Data-Driven Approach to Generating Achievable Dose–Volume Histogram Objectives in Intensity-Modulated Radiotherapy Planning

Wu, Binbin; Ricchetti, F.; Sanguineti, Giuseppe; Kazhdan, Michael; Simari, Patricio; Jacques, R.; Taylor, Russell H.; McNutt, Todd

doi:10.1016/j.ijrobp.2010.05.026

Cited by 226 publications

(247 citation statements)

References 10 publications

(9 reference statements)

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“…Wu et al have used a database of plans for IMRT treatment plan quality control as well as for generating dose-volume histogram objectives [44,45]. Additionally, the challenges of addressing issues of variability in manual contouring and segmentation, particularly for head and neck cancers, are being explored with atlas-based solutions that utilize patient databases [46][47][48].…”

Section: Knowledge-based Applicationsmentioning

confidence: 99%

Knowledge-based IMRT treatment planning for prostate cancer

et al. 2011

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The goal of intensity-modulated radiation therapy (IMRT) treatment plan optimization is to produce a cumulative dose distribution that satisfies both the dose prescription and the normal tissue dose constraints. The typical manual treatment planning process is iterative, time consuming, and highly dependent on the skill and experience of the planner. We have addressed this problem by developing a knowledgebased approach that utilizes a database of prior plans to leverage the planning expertise of physicians and physicists at our institution. We developed a case-similarity algorithm that uses mutual information to identify a similar matched case for a given query case, and various treatment parameters from the matched case are then adapted to derive new treatment plans that are patient specific.We used 10 randomly selected cases matched against a knowledge base of 100 cases to demonstrate that new, clinically acceptable IMRT treatment plans can be developed. This approach substantially reduced planning time by skipping all but the last few iterations of the optimization process. Additionally, we established a simple metric based on the areas under the curve (AUC) of the dose volume histogram (DVH), specifically for the planning target volume (PTV), rectum, and bladder. This plan quality metric was used to successfully rank order the plan quality of a collection of knowledgebased plans. Further, we used 100 pre-optimized plans (20 query x 5 matches) to show that the average normalized MI score can be used as a surrogate of overall plan quality.Plans of lower pre-optimized plan quality tended to improve substantially after optimization, though its final plan quality did not improve to the same level as a plan that has a higher pre-optimized plan quality to begin with. Optimization usually improved PTV coverage slightly while providing substantial dose sparing for both v bladder and rectum of 12.4% and 9.1% respectively. Lastly, we developed new treatment plans for cases selected from an outside institution matched against our sitespecific database. The knowledge-based plans are very comparable to the original manual plan, providing adequate PTV coverage as well as substantial improvement in dose sparing to the rectum and bladder.In conclusion, we found that a site-specific database of prior plans can be effectively used to design new treatment plans for our own institution as well as outside cases. Specifically, knowledge-based plans can provide clinically acceptable planning target volume coverage and clinically acceptable dose sparing to the rectum and bladder. This approach has been demonstrated to improve the efficiency of the treatment planning process, and may potentially improve the quality of patient care by enabling more consistent treatment planning across institutions.vi

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Section: Knowledge-based Applicationsmentioning

confidence: 99%

Knowledge-based IMRT treatment planning for prostate cancer

et al. 2011

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“…A database of previously accepted plans for a specific disease site is built. A new plan is supposed to achieve quality comparable to the previous cases with similar patient anatomy and objectives 7 , 8 , 9 , 10 . Another approach to partially automating the dose optimization process is implemented in the AutoPlanning (AP) software module, an option with Pinnacle v. 9.10 TPS (Philips Medical Systems, Fitchburg, WI).…”

Section: Introductionmentioning

confidence: 99%

Initial evaluation of automated treatment planning software

Gintz

Latifi

Caudell

et al. 2016

J Applied Clin Med Phys

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Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose‐volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post‐treatment autoplanning (AP) were compared to the original human‐driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed‐rank test p=0.027). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands (p<0.001) and the inferior pharyngeal constrictor (p=0.016), as well as for the maximum doses to the spinal cord (p=0.018) and brainstem (p=0.040). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing.PACS number(s): 87.55.D

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“…It is also possible that the relationship between rectal dose reduction and hydrogel is not adequately described by onedimensional measures utilized here, since the hydrogel was observed to vary in geometric shape as well as thickness. Other metrics such as overlap volume histograms, which take into account three-dimensional geometric relationships between target volumes and organs at risk to determine achievable dose-volume histograms, may be useful in this regard (12). In a separate study using a subset of patients, we found that an overlap-volume histogram metric was more predictive of rectal sparing than volume of injected gel (13) The effect of plan conformity on rectal V70 was demonstrated by the presence of significant correlations between the two measures on both pre-and post-injection plans.…”

Section: Discussionmentioning

confidence: 99%

A multi-institutional clinical trial of rectal dose reduction via injected polyethylene-glycol hydrogel during IMRT for prostate cancer: Analysis of dosimetric outcomes.

Song¹,

Herfarth²,

Uhl³

et al. 2013

JCO

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Purpose-To characterize the effect of a prostate-rectum spacer on dose to rectum during external beam radiotherapy for prostate cancer, and to assess for factors correlated with rectal dose reduction.Materials and methods-Fifty-two patients at 4 institutions were enrolled onto a prospective pilot clinical trial. Patients underwent baseline scans, then were injected with perirectal spacing hydrogel and re-scanned. IMRT plans were created on both scans for comparison. Objectives were to establish rates of creation of ≥7.5mm of prostate-rectal separation, and decrease in rectal V70 of ≥25%. Multiple regression analysis was performed to evaluate associations between pre-vs. postinjection changes in rectal V70 and changes in plan conformity, rectal volume, bladder volume, bladder V70, PTV volume, as well as post-injection mid-gland separation, gel volume, gel thickness, length of PTV/gel contact, or gel left-to-right symmetry.Results-Hydrogel resulted in ≥ 7.5mm prostate-rectal separation in 95.8% of patients; 95.7% had decreased rectal V70 of ≥ 25%, with mean reduction of 8.0 Gy. There were no significant differences in pre-and post-injection prostate, PTV, rectal, and bladder volumes. Plan conformities were significantly different pre-vs. post-injection (P = 0.02); plans with worse conformity indexes post-injection compared to pre-injection (n=13) still had improvements in rectal V70. In multiple regression analysis, greater post-injection reduction in V70 was associated with decreased relative post-injection plan conformity (P=0.01). Reductions in V70 did not significantly vary by institution, despite significant inter-institutional variations in plan conformity. There were no significant relationships between reduction in V70 and the other characteristics analyzed. Conflict of Interest NotificationThis work was supported by funding from Augmenix Inc., including provision of research materials (hydrogel), funding for data monitoring support, and research-related travel costs. Drs. Song, DeWeese, and Ford have also received consulting fees from Augmenix Inc. Conclusions-Injection of hydrogel into prostate-rectal interface resulted in dose reductions to rectum for > 90% of patients treated. Rectal sparing was statistically significant across a range of 10-75 Gy, and was demonstrated within the presence of significant inter-institutional variability in plan conformity, target definitions, and injection results. NIH Public Access

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Data-Driven Approach to Generating Achievable Dose–Volume Histogram Objectives in Intensity-Modulated Radiotherapy Planning

Cited by 226 publications

References 10 publications

Knowledge-based IMRT treatment planning for prostate cancer

Knowledge-based IMRT treatment planning for prostate cancer

Initial evaluation of automated treatment planning software

A multi-institutional clinical trial of rectal dose reduction via injected polyethylene-glycol hydrogel during IMRT for prostate cancer: Analysis of dosimetric outcomes.

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