Abstract
PurposeTo develop a knowledge‐based planning (KBP) routine for stereotactic body radiotherapy (SBRT) of peripherally located early‐stage non‐small‐cell lung cancer (NSCLC) tumors via dynamic conformal arc (DCA)‐based volumetric modulated arc therapy (VMAT) using the commercially available RapidPlanTM software. This proposed technique potentially improves plan quality, reduces complexity, and minimizes interplay effect and small‐field dosimetry errors associated with treatment delivery.MethodsKBP model was developed and validated using 70 clinically treated high quality non‐coplanar VMAT lung SBRT plans for training and 20 independent plans for validation. All patients were treated with 54 Gy in three treatments. Additionally, a novel k‐DCA planning routine was deployed to create plans incorporating historical three‐dimensional‐conformal SBRT planning practices via DCA‐based approach prior to VMAT optimization in an automated planning engine. Conventional KBPs and k‐DCA plans were compared with clinically treated plans per RTOG‐0618 requirements for target conformity, tumor dose heterogeneity, intermediate dose fall‐off and organs‐at‐risk (OAR) sparing. Treatment planning time, treatment delivery efficiency, and accuracy were recorded.ResultsKBPs and k‐DCA plans were similar or better than clinical plans. Average planning target volume for validation was 22.4 ± 14.1 cc (7.1–62.3 cc). KBPs and k‐DCA plans provided similar conformity to clinical plans with average absolute differences of 0.01 and 0.01, respectively. Maximal doses to OAR were lowered in both KBPs and k‐DCA plans. KBPs increased monitor units (MU) on average 1316 (P < 0.001) while k‐DCA reduced total MU on average by 1114 (P < 0.001). This routine can create k‐DCA plan in less than 30 min. Independent Monte Carlo calculation demonstrated that k‐DCA plans showed better agreement with planned dose distribution.ConclusionA k‐DCA planning routine was developed in concurrence with a knowledge‐based approach for the treatment of peripherally located lung tumors. This method minimizes plan complexity associated with model‐based KBP techniques and improve plan quality and treatment planning efficiency.
Highlights
Stereotactic body radiation therapy (SBRT) of lung tumors is an alternative treatment modality to surgery for early stage non‐small‐ cell lung cancer (NSCLC) patients, boasting local control rates greater than 97% at 3‐yr.[1,2,3] These outstanding clinical outcomes were predominantly based on traditional lung stereotactic body radiotherapy (SBRT) treatments performed with 7 to 13 coplanar/non‐coplanar three‐dimensional (3D)‐conformal static beams or with a few dynamic conformal arcs (DCA).[4,5] With modern advances in technology, lung SBRT can be delivered using intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT)
planning target volume (PTV) minimum coverage was maintained while slightly increasing the PTV mean dose (P < 0.001) with no increase in intermediate dose‐spillage with knowledge‐based planning (KBP)
When the proposed automatic planning routine to create a k‐DCA plan was deployed, a higher target dose was achieved at minimal costs to plan quality when compared to clinical plans
Summary
Stereotactic body radiation therapy (SBRT) of lung tumors is an alternative treatment modality to surgery for early stage non‐small‐ cell lung cancer (NSCLC) patients, boasting local control rates greater than 97% at 3‐yr.[1,2,3] These outstanding clinical outcomes were predominantly based on traditional lung SBRT treatments performed with 7 to 13 coplanar/non‐coplanar three‐dimensional (3D)‐conformal static beams or with a few dynamic conformal arcs (DCA).[4,5] With modern advances in technology, lung SBRT can be delivered using intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT). VMAT offers the most conformal dose distribution with higher chances of sparing organs‐at‐risk (OAR).[6] When coupled with a 6 MV flattening filter free (FFF) beam, VMAT benefits are enhanced by providing higher dose rates, reduction in out of field dose, and improved coverage at the lung‐tumor interface when compared to traditionally flattened beams.[7,8]. The generation of a high quality VMAT lung SBRT plan can require multiple iterations of optimization due to difficult patient geometry, tumor size, or location.[9] In general, inverse planning heavily depends on a planner’s experience, treatment planning time, and planner’s skill. This form of KBP has demonstrated success in creating dosimetrically similar or better plans when compared to manual planning across many treatment sites with limited but recently increasing literature for lung SBRT.[12,13,14,15,16,17,18]
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