuable sources of feedback for radiologists. Paying attention to the clinical questions and giving advice tailored to the needs of the referring physicians are opportunities to improve radiology reporting.

Changes in prostate cancer detection rate of MRI-TRUS fusion vs systematic biopsy over time: evidence of a learning curve

BACKGROUND

To determine the effect of urologist and radiologist learning curves and changes in MRI-TRUS fusion platform during 9 years of NCI's experience with multiparametric magnetic resonance imaging (mpMRI)/TRUS fusion biopsy.

METHODS

A prospectively maintained database of patients undergoing mpMRI followed by fusion biopsy (Fbx) and systematic biopsy (Sbx) from 2007 to 2016 was reviewed. The patients were stratified based on the timing of first biopsy. Cohort 1 (7/2007-12/2010) accounted for learning curve. Cohort 2 (1/2011-5/2013) and cohort 3 (5/2013-4/2016) included patients biopsied prior to and after debut of a new software platform, respectively. Clinically significant (CS) disease was defined as Gleason 7 (3+4) or higher. McNemar's test compared cancer detection rates (CDRs) of Sbx and Fbx between time periods.

RESULTS

1528 patients were included in the study with 230, 537 and 761 patients included in three respective cohorts. Median age (interquartile range) was 61.0 (±9.0), 62.0 (±7.3), and 64.0 (±11.0) years in three cohorts, respectively (P<0.001). Fbx and Sbx had comparable CS CDR in cohort 1 (24.8 vs 22.2%, P=0.377). Fbx detected significantly more CS disease compared to Sbx in the following two periods (cohort 2: 31.5 vs 25.0%, P=0.001; cohort 3: 36.4 vs 30.3%, P<0.001) and detected significantly less low risk disease in the same period (cohort 2: 14.5 vs 19.6%, P<0.001; cohort 3: 12.6 vs 16.7%, P<0.001). Even after multivariate adjustment with age, PSA, race, clinical stage and MRI suspicion score, Fbx CS cancer detection increased in successive cohorts (cohort 2: OR 2.23, P=0.043; cohort 3: OR 2.92, P=0.007).

CONCLUSIONS

In the past 9 years, there has been significant improvement in the accuracy of Fbx. Our results show that after an early learning period, Fbx detected higher rates of CS cancer and lower rates of clinically insignificant cancer than Sbx. Software advances allowed for even greater detection of CS disease.

Diagnostic value and relative weight of sequence-specific magnetic resonance features in characterizing clinically significant prostate cancers

Purpose

To assess the diagnostic weight of sequence-specific magnetic resonance features in characterizing clinically significant prostate cancers (csPCa).

Materials and methods

We used a prospective database of 262 patients who underwent T2-weighted, diffusion-weighted, and dynamic contrast-enhanced (DCE) imaging before prostatectomy. For each lesion, two independent readers (R1, R2) prospectively defined nine features: shape, volume (V_Max), signal abnormality on each pulse sequence, number of pulse sequences with a marked (S_Max) and non-visible (S_Min) abnormality, likelihood of extracapsular extension (ECE) and PSA density (dPSA). Overall likelihood of malignancy was assessed using a 5-level Likert score. Features were evaluated using the area under the receiver operating characteristic curve (AUC). csPCa was defined as Gleason ≥7 cancer (csPCa-A), Gleason ≥7(4+3) cancer (csPCa-B) or Gleason ≥7 cancer with histological extraprostatic extension (csPCa-C),

Results

For csPCa-A, the Signal1 model (S_Max+S_Min) provided the best combination of signal-related variables, for both readers. The performance was improved by adding V_Max, ECE and/or dPSA, but not shape. All models performed better with DCE findings than without.

When moving from csPCa-A to csPCa-B and csPCa-C definitions, the added value of V_Max, dPSA and ECE increased as compared to signal-related variables, and the added value of DCE decreased.

For R1, the best models were Signal1+ECE+dPSA (AUC = 0,805 [95%CI:0,757–0,866]), Signal1+V_Max+dPSA (AUC = 0.823 [95%CI:0.760–0.893]) and Signal1+ECE+dPSA [AUC = 0.840 (95%CI:0.774–0.907)] for csPCa-A, csPCA-B and csPCA-C respectively. The AUCs of the corresponding Likert scores were 0.844 [95%CI:0.806–0.877, p = 0.11], 0.841 [95%CI:0.799–0.876, p = 0.52]) and 0.849 [95%CI:0.811–0.884, p = 0.49], respectively.

For R2, the best models were Signal1+V_Max+dPSA (AUC = 0,790 [95%CI:0,731–0,857]), Signal1+V_Max (AUC = 0.813 [95%CI:0.746–0.882]) and Signal1+ECE+V_Max (AUC = 0.843 [95%CI: 0.781–0.907]) for csPCa-A, csPCA-B and csPCA-C respectively. The AUCs of the corresponding Likert scores were 0. 829 [95%CI:0.791–0.868, p = 0.13], 0.790 [95%CI:0.742–0.841, p = 0.12]) and 0.808 [95%CI:0.764–0.845, p = 0.006]), respectively.

Conclusion

Combination of simple variables can match the Likert score’s results. The optimal combination depends on the definition of csPCa.