3 research outputs found
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Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials.
PurposeTo demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system.Methods and materialsWe analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volume histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V10 (percentage volume of PBM receiving at least 10 Gy dose) and V20 (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V40 (absolute volume of bowel receiving at least 40 Gy dose) and V45 (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning "routine"). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBPFINAL), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBPFINAL plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets.ResultsKBPFINAL plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBPFINAL versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBPFINAL plans, indicating lowered probability of hematologic toxicity.ConclusionsThis work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints
Utilization of cone-beam CT for offline evaluation of target volume coverage during prostate image-guided radiotherapy based on bony anatomy alignment
AimTo assess target volume coverage during prostate image-guided radiotherapy based on bony anatomy alignment and to assess possibility of safety margin reduction.BackgroundImplementation of IGRT should influence safety margins. Utilization of cone-beam CT provides current 3D anatomic information directly in irradiation position. Such information enables reconstruction of the actual dose distribution.Materials and methodsSeventeen prostate patients were treated with daily bony anatomy image-guidance. Cone-beam CT (CBCT) scans were acquired once a week immediately after bony anatomy alignment. After the prostate, seminal vesicles, rectum and bladder were contoured, the delivered dose distribution was reconstructed. Target dose coverage was evaluated by the proportion of the CTV encompassed by the 95% isodose. Original plans employed a 1[[ce:hsp sp="0.25"/]]cm safety margin. Alternative plans assuming a smaller 7[[ce:hsp sp="0.25"/]]mm margin between CTV and PTV were evaluated in the same way. Rectal and bladder volumes were compared with the initial ones. Rectal and bladder volumes irradiated with doses higher than 75[[ce:hsp sp="0.25"/]]Gy, 70[[ce:hsp sp="0.25"/]]Gy, 60[[ce:hsp sp="0.25"/]]Gy, 50[[ce:hsp sp="0.25"/]]Gy and 40[[ce:hsp sp="0.25"/]]Gy were analyzed.ResultsIn 12% of reconstructed plans the prostate coverage was not sufficient. The prostate underdosage was observed in 5 patients. Coverage of seminal vesicles was not satisfactory in 3% of plans. Most of the target underdosage corresponded to excessive rectal or bladder filling. Evaluation of alternative plans assuming a smaller 7[[ce:hsp sp="0.25"/]]mm margin revealed 22% and 11% of plans where prostate and seminal vesicles coverage, respectively, was compromised. These were distributed over 8 and 7 patients, respectively.ConclusionSufficient dose coverage of target volumes was not achieved for all patients. Reducing of safety margin is not acceptable. Initial rectal and bladder volumes cannot be considered representative for subsequent treatment
Recommended from our members
Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials.
PurposeTo demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system.Methods and materialsWe analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volume histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V10 (percentage volume of PBM receiving at least 10 Gy dose) and V20 (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V40 (absolute volume of bowel receiving at least 40 Gy dose) and V45 (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning "routine"). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBPFINAL), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBPFINAL plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets.ResultsKBPFINAL plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBPFINAL versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBPFINAL plans, indicating lowered probability of hematologic toxicity.ConclusionsThis work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints