Local Staging of Prostate Cancer Using Three Dimensional (3D) Transrectal Ultrasound Assisted with Power Doppler Capability
Bibliographic record
Abstract
Introduction: The ability to differentiate between carcinoma confined to the prostate and the extra-capsular extension (ECE) of the tumor is the key point for management. ECE of prostate cancer can lead to failure of radical prostatectomy and every attempt should be made to localize the tumor and assess its extensions preoperatively. The study aimed to evaluate the value of three dimensional (3D) Transrectal ultrasound (TRUS) assisted with power Doppler in local staging of prostate cancer. Methodology: -3D TRUS assisted with the power Doppler capability was performed for 120 patients were complaining of burning urination, difficult urination or blood in urine, among them 95 patients were subjected to 3D TRUS guided biopsies. Results: 33 patients showed prostatic carcinomas, 2 patients showed prostatic sarcoma. In patients with proven prostate cancer 3D TRUS showed an estimated sensitivity 85.7% and specificity 90% with a positive predictive value 83.3%, negative predictive value 91.5% and total accuracy 90.9%. 77% of our cancer patients (27/35) showed hypervascularity by power Doppler ultrasonography while 8 patients (23%) showed no abnormal high vascularity. Power Doppler increased the sensitivity of 3D TRUS in the detection of prostate cancer from 85.7% to 88.5% 3D TRUS clearly identified the extra-prostatic spread in 15 out of 18 patients of an estimated sensitivity (83%). Conclusion: 3D TRUS aided with power Doppler is a valuable tool in local staging of prostate cancer .The expected benefits in local staging of prostate cancer from the combination of 3D TRUS, power Doppler and 3D TRUS guided biopsy as one sitting exam, will be highly promising.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".