The Anderson nomograms for permanent interstitial prostate implants: a briefing for practitioners.
Academic Article
Overview
abstract
PURPOSE: The objective of this report is to re-evaluate the role of the Anderson nomograms in treatment planning for permanent prostate implants. The incentive for revisiting this topic concerns three issues: (1) Although nomograms continue to be used in many centers for ordering seeds, few centers use them during treatment planning; (2) Whereas nomograms were designed to deliver a minimum peripheral dose for a uniform distribution of seeds in the gland, many practitioners use peripheral seed loading patterns to reduce urethral toxicity; and (3) As preoperative and intraoperative treatment planning is becoming standard, the apparent role of nomograms is diminished. The nomogram method is reviewed in terms of: (1) total activity predicted, (2) target coverage (as planned in the operating room and as calculated from postimplant computed tomography studies), and (3) reproducibility (i.e., patient-to-patient and planner-to-planner variability). In each case, the computer-optimization system for intraoperative planning currently in use at our institution was taken as the "gold standard." METHODS AND MATERIALS: We compared for the same patient the results of nomogram planning to those yielded by genetic algorithm (GA) optimization in terms of total activity predicted (n = 20 cases) and percent target coverage (n = 5 cases). Furthermore, we examined retrospectively the dosimetry of 61 prostate implants planned with the GA (n = 27) and the current implementation of Anderson nomograms (n = 34). RESULTS: Nomogram predictions of the total activity required are in good agreement (within 10%) with the GA-planned activity. However, computer-optimized plans consistently yield superior plans, as reflected in both pre- and postimplant analyses. We find also that user (specifically, treatment planner) implementation of the nomograms may be a major source of variability in nomogram planning-a difficulty to which robust computer optimization is less prone. CONCLUSIONS: Nomograms continue to be useful tools for predicting the total required activity for volume implants, and thus for performing an independent check of this quantity. Not unexpectedly, computer optimization remains the preferred planning method. Generally, nomogram-guided implants do not incorporate structures other than the treatment volume into the planning process. Further yet, they deliver a lower dose than that prescribed and result in greater variability among plans than computer-optimized treatments. In summary, nomograms (1) remain an efficient quality assurance tool for computer-generated plans, (2) serve as a good predictor of the number of seeds required for ordering purposes, and (3) provide a simple and dependable backup planning method in case the intraoperative planning system fails.
