Person: Craft, David
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Craft
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David
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Craft, David
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Publication Volumetric‐modulated arc therapy using multicriteria optimization for body and extremity sarcoma(John Wiley and Sons Inc., 2016) Young, Michael; Craft, David; Colbert, Caroline M.; Remillard, Kyla; Vanbenthuysen, Liam; Wang, YiThis study evaluates the implementation of volumetric‐modulated arc therapy (VMAT) using multicriteria optimization (MCO) in the RayStation treatment planning system (TPS) for complex sites, namely extremity and body sarcoma. The VMAT‐MCO algorithm implemented in RayStation is newly developed and requires an integrated, comprehensive analysis of plan generation, delivery, and treatment efficiency. Ten patients previously treated by intensity‐modulated radiation therapy (IMRT) with MCO were randomly selected and replanned using VMAT‐MCO. The plan quality was compared using homogeneity index (HI) and conformity index (CI) of the planning target volume (PTV) and dose sparing of organs at risk (OARs). Given the diversity of the tumor location, the 10 plans did not have a common OAR except for skin. The skin D50 and Dmean was directly compared between VMAT‐MCO and IMRT‐MCO. Additional OAR dose points were compared on a plan‐by‐plan basis. The treatment efficiency was compared using plan monitor units (MU) and net beam‐on time. Plan quality assurance was performed using the Sun Nuclear ArcCHECK phantom and a gamma criteria of 3%/3 mm. No statistically significant differences were found between VMAT‐ and IMRT‐MCO for HI and CI of the PTV or D50 and Dmean to the skin. The VMAT‐MCO plans showed general improvements in sparing to OARs. The VMAT‐MCO plan set showed statistically significant improvements over the IMRT‐MCO set in treatment efficiency per plan MU (p<0.05) and net beam‐on time (p<0.01). The VMAT‐MCO plan deliverability was validated. Similar gamma passing rates were observed for the two modalities. This study verifies the suitability of VMAT‐MCO for sarcoma cancer and highlighted the comparability in plan quality and improvement in treatment efficiency offered by VMAT‐MCO as compared to IMRT‐MCO. PACS number(s): separated by commas 87.55.D, 87.55.de, 87.55.QrPublication Shared data for intensity modulated radiation therapy (IMRT) optimization research: the CORT dataset(BioMed Central, 2014) Craft, David; Bangert, Mark; Long, Troy; Papp, Dávid; Unkelbach, JanBackground: We provide common datasets (which we call the CORT dataset: common optimization for radiation therapy) that researchers can use when developing and contrasting radiation treatment planning optimization algorithms. The datasets allow researchers to make one-to-one comparisons of algorithms in order to solve various instances of the radiation therapy treatment planning problem in intensity modulated radiation therapy (IMRT), including beam angle optimization, volumetric modulated arc therapy and direct aperture optimization. Results: We provide datasets for a prostate case, a liver case, a head and neck case, and a standard IMRT phantom. We provide the dose-influence matrix from a variety of beam/couch angle pairs for each dataset. The dose-influence matrix is the main entity needed to perform optimizations: it contains the dose to each patient voxel from each pencil beam. In addition, the original Digital Imaging and Communications in Medicine (DICOM) computed tomography (CT) scan, as well as the DICOM structure file, are provided for each case. Conclusions: Here we present an open dataset – the first of its kind – to the radiation oncology community, which will allow researchers to compare methods for optimizing radiation dose delivery.Publication Pathway-Informed Classification System (PICS) for Cancer Analysis Using Gene Expression Data(Libertas Academica, 2016) Young, Michael; Craft, DavidWe introduce Pathway-Informed Classification System (PICS) for classifying cancers based on tumor sample gene expression levels. PICS is a computational method capable of expeditiously elucidating both known and novel biological pathway involvement specific to various cancers and uses that learned pathway information to separate patients into distinct classes. The method clearly separates a pan-cancer dataset by tissue of origin and also sub-classifies individual cancer datasets into distinct survival classes. Gene expression values are collapsed into pathway scores that reveal which biological activities are most useful for clustering cancer cohorts into subtypes. Variants of the method allow it to be used on datasets that do and do not contain noncancerous samples. Activity levels of all types of pathways, broadly grouped into metabolic, cellular processes and signaling, and immune system, are useful for separating the pan-cancer cohort. In the clustering of specific cancer types, certain pathway types become more valuable depending on the site being studied. For lung cancer, signaling pathways dominate; for pancreatic cancer, signaling and metabolic pathways dominate; and for melanoma, immune system pathways are the most useful. This work suggests the utility of pathway-level genomic analysis and points in the direction of using pathway classification for predicting the efficacy and side effects of drugs and radiation.Publication Multicriteria plan optimization in the hands of physicians: a pilot study in prostate cancer and brain tumors(BioMed Central, 2017) Müller, Birgit S.; Shih, Helen; Efstathiou, Jason; Bortfeld, Thomas; Craft, DavidBackground: The purpose of this study was to demonstrate the feasibility of physician driven planning in intensity modulated radiotherapy (IMRT) with a multicriteria optimization (MCO) treatment planning system and template based plan optimization. Exploiting the full planning potential of MCO navigation, this alternative planning approach intends to improve planning efficiency and individual plan quality. Methods: Planning was retrospectively performed on 12 brain tumor and 10 post-prostatectomy prostate patients previously treated with MCO-IMRT. For each patient, physicians were provided with a template-based generated Pareto surface of optimal plans to navigate, using the beam angles from the original clinical plans. We compared physician generated plans to clinically delivered plans (created by dosimetrists) in terms of dosimetric differences, physician preferences and planning times. Results: Plan qualities were similar, however physician generated and clinical plans differed in the prioritization of clinical goals. Physician derived prostate plans showed significantly better sparing of the high dose rectum and bladder regions (p(D1) < 0.05; D1: dose received by 1% of the corresponding structure). Physicians’ brain tumor plans indicated higher doses for targets and brainstem (p(D1) < 0.05). Within blinded plan comparisons physicians preferred the clinical plans more often (brain: 6:3 out of 12, prostate: 2:6 out of 10) (not statistically significant). While times of physician involvement were comparable for prostate planning, the new workflow reduced the average involved time for brain cases by 30%. Planner times were reduced for all cases. Subjective benefits, such as a better understanding of planning situations, were observed by clinicians through the insight into plan optimization and experiencing dosimetric trade-offs. Conclusions: We introduce physician driven planning with MCO for brain and prostate tumors as a feasible planning workflow. The proposed approach standardizes the planning process by utilizing site specific templates and integrates physicians more tightly into treatment planning. Physicians’ navigated plan qualities were comparable to the clinical plans. Given the reduction of planning time of the planner and the equal or lower planning time of physicians, this approach has the potential to improve departmental efficiencies.