The value of magnetic resonance imaging-ultrasound fusion targeted biopsies for clinical decision making among patients with previously negative transrectal ultrasound biopsy and persistent prostate-specific antigen elevation
Bibliographic record
Abstract
INTRODUCTION: Targeted biopsy approaches have been shown to increase the detection of clinically significant prostate cancer (csPCa) within index prostate lesions. We report our initial experience with magnetic resonance imaging-ultrasound fusion biopsies (MRI-TB) in a population of men who had a previously negative transrectal ultrasound (TRUS) biopsy, persistent prostate-specific antigen (PSA) elevation, and ongoing suspicion of PCa. Patients were followed prospectively to assess for changes in clinical management following targeted biopsy. METHODS: We prospectively followed the first 122 patients undergoing MRI-TB at our institution. All men had clinical suspicion of PCa, prior negative TRUS biopsies, and persistent PSA elevation. A total of 177 index lesions were identified on multiparametric MRI and reviewed using the Prostate Imaging Reporting and Data System (PI-RADS) v2 scoring system. Lesions classified as PI-RADS ≥3 received targeted biopsy. Biopsy-naive patients and those on active surveillance were excluded. The primary outcome was detection rate of csPCa, defined as International Society of Urological Pathology (ISUP) Grade Group (GG) ≥2. Multivariate analysis was used to determine predictors of csPCa on fusion biopsy. RESULTS: Prior to fusion biopsy, patients had a mean of 17.9±8.6 negative core biopsies per patient and a median PSA of 9.5 (standard deviation [SD] 6.2) ng/nl. MRI-TB resulted in diagnosis of csPCa in 42/122 (34.4%) patients. Clinically significant PCa was found in eight (13.1%), 14 (21.9%), and 25 (48.1%) of PI-RADS 3, 4, and 5 lesions, respectively. The location of csPCa was within the peripheral zone (55.3%), transitional zone (40.4%), and central zone (8.5%). Clinical outcomes of patients with newly diagnosed csPCa show 4.8%, 57.1%, and 38.1% receiving active surveillance, radiation treatment, and radical prostatectomy, respectively. Predictors for csPCa were presence of PI-RADS 5 lesions, age, length of time from MRI to biopsy, and smaller prostate volumes. CONCLUSIONS: MRI-TB yields high detection rates for csPCa in men with elusive PSA elevation and frequently guides a change in clinical management. Clinical decision-making based on MRI findings and PI-RADS lesion scores are best informed by an understanding of institutional reporting patterns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".