Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-small Cell Lung Cancer

Abstract

Purpose-We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs).Methods and Materials-We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTV orig ) in 3 equispaced steps to the predicted residue (PTV pred ). Patients were treated with a uniform prescription dose to PTV orig . By contrast, PTP optimization started with the same prescription dose to PTV orig but linearly increased the dose at each step, until reaching the highest dose achievable to PTV pred consistent with OAR limits. This method is compared with midcourse adaptive replanning.Results-Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm 3 . On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTV orig at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach.Conclusions-PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

Exploratory study of the association of volumetric modulated arc therapy (VMAT) plan robustness with local failure in head and neck cancer

“…Small degrees of uncertainty (≤ 3 mm in any direction) appear to lead to LF and should be accounted for with robust planning. Recently, several groups have proposed using robust probabilistic planning to replace the concept of PTV in photon therapy . The plan robustness quantification tools developed for this study could help design knowledge‐based anisotropic margins in our clinical practice.…”

An overview on personalisation of radiotherapy prescriptions in locally advanced non-small cell lung cancer: Are we there yet?

“…As a result, the findings were evaluated in a qualitative manner. 19 relevant publications were identified (Figure1) [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32].…”

“…Nine studies [24][25][26][27][28][29][30][31][32] were identified that outlined novel concepts which may prove to be a future basis for personalised RT prescriptions, findings are summarised in Table 3. These studies can be broadly categorised depending on the patient specific feature they are utilising as a basis for personalisation.…”

“…One approach attempted to generate a mathematical model that would predict visible tumour response to radiation therapy during treatment and consequently also predicted a residual disease volume that would remain at the end of RT delivery. This was generated from a database of treated patients was the focus of both a feasibility study [26] and a follow up analysis [27]. Disease response to treatment was predicted prior to treatment delivery and an individualised simultaneous integrated boost (SIB) to this 'residual' volume would then be prescribed at the outset.…”

“…Disease response to treatment was predicted prior to treatment delivery and an individualised simultaneous integrated boost (SIB) to this 'residual' volume would then be prescribed at the outset. Dose escalation to the residual volume was determined to be feasible [26] but the cohort of patients was small (n=5). The follow up study n=10 [27] found that use of this predictive approach facilitated mean dose escalation of 10.4Gy, to the actual residual tumour volume.…”