Initial evaluation of automated treatment planning software

Abstract

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

A method for a priori estimation of best feasible DVH for organs‐at‐risk: Validation for head and neck VMAT planning

“…In the PlanIQ software, the user can set up plan quality algorithms that are relevant dosimetric metrics and corresponding scoring functions for each target and OAR. The output is a composite plan quality metric (PQM) . If desired, the FDVH can be used in the current software to normalize any individual metric score based on the best possible sparing for the specific patient, rather than the generic OAR objective.…”

“…To illustrate how the presence of competing objectives changes the achieved DVHs in relation to the single‐OAR FDVHs, the mean doses and DSCs for the same organs as before were calculated for the previously described Pinnacle AP test plans …”

“…In the next step, for validation of FDVH predictions on realistic datasets, 10 previously described advanced HN cases were used. 5 Each patient had two targets: a primary PTV treated to 70 Gy in 35 fractions and an elective bilateral neck clinical target volume (CTV) simultaneously irradiated to 56 Gy. The OARs selected for this study were each parotid, larynx, and inferior pharyngeal constrictor (IPC).…”

“…It is intended as a guide to help generate challenging patient‐specific dose objectives, not as a “predicted DVH” engine. The secondary goal is to allow scored plan metrics, components of a composite Plan Quality Metric (PQM) formalism described previously, to be adjusted for the challenges presented by patient‐specific anatomy.…”

Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning

“…Another suggested approach is computerization of the typical trial-and-error scheme adopted by treatment planners. While some of these methods are site-specific [28], others are developed with the ambition to handle a large class of cases [13,15,27].…”