Fully automated VMAT treatment planning for advanced-stage NSCLC patients

Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer

PURPOSE

The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer.

METHODS

A DL model was developed for predicting patient-specific doses, trained and validated on a dataset of 235 patients with diverse target volumes and prescriptions. The model was integrated into clinical workflow with DL-predicted objective functions. The automatic plans were retrospectively designed for additional 50 treated manual volumetric modulated arc therapy (VMAT) plans. A comparison was made between automatic and manual plans in terms of dosimetric indexes, monitor units (MUs) and planning time. Plan quality metric (PQM) encompassing these indexes was evaluated, with higher PQM values indicating superior plan quality. Qualitative evaluations of two plans were conducted by four reviewers.

RESULTS

The PQM score was 40.7 ± 13.1 for manual plans and 40.8 ± 13.5 for automatic plans (P = 0.75). Compared to manual plans, the targets coverage and homogeneity of automatic plans demonstrated no significant difference. Manual plans exhibited better sparing for lung in V5 (difference: 1.8 ± 4.2 %, P = 0.02), whereas automatic plans showed enhanced sparing for heart in V30 (difference: 1.4 ± 4.7 %, P = 0.02) and for spinal cord in Dmax (difference: 0.7 ± 4.7 Gy, P = 0.04). The planning time and MUs of automatic plans were significantly reduced by 70.5 ± 20.0 min and 97.4 ± 82.1. Automatic plans were deemed acceptable in 88 % of the reviews (176/200).

CONCLUSIONS

The DL-assisted approach for lung cancer notably decreased planning time and MUs, while demonstrating comparable or superior quality relative to manual plans. It has the potential to provide benefit to lung cancer patients.

Fully automated volumetric modulated arc therapy technique for radiation therapy of locally advanced breast cancer

BACKGROUND

This study aimed to evaluate an a-priori multicriteria plan optimization algorithm (mCycle) for locally advanced breast cancer radiation therapy (RT) by comparing automatically generated VMAT (Volumetric Modulated Arc Therapy) plans (AP-VMAT) with manual clinical Helical Tomotherapy (HT) plans.

METHODS

The study included 25 patients who received postoperative RT using HT. The patient cohort had diverse target selections, including both left and right breast/chest wall (CW) and III-IV node, with or without internal mammary node (IMN) and Simultaneous Integrated Boost (SIB). The Planning Target Volume (PTV) was obtained by applying a 5 mm isotropic expansion to the CTV (Clinical Target Volume), with a 5 mm clip from the skin. Comparisons of dosimetric parameters and delivery/planning times were conducted. Dosimetric verification of the AP-VMAT plans was performed.

RESULTS

The study showed statistically significant improvements in AP-VMAT plans compared to HT for OARs (Organs At Risk) mean dose, except for the heart and ipsilateral lung. No significant differences in V95% were observed for PTV breast/CW and PTV III-IV, while increased coverage (higher V95%) was seen for PTV IMN in AP-VMAT plans. HT plans exhibited smaller values of PTV V105% for breast/CW and III-IV, with no differences in PTV IMN and boost. HT had an average (± standard deviation) delivery time of (17 ± 8) minutes, while AP-VMAT took (3 ± 1) minutes. The average γ passing rate for AP-VMAT plans was 97%±1%. Planning times reduced from an average of 6 h for HT to about 2 min for AP-VMAT.

CONCLUSIONS

Comparing AP-VMAT plans with clinical HT plans showed similar or improved quality. The implementation of mCycle demonstrated successful automation of the planning process for VMAT treatment of locally advanced breast cancer, significantly reducing workload.

Improving knowledge-based treatment planning for lung cancer radiotherapy with automatic multi-criteria optimized training plans

BACKGROUND

Knowledge-based planning (KBP) is a method for automated radiotherapy treatment planning where appropriate optimization objectives for new patients are predicted based on a library of training plans. KBP can save time and improve organ at-risk sparing and inter-patient consistency compared to manual planning, but its performance depends on the quality of the training plans. We used another system for automated planning, which generates multi-criteria optimized (MCO) plans based on a wish list, to create training plans for the KBP model, to allow seamless integration of knowledge from a new system into clinical routine. Model performance was compared for KBP models trained with manually created and automatic MCO treatment plans.

MATERIAL AND METHODS

Two RapidPlan models with the same 30 locally advanced non-small cell lung cancer patients included were created, one containing manually created clinical plans (RP_CLIN) and one containing fully automatic multi-criteria optimized plans (RP_MCO). For 15 validation patients, model performance was compared in terms of dose-volume parameters and normal tissue complication probabilities, and an oncologist performed a blind comparison of the clinical (CLIN), RP_CLIN, and RP_MCO plans.

RESULTS

The heart and esophagus doses were lower for RP_MCO compared to RP_CLIN, resulting in an average reduction in the risk of 2-year mortality by 0.9 percentage points and the risk of acute esophageal toxicity by 1.6 percentage points with RP_MCO. The oncologist preferred the RP_MCO plan for 8 patients and the CLIN plan for 7 patients, while the RP_CLIN plan was not preferred for any patients.

CONCLUSION

RP_MCO improved OAR sparing compared to RP_CLIN and was selected for implementation in the clinic. Training a KBP model with clinical plans may lead to suboptimal output plans, and making an extra effort to optimize the library plans in the KBP model creation phase can improve the plan quality for many future patients.

Per-fraction planning to enhance optimization degrees of freedom compared to the conventional single-plan approach

Objective. In conventional radiotherapy, a single treatment plan is generated pre-treatment, and delivered in daily fractions. In this study, we propose to generate different treatment plans for all fractions ('Per-fraction' planning) to reduce cumulative organs at risk (OAR) doses. Per-fraction planning was compared to the 'Conventional' single-plan approach for non-coplanar 4 × 9.5 Gy prostate stereotactic body radiation therapy (SBRT).Approach. An in-house application for fully automated, non-coplanar multi-criterial treatment planning with integrated beam angle and fluence optimization was used for plan generations. For the Conventional approach, a single 12-beam non-coplanar IMRT plan with individualized beam angles was generated for each of the 20 included patients. In Per-fraction planning, four fraction plans were generated for each patient. For each fraction, a different set of patient-specific 12-beam configurations could be automatically selected. Per-fraction plans were sequentially generated by adding dose to already generated fraction plan(s). For each fraction, the cumulative- and fraction dose were simultaneously optimized, allowing some minor constraint violations in fraction doses, but not in cumulative.Main results. In the Per-fraction approach, on average 32.9 ± 3.1 [29;39] unique beams per patient were used. PTV doses in the separate Per-fraction plans were acceptable and highly similar to those in Conventional plans, while also fulfilling all OAR hard constraints. When comparing total cumulative doses, Per-fraction planning showed improved bladder sparing for all patients with reductions in Dmean of 22.6% (p= 0.0001) and in D1cc of 2.0% (p= 0.0001), reductions in patient volumes receiving 30% and 50% of the prescribed dose of 54.7% and 6.3%, respectively, and a 3.1% lower rectum Dmean (p= 0.007). Rectum D1cc was 4.1% higher (p= 0.0001) and Urethra dose was similar.Significance. In this proof-of-concept paper, Per-fraction planning resulted in several dose improvements in healthy tissues compared to the Conventional single-plan approach, for similar PTV dose. By keeping the number of beams per fraction the same as in Conventional planning, reported dosimetric improvements could be obtained without increase in fraction durations. Further research is needed to explore the full potential of the Per-fraction planning approach.

Machine learning in non-small cell lung cancer radiotherapy: A bibliometric analysis

Background

Machine learning is now well-developed in non-small cell lung cancer (NSCLC) radiotherapy. But the research trend and hotspots are still unclear. To investigate the progress in machine learning in radiotherapy NSCLC, we performed a bibliometric analysis of associated research and discuss the current research hotspots and potential hot areas in the future.

Methods

The involved researches were obtained from the Web of Science Core Collection database (WoSCC). We used R-studio software, the Bibliometrix package and VOSviewer (Version 1.6.18) software to perform bibliometric analysis.

Results

We found 197 publications about machine learning in radiotherapy for NSCLC in the WoSCC, and the journal Medical Physics contributed the most articles. The University of Texas MD Anderson Cancer Center was the most frequent publishing institution, and the United States contributed most of the publications. In our bibliometric analysis, “radiomics” was the most frequent keyword, and we found that machine learning is mainly applied to analyze medical images in the radiotherapy of NSCLC.

Results

The research we identified about machine learning in NSCLC radiotherapy was mainly related to the radiotherapy planning of NSCLC and the prediction of treatment effects and adverse events in NSCLC patients who were under radiotherapy. Our research has added new insights into machine learning in NSCLC radiotherapy and could help researchers better identify hot research areas in the future.

Patient selection, inter-fraction plan robustness and reduction of toxicity risk with deep inspiration breath hold in intensity-modulated radiotherapy of locally advanced non-small cell lung cancer

Background

State-of-the-art radiotherapy of locally advanced non-small cell lung cancer (LA-NSCLC) is performed with intensity-modulation during free breathing (FB). Previous studies have found encouraging geometric reproducibility and patient compliance of deep inspiration breath hold (DIBH) radiotherapy for LA-NSCLC patients. However, dosimetric comparisons of DIBH with FB are sparse, and DIBH is not routinely used for this patient group. The objective of this simulation study was therefore to compare DIBH and FB in a prospective cohort of LA-NSCLC patients treated with intensity-modulated radiotherapy (IMRT).

Methods

For 38 LA-NSCLC patients, 4DCTs and DIBH CTs were acquired for treatment planning and during the first and third week of radiotherapy treatment. Using automated planning, one FB and one DIBH IMRT plan were generated for each patient. FB and DIBH was compared in terms of dosimetric parameters and NTCP. The treatment plans were recalculated on the repeat CTs to evaluate robustness. Correlations between ΔNTCPs and patient characteristics that could potentially predict the benefit of DIBH were explored.

Results

DIBH reduced the median D_mean to the lungs and heart by 1.4 Gy and 1.1 Gy, respectively. This translated into reductions in NTCP for radiation pneumonitis grade ≥2 from 20.3% to 18.3%, and for 2-year mortality from 51.4% to 50.3%. The organ at risk sparing with DIBH remained significant in week 1 and week 3 of treatment, and the robustness of the target coverage was similar for FB and DIBH. While the risk of radiation pneumonitis was consistently reduced with DIBH regardless of patient characteristics, the ability to reduce the risk of 2-year mortality was evident among patients with upper and left lower lobe tumors but not right lower lobe tumors.

Conclusion

Compared to FB, DIBH allowed for smaller target volumes and similar target coverage. DIBH reduced the lung and heart dose, as well as the risk of radiation pneumonitis and 2-year mortality, for 92% and 74% of LA-NSCLC patients, respectively. However, the advantages varied considerably between patients, and the ability to reduce the risk of 2-year mortality was dependent on tumor location. Evaluation of repeat CTs showed similar robustness of the dose distributions with each technique.

Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma

PURPOSE

Complexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of non-coplanar treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated beam angle optimization was used to define non-coplanar VMAT class solutions (CSs), each consisting of a coplanar arc and additional 1 or 2 fixed, non-coplanar partial arcs.

METHODS

Automated planning was used to generate a coplanar VMAT plan with 5 complementary computer-optimized non-coplanar IMRT beams (VMAT+5) for each of the 20 included patients. Subsequently, the frequency distribution of the 100 patient-specific non-coplanar IMRT beam directions was used to select non-coplanar arcs for supplementing coplanar VMAT. A second investigated CS with only one non-coplanar arc consisted of coplanar VMAT plus a partial arc at 90° couch angle (VMATCS90). Plans generated with the two VMATCSs were compared to coplanar VMAT.

RESULTS

VMAT+5 analysis resulted in VMATCS60: two partial non-coplanar arcs at couch angles 60° and -60° to complement coplanar VMAT. Compared to coplanar VMAT, the non-coplanar VMATCS60 and VMATCS90 yielded substantial average dose reductions in OARs associated with xerostomia and dysphagia, i.e., parotids, submandibular glands, oral cavity and swallowing muscles (p < 0.05) for the same PTV coverage and without violating hard constraints. Impact of non-coplanar treatment and superiority of either VMACS60 and VMATCS90 was highly patient dependent.

CONCLUSIONS

Compared to coplanar VMAT, dose to OARs was substantially reduced with a CS with one or two non-coplanar arcs. Preferences for coplanar or one or two additional arcs are highly patient-specific, balancing plan quality and treatment time.

Exposure of the heart in lung cancer radiation therapy: A systematic review of heart doses published during 2013 to 2020

BACKGROUND AND PURPOSE

Lung cancer radiotherapy increases the risk of cardiotoxicity and heart radiation dose is an independent predictor of poor survival. This study describes heart doses and strategies aiming to reduce exposure.

MATERIALS AND METHODS

A systematic review of lung cancer dosimetry studies reporting heart doses published 2013-2020 was undertaken. Doses were compared according to laterality, region irradiated, treatment modality (stereotactic ablative body radiotherapy (SABR) and non-SABR), planning technique, and respiratory motion management.

RESULTS

For 392 non-SABR regimens in 105 studies, the average MHD was 10.3 Gy (0.0-48.4) and was not significantly different between left and right-sided tumours. It was similar between IMRT and 3DCRT (10.9 Gy versus 10.6 Gy) and lower with particle beam therapy (proton 7.0 Gy; carbon-ion 1.9 Gy). Active respiratory motion management reduced exposure (7.4 Gy versus 9.3 Gy). For 168 SABR regimens in 35 studies, MHD was 4.0 Gy (0.0-32.4). Exposure was higher in central and lower lobe lesions (6.3 and 5.8 Gy respectively). MHD was lowest for carbon ions (0.5 Gy) compared to other techniques. Active respiratory motion management reduced exposure (2.4 Gy versus 5.0 Gy). Delineation guidelines and Dose Volume Constraints for the heart varied substantially.

CONCLUSIONS

There is scope to reduce heart radiation dose in lung cancer radiotherapy. Consensus on planning objectives, contouring and DVCs for the heart may lead to reduced heart doses in the future. For IMRT, more stringent optimisation objectives may reduce heart dose. Active respiratory motion management or particle therapy may be considered in situations where cardiac dose is high.

Automated Planning for Prostate Stereotactic Body Radiation Therapy on the 1.5 T MR-Linac

Purpose

Adaptive stereotactic body radiation therapy (SBRT) for prostate cancer (PC) by the 1.5 T MR-linac currently requires online planning by an expert user. A fully automated and user-independent solution to adaptive planning (mCycle) of PC-SBRT was compared with user's plans for the 1.5 T MR-linac.

Methods and Materials

Fifty adapted plans on daily magnetic resonance imaging scans for 10 patients with PC treated by 35 Gy (prescription dose [D_p]) in 5 fractions were reoptimized offline from scratch, both by an expert planner (manual) and by mCycle. Manual plans consisted of multicriterial optimization (MCO) of the fluence map plus manual tweaking in segmentation, whereas in mCycle plans, the objectives were sequentially optimized by MCO according to an a-priori assigned priority list. The main criteria for planning approval were a dose ≥95% of the D_p to at least 95% of the planning target volume (PTV), V_33.2 (PTV) ≥ 95%, a dose less than the D_p to the hottest cubic centimeter (V₃₅ ≤ 1 cm³) of rectum, bladder, penile bulb, and urethral planning risk volume (ie, urethra plus 3 mm isotropically), and V₃₂ ≤ 5%, V₂₈ ≤ 10%, and V₁₈ ≤ 35% to the rectum. Such dose-volume metrics, plus some efficiency and deliverability metrics, were used for the comparison of mCycle versus manual plans.

Results

mCycle plans improved target dose coverage, with V_33.2 (PTV) passing on average (±1 SD) from 95.7% (±1.0%) for manual plans to 97.5% (±1.3%) for mCycle plans (P < .001), and rectal dose sparing, with significantly reduced V₃₂, V₂₈, and V₁₈ (P ≤ .004). Although at an equivalent number of segments, mCycle plans consumed moderately more monitor units (+17%) and delivery time (+9%) (P < .001), whereas they were generally faster (–19%) in terms of optimization times (P < .019). No significant differences were found for the passing rates of locally normalized γ (3 mm, 3%) (P = .059) and γ (2 mm, 2%) (P = .432) deliverability metrics.

Conclusions

In the offline setting, mCycle proved to be a trustable solution for automated planning of PC-SBRT on the 1.5 T MR-linac. mCycle integration in the online workflow will free the user from the challenging online-optimization task.

Implementation of automatic plan optimization in Italy: Status and perspectives

PURPOSE

To investigate and report on the diffusion and clinical use of automated radiotherapy planning systems in Italy and to assess the perspectives of the community of Italian medical physicists involved in radiotherapy on the use of these tools.

MATERIALS AND METHODS

A survey of medical physicists (one per Institute) of 175 radiotherapy centers in Italy was conducted between February 21st and April 1st, 2021. The information collected included the institute's characteristics, plan activity, availability/use of automatic tools and related issues regarding satisfaction, criticisms, expectations, and perceived professional modifications. Responses were analysed, including the impact of a few variables such as the institute type and experience.

RESULTS

125 of the centers (71%) answered the survey, with regional variability (range: 47%-100%); among these, 49% have a TPS with some automatic option. Clinical use of automatic planning is present in 33% of the centers, with 13% applying it in >50% of their plans. Among the 125 responding centres the most used systems are Pinnacle (16%), Raystation (9%) and Eclipse (4%). The majority of participants consider the use of automated techniques to be beneficial, while only 1% do not see any advantage; 83% of respondents see the possibility of enriching their professional role as a potential benefit, while 3% see potential threats.

CONCLUSIONS

Our survey shows that 49% of the responding centres have an automatic planning solution although clinically used in only 33% of the cases. Most physicists consider the use of automated techniques to be beneficial and show a prevalently positive attitude.

Enhancing Radiotherapy for Locally Advanced Non-Small Cell Lung Cancer Patients with iCE, a Novel System for Automated Multi-Criterial Treatment Planning Including Beam Angle Optimization

In this study, the novel iCE radiotherapy treatment planning system (TPS) for automated multi-criterial planning with integrated beam angle optimization (BAO) was developed, and applied to optimize organ at risk (OAR) sparing and systematically investigate the impact of beam angles on radiotherapy dose in locally advanced non-small cell lung cancer (LA-NSCLC). iCE consists of an in-house, sophisticated multi-criterial optimizer with integrated BAO, coupled to a broadly used commercial TPS. The in-house optimizer performs fluence map optimization to automatically generate an intensity-modulated radiotherapy (IMRT) plan with optimal beam angles for each patient. The obtained angles and dose-volume histograms are then used to automatically generate the final deliverable plan with the commercial TPS. For the majority of 26 LA-NSCLC patients, iCE achieved improved heart and esophagus sparing compared to the manually created clinical plans, with significant reductions in the median heart D_mean (8.1 vs. 9.0 Gy, p = 0.02) and esophagus D_mean (18.5 vs. 20.3 Gy, p = 0.02), and reductions of up to 6.7 Gy and 5.8 Gy for individual patients. iCE was superior to automated planning using manually selected beam angles. Differences in the OAR doses of iCE plans with 6 beams compared to 4 and 8 beams were statistically significant overall, but highly patient-specific. In conclusion, automated planning with integrated BAO can further enhance and individualize radiotherapy for LA-NSCLC.

Variations in Head and Neck Treatment Plan Quality Assessment Among Radiation Oncologists and Medical Physicists in a Single Radiotherapy Department

Background

Agreement between planners and treating radiation oncologists (ROs) on plan quality criteria is essential for consistent planning. Differences between ROs and planning medical physicists (MPs) in perceived quality of head and neck cancer plans were assessed.

Materials and Methods

Five ROs and four MPs scored 65 plans for in total 15 patients. For each patient, the clinical (CLIN) plan and two or four alternative plans, generated with automated multi-criteria optimization (MCO), were included. There was always one MCO plan aiming at maximally adhering to clinical plan requirements, while the other MCO plans had a lower aimed quality. Scores were given as follows: 1-7 and 1-2, not acceptable; 3-5, acceptable if further planning would not resolve perceived weaknesses; and 6-7, straightway acceptable. One MP and one RO repeated plan scoring for intra-observer variation assessment.

Results

For the 36 unique observer pairs, the median percentage of plans for which the two observers agreed on a plan score (100% = 65 plans) was 27.7% [6.2, 40.0]. In the repeat scoring, agreements between first and second scoring were 52.3% and 40.0%, respectively. With a binary division between unacceptable (scores 1 and 2) and acceptable (3-7) plans, the median inter-observer agreement percentage was 78.5% [63.1, 86.2], while intra-observer agreements were 96.9% and 86.2%. There were no differences in observed agreements between RO-RO, MP-MP, and RO-MP pairs. Agreements for the highest-quality, automatically generated MCO plans were higher than for the CLIN plans.

Conclusions

Inter-observer differences in plan quality scores were substantial and could result in inconsistencies in generated treatment plans. Agreements among ROs were not better than between ROs and MPs, despite large differences in training and clinical role. High-quality automatically generated plans showed the best score agreements.

Automatic VMAT technique to treat glioblastoma: A two years' experience

PURPOSE

The present work aims to guide the physicist in order to start automated planning for the VMAT treatment of glioblastoma multiforme (GBM) by giving a recipe that was set up and tested during a long-term (two years) evaluation.

METHODS

An automatic technique in AutoPlanning module of the Pinnacle3 (Philips Medical Systems, Fitchburg, WI) treatment planning system was created and validated by comparing dose distributions of automatic plans (APs) and manual plans (MPs) and by performing a blind AP-MP comparison on a cohort of 20 patients. Automatic technique was then applied to 145 patients and failures were recorded i.e. the number of times for which dose distributions produced by the automatic module were not suitable for treatment.

RESULTS

Each of the 20 APs considered in the validation step was clinically acceptable and proved to be better (15 cases) or equal (5 cases) respect to MPs. A statistically significant improvement in brain stem, optic pathways, cochleae, pituitary gland and scalp sparing was observed for APs, while no statistically significant differences were recorded in target coverage or plan parameters. For only 5 cases out of the 145 plans the operator intervention was needed in order to obtain a clinical acceptable plan, while for the remaining 140 plans the automatic created solution was suitable.

CONCLUSIONS

A straightforward automatic procedure has been created and tested in our clinic. The AutoPlanning technique proposed represents a reliable tool to improve treatment planning efficiency and the recipe, here presented, could be simply imported to every radiotherapy center.

Comparison of volumetric modulated arc therapy and intensity-modulated radiotherapy for left-sided whole-breast irradiation using automated planning

Background

Published treatment technique comparisons for postoperative left-sided whole breast irradiation (WBI) with deep-inspiration breath-hold (DIBH) are scarce, small, and inconclusive. In this study, fully automated multi-criterial plan optimization, generating a single high-quality, Pareto-optimal plan per patient and treatment technique, was used to compare for a large patient cohort 1) intensity modulated radiotherapy (IMRT) with two tangential fields and 2) volumetric modulated arc therapy (VMAT) with two small tangential subarcs.

Materials and methods

Forty-eight randomly selected patients recently treated with DIBH and 16 × 2.66 Gy were included. The optimizer was configured for the clinical planning protocol. Comparisons between IMRT and VMAT included dosimetric plan parameters, estimated excess relative risks (ERR) for toxicities, delivery times, MUs, and deliverability accuracy at a linac.

Results

The automatically generated IMRT and VMAT plans applied in this study were similar or higher in quality than the manually generated clinical plans. For equal PTVin V95% (98.4 ± 0.9%), VMAT had significant advantages compared to IMRT regarding breast dose homogeneity and doses in heart and ipsilateral lung, at the cost of some minor deteriorations for contralateral breast (few cases with larger deteriorations) and lung. Conformality improved from 1.38 to 1.18 (p < 0.001). With VMAT, ERR for major coronary events and ipsilateral lung tumors were reduced by 3% (range: −1–12%) and 16% (range: −3–38%), respectively. MUs and delivery times were higher for VMAT. There were no statistical differences in γ passing rates.

Conclusion

For WBI in conservative therapy of left-sided breast patients treated with DIBH, VMAT with two tangential subarcs was generally dosimetrically superior to IMRT with two tangential static fields. Results need confirmation by robustness analyses.

Evaluation of fully automated a priori MCO treatment planning in VMAT for head-and-neck cancer

PURPOSE

Automated planning techniques aim to reduce manual planning time and inter-operator variability without compromising the plan quality which is particularly challenging for head-and-neck (HN) cancer radiotherapy. The objective of this study was to evaluate the performance of an a priori-multicriteria plan optimization algorithm on a cohort of HN patients.

METHODS

A total of 14 nasopharyngeal carcinoma (upper-HN) and 14 "middle-lower indications" (lower-HN) previously treated in our institution were enrolled in this study. Automatically generated plans (autoVMAT) were compared to manual VMAT or Helical Tomotherapy planning (manVMAT-HT) by assessing differences in dose delivered to targets and organs at risk (OARs), calculating plan quality indexes (PQIs) and performing blinded comparisons by clinicians. Quality control of the plans and measurements of the delivery times were also performed.

RESULTS

For the 14 lower-HN patients, with equivalent planning target volume (PTV) dosimetric criteria and dose homogeneity, significant decrease in the mean doses to the oral cavity, esophagus, trachea and larynx were observed for autoVMAT compared to manVMAT-HT. Regarding the 14 upper-HN cases, the PTV coverage was generally significantly superior for autoVMAT which was also confirmed with higher calculated PQIs on PTVs for 13 out of 14 patients, whereas PQIs calculated on OARs were generally equivalent. Number of MUs and total delivery time were significantly higher for autoVMAT compared to manVMAT. All plans were considered clinically acceptable by clinicians.

CONCLUSIONS

Overall superiority of autoVMAT compared to manVMAT-HT plans was demonstrated for HN cancer. The obtained plans were operator-independent and required no post-optimization or manual intervention.

Robust dose-painting-by-numbers vs. nonselective dose escalation for non-small cell lung cancer patients

Purpose

Theoretical studies have shown that dose‐painting‐by‐numbers (DPBN) could lead to large gains in tumor control probability (TCP) compared to conventional dose distributions. However, these gains may vary considerably among patients due to (a) variations in the overall radiosensitivity of the tumor, (b) variations in the 3D distribution of intra‐tumor radiosensitivity within the tumor in combination with patient anatomy, (c) uncertainties of the 3D radiosensitivity maps, (d) geometrical uncertainties, and (e) temporal changes in radiosensitivity. The goal of this study was to investigate how much of the theoretical gains of DPBN remain when accounting for these factors. DPBN was compared to both a homogeneous reference dose distribution and to nonselective dose escalation (NSDE), that uses the same dose constraints as DPBN, but does not require 3D radiosensitivity maps.

Methods

A fully automated DPBN treatment planning strategy was developed and implemented in our in‐house developed treatment planning system (TPS) that is robust to uncertainties in radiosensitivity and patient positioning. The method optimized the expected TCP based on 3D maps of intra‐tumor radiosensitivity, while accounting for normal tissue constraints, uncertainties in radiosensitivity, and setup uncertainties. Based on FDG‐PETCT scans of 12 non‐small cell lung cancer (NSCLC) patients, data of 324 virtual patients were created synthetically with large variations in the aforementioned parameters. DPBN was compared to both a uniform dose distribution of 60 Gy, and NSDE. In total, 360 DPBN and 24 NSDE treatment plans were optimized.

Results

The average gain in TCP over all patients and radiosensitivity maps of DPBN was 0.54 ± 0.20 (range 0–0.97) compared to the 60 Gy uniform reference dose distribution, but only 0.03 ± 0.03 (range 0–0.22) compared to NSDE. The gains varied per patient depending on the radiosensitivity of the entire tumor and the 3D radiosensitivity maps. Uncertainty in radiosensitivity led to a considerable loss in TCP gain, which could be recovered almost completely by accounting for the uncertainty directly in the optimization.

Conclusions

Our results suggest that the gains of DPBN can be considerable compared to a 60 Gy uniform reference dose distribution, but small compared to NSDE for most patients. Using the robust DPBN treatment planning system developed in this work, the optimal DPBN treatment plan could be derived for any patient for whom 3D intra‐tumor radiosensitivity maps are known, and can be used to select patients that might benefit from DPBN. NSDE could be an effective strategy to increase TCP without requiring biological information of the tumor.

Changes on myocardial perfusion scintigraphy and contrast-enhanced cardiac magnetic resonance imaging after definitive radiotherapy in patients with lung cancer

Aim:

To determine whether myocardial perfusion scintigraphy (MPS) changes in lung cancer patients treated with radiotherapy (RT) were detectable with late gadolinium enhancement cardiac magnetic resonance imaging (LGE CMR).

Materials and methods:

Twenty-one patients with lung cancer were evaluated pre-RT and at 2 and 6 months post-RT follow-up (FU) with MPS and LGE CMR. MPS changes in the left ventricle (LV) were analysed using the semi-quantitative summed rest score method (20 segments) and the Bull’s-eye-view technique. The LGE CMR studies were analysed for visual signs of myocardial damage (fibrosis), that is, focal LGE in the LV and cardiac function parameters.

Results:

MPS changes were detected in 7/20 patients at 2 months FU and in 8/13 patients at 6 months FU. Only one patient had a new irreversible defect judged to be caused by direct irradiation. MPS changes in two cases were deemed to be caused by attenuation. All new MPS defects were minor and no corresponding myocardial damage, or any functional changes, were evident on LGE CMR.

Findings:

The extent of MPS changes at 6 months FU appeared less prominent than in previous reports. No visual signs or functional changes corresponding to myocardial damage were detected on LGE CMR. A risk for false-positive MPS changes caused by attenuation is evident.

Comprehensive Comparison of Progressive Optimization Algorithm Based Automatic Plan and Manually Planned Treatment Technique for Cervical-Thoracic Esophageal Cancers

Purpose:

The purpose of the present study was first to apply the progressive optimization algorithm based automatic volumetric modulated arc therapy (POA-VMAT) technology to accelerate and improve the radiotherapy of cervicothoracic esophageal cancer (CTEC). We comprehensive analyze the feasibility, normal tissue complication probability (NTCP) and dosimetric results of POA-VMAT, manual based VMAT and step-shoot intensity-modulated radiation therapy (IMRT) plans in the treatment of CTEC.

Methods:

Sixty patients with CTEC with or without concomitant chemotherapy at our institution between 2017 and 2019 were retrospectively identified. The manual 7field-IMRT (7f-IMRT), Single-arc-VMAT and Double-arc-VMAT (Single-Arc/Double-Arc) plans were generated in all cases. The POA-VMAT was designed using the automatic dual-arc VMAT technology of Pinnacle³ 9.10 planning system based on progressive optimization algorithm. Specially, it includes the selection of treatment techniques, the running of automated planning scripts, and the evaluation of the final radiotherapy regimen. Subsequently, quantitative evaluation of plans was performed by means of standard dose–volume histograms, homogeneity index (HI) and conformity index (CI).

Results:

Target dose conformity of the 7f-IMRT plan was inferior to all plans, whereas the Double-Arc plan was slightly inferior to the POA-VMAT but superior to the Single-Arc and 7f-IMRT plan. The HI for 7f-IMRT, Single-Arc, Double-Arc and POA-VMAT were 0.17 ± 0.08, 0.28 ± 0.06, 0.29 ± 0.06 and 0.28 ± 0.03, respectively. For the NTCP results, there was significant statistical difference among POA-VMAT, IMRT and VMAT plans. The total MU was reduced by 48.3% and 42.1% in Single-Arc and POA-VMAT plans compare to IMRT plans.

Conclusions:

By comprehensive consideration, POA-VMAT efficiently generate acceptable treatment plans for CTEC without dose escalation to OARs and overall superior to manual planning which is a good option for treating CTEC.

Sparing Organs at Risk with Simultaneous Integrated Boost Volumetric Modulated Arc Therapy for Locally Advanced Non-Small Cell Lung Cancer: An Automatic Treatment Planning Study

Background

The technique of simultaneous integrated boost volumetric modulated arc therapy (SIB-VMAT) has been widely used in locally advanced non-small cell lung cancer; however, its dosimetric advantages are seldom reported. This study aimed to quantify dosimetric advantages of SIB-VMAT.

Methods

Forty patients with stage III non-small cell lung cancer in our hospital were retrospectively included. SIB-VMAT and conventional VMAT (C-VMAT) plans were generated for every patient using the automatic treatment planning system. A reduced dose was delivered to PTV in SIB-VAMT plans compared to C-VMAT plans (50.4Gy vs 60Gy). The prescribed dose was 50.4 Gy in 28 fractions to PTV and 59.92 Gy in 28 fractions to PGTV in SIB-VMAT plans, while 60 Gy in 30 fractions to PTV in C-VMAT plans. Dose-volume metrics of PTV, total lung, heart, esophagus and spinal cord were recorded. The quality score was used to evaluate organs at risk (OAR) protection for two type prescription plans.

Results

Conformal coverage of the targets (PGTV/PTV) by 95% of the prescription dose was well achieved in radiation plans. SIB-VMAT plans achieved significantly higher quality score than C-VMAT plans (Mean: 68.15±13.32 vs 49.15±13.35, P<0.001). More plans scored above sixty in SIB-VMAT group compared to C-VMAT group (72.5% vs 20%, P<0.001). Notable reductions in mean dose, V₃₀, V₄₀ and V₅₀ of total lung were observed in SIB-VMAT plans compared to C-VMAT plans, with median decreased proportions of 6.5%, 8.7%, 19.6% and 32.1%, respectively. Statistically significant decrease in heart V₃₀ and V₄₀ was also achieved in SIB-VMAT plans, with median decreased proportions of 26.1% and 38.8%. SIB-VMAT plans achieved significant reductions in the maximum doses to both esophagus and spinal cord. Patients with CTV/(GTV+GTVnd) ≥8.6 showed more notable decrease in total lung V₅₀ (median, 33.6% vs 28.8%, P=0.001) in SIB-VMAT plans compared to those with the ratio being less than 8.6.

Conclusion

SIB-VMAT technique could lead to a substantial sparing of normal organs, including lung, heart, esophagus and cord, mainly through reducing high and inter-median dose exposure. Patients with CTV/(GTV+GTVnd) ≥8.6 might benefit more from SIB-VMAT.

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer

Background and purpose: In this study we developed a workflow for fully-automated generation of deliverable IMRT plans for a 1.5 T MR-Linac (MRL) based on contoured CT scans, and we evaluated automated MRL planning for rectal cancer.Methods: The Monte Carlo dose calculation engine used in the clinical MRL TPS (Monaco, Elekta AB, Stockholm, Sweden), suited for high accuracy dose calculations in a 1.5 T magnetic field, was coupled to our in-house developed Erasmus-iCycle optimizer. Clinically deliverable plans for 23 rectal cancer patients were automatically generated in a two-step process, i.e., multi-criterial fluence map optimization with Erasmus-iCycle followed by a conversion into a deliverable IMRT plan in the clinical TPS. Automatically generated plans (AUTOplans) were compared to plans that were manually generated with the clinical TPS (MANplans).Results: With AUTOplanning large reductions in planning time and workload were obtained; 4-6 h mainly hands-on planning for MANplans vs ∼1 h of mainly computer computation time for AUTOplans. For equal target coverage, the bladder and bowel bag D_mean was reduced in the AUTOplans by 1.3 Gy (6.9%) on average with a maximum reduction of 4.5 Gy (23.8%). Dosimetric measurements at the MRL demonstrated clinically acceptable delivery accuracy for the AUTOplans.Conclusions: A system for fully automated multi-criterial planning for a 1.5 T MR-Linac was developed and tested for rectal cancer patients. Automated planning resulted in major reductions in planning workload and time, while plan quality improved. Negative impact of the high magnetic field on the dose distributions could be avoided.

Template-based automation of treatment planning in advanced radiotherapy: a comprehensive dosimetric and clinical evaluation

Despite the recent advanced developments in radiation therapy planning, treatment planning for head-neck and pelvic cancers remains challenging due to large concave target volumes, multiple dose prescriptions and numerous organs at risk close to targets. Inter-institutional studies highlighted that plan quality strongly depends on planner experience and skills. Automated optimization of planning procedure may improve plan quality and best practice. We performed a comprehensive dosimetric and clinical evaluation of the Pinnacle3 AutoPlanning engine, comparing automatically generated plans (AP) with the historically clinically accepted manually-generated ones (MP). Thirty-six patients (12 for each of the following anatomical sites: head-neck, high-risk prostate and endometrial cancer) were re-planned with the AutoPlanning engine. Planning and optimization workflow was developed to automatically generate "dual-arc" VMAT plans with simultaneously integrated boost. Various dose and dose-volume parameters were used to build three metrics able to supply a global Plan Quality Index evaluation in terms of dose conformity indexes, targets coverage and sparing of critical organs. All plans were scored in a blinded clinical evaluation by two senior radiation oncologists. Dose accuracy was validated using the PTW Octavius-4D phantom together with the 1500 2D-array. Autoplanning was able to produce high-quality clinically acceptable plans in all cases. The main benefit of Autoplanning strategy was the improvement of overall treatment quality due to significant increased dose conformity and reduction of integral dose by 6-10%, keeping similar targets coverage. Overall planning time was reduced to 60-80 minutes, about a third of time needed for manual planning. In 94% of clinical evaluations, the AP plans scored equal or better to MP plans. Despite the increased fluence modulation, dose measurements reported an optimal agreement with dose calculations with a γ-pass-rate greater than 95% for 3%(global)-2 mm criteria. Autoplanning engine is an effective device enabling the generation of VMAT high quality treatment plans according to institutional specific planning protocols.

Validation of in-house knowledge-based planning model for advance-stage lung cancer patients treated using VMAT radiotherapy

OBJECTIVES

Radiotherapy plan quality may vary considerably depending on planner's experience and time constraints. The variability in treatment plans can be assessed by calculating the difference between achieved and the optimal dose distribution. The achieved treatment plans may still be suboptimal if there is further scope to reduce organs-at-risk doses without compromising target coverage and deliverability. This study aims to develop a knowledge-based planning (KBP) model to reduce variability of volumetric modulated arc therapy (VMAT) lung plans by predicting minimum achievable lung volume-dose metrics.

METHODS

Dosimetric and geometric data collected from 40 retrospective plans were used to develop KBP models aiming to predict the minimum achievable lung dose metrics via calculating the ratio of the residual lung volume to the total lung volume. Model accuracy was verified by replanning 40 plans. Plan complexity metrics were calculated using locally developed script and their effect on treatment delivery was assessed via measurement.

RESULTS

The use of KBP resulted in significant reduction in plan variability in all three studied dosimetric parameters V5, V20 and mean lung dose by 4.9% (p = 0.007, 10.8 to 5.9%), 1.3% (p = 0.038, 4.0 to 2.7%) and 0.9 Gy (p = 0.012, 2.5 to 1.6Gy), respectively. It also increased lung sparing without compromising the overall plan quality. The accuracy of the model was proven as clinically acceptable. Plan complexity increased compared to original plans; however, the implication on delivery errors was clinically insignificant as demonstrated by plan verification measurements.

CONCLUSION

Our in-house model for VMAT lung plans led to a significant reduction in plan variability with concurrent decrease in lung dose. Our study also demonstrated that treatment delivery verifications are important prior to clinical implementation of KBP models.

ADVANCES IN KNOWLEDGE

In-house KBP models can predict minimum achievable lung dose-volume constraints for advance-stage lung cancer patients treated with VMAT. The study demonstrates that plan complexity could increase and should be assessed prior to clinical implementation.

Evaluation of an AI-Powered Lung Nodule Algorithm for Detection and 3D Segmentation of Primary Lung Tumors

Automated detection and segmentation is a prerequisite for the deployment of image-based secondary analyses, especially for lung tumors. However, currently only applications for lung nodules ≤3 cm exist. Therefore, we tested the performance of a fully automated AI-based lung nodule algorithm for detection and 3D segmentation of primary lung tumors in the context of tumor staging using the CT component of FDG-PET/CT and including all T-categories (T1-T4). FDG-PET/CTs of 320 patients with histologically confirmed lung cancer performed between 01/2010 and 06/2016 were selected. First, the main primary lung tumor within each scan was manually segmented using the CT component of the PET/CTs as reference. Second, the CT series were transferred to a platform with AI-based algorithms trained on chest CTs for detection and segmentation of lung nodules. Detection and segmentation performance were analyzed. Factors influencing detection rates were explored with binominal logistic regression and radiomic analysis. We also processed 94 PET/CTs negative for pulmonary nodules to investigate frequency and reasons of false-positive findings. The ratio of detected tumors was best in the T1-category (90.4%) and decreased continuously: T2 (70.8%), T3 (29.4%), and T4 (8.8%). Tumor contact with the pleura was a strong predictor of misdetection. Segmentation performance was excellent for T1 tumors (r = 0.908, p < 0.001) and tumors without pleural contact (r = 0.971, p < 0.001). Volumes of larger tumors were systematically underestimated. There were 0.41 false-positive findings per exam. The algorithm tested facilitates a reliable detection and 3D segmentation of T1/T2 lung tumors on FDG-PET/CTs. The detection and segmentation of more advanced lung tumors is currently imprecise due to the conception of the algorithm for lung nodules <3 cm. Future efforts should therefore focus on this collective to facilitate segmentation of all tumor types and sizes to bridge the gap between CAD applications for screening and staging of lung cancer.

First fully automated planning solution for robotic radiosurgery - comparison with automatically planned volumetric arc therapy for prostate cancer

BACKGROUND

For conventional radiotherapy treatment units, automated planning can significantly improve plan quality. For robotic radiosurgery, systems for automatic generation of clinically deliverable plans do not yet exist. For prostate stereotactic body radiation therapy (SBRT), few studies have systematically compared VMAT with robotic treatment.

MATERIAL AND METHODS

The multi-criteria autoplanning optimizer, developed at our institute, was coupled to the commercial treatment planning system of our robotic treatment unit, for fully automated generation of clinically deliverable plans (autoROBOT). The system was then validated by comparing autoROBOT plans with manually generated plans. Next, the autoROBOT system was used for systematic comparisons between autoROBOT plans and VMAT plans, that were also automatically generated (autoVMAT). CTV-PTV margins of 3 mm were used for autoROBOT (clinical routine) and autoVMAT plan generation. For autoVMAT, an extra plan was generated with 5 mm margin (often applied for VMAT). Plans were generated for a 4 × 9.5 Gy fractionation scheme.

RESULTS

Compared to manual planning, autoROBOT improved rectum D[Formula: see text] (16%), V[Formula: see text] (75%) and D[Formula: see text] (41%), and bladder D[Formula: see text] (37%) (all p [Formula: see text] .002), with equal PTV coverage. In the autoROBOT and autoVMAT comparison, both with 3 mm margin, rectum doses were lower for autoROBOT by 5% for rectum D[Formula: see text] (p=.002), 33% for V[Formula: see text] (p=.001) and 4% for D[Formula: see text] (p=.05), with comparable PTV coverage and other OAR sparing. With 5 mm margin for VMAT, 18/20 plans had a PTV coverage lower than requested (<95%) and all plans had higher rectum doses than autoROBOT (mean percentage differences of 13% for D[Formula: see text], 69% for V[Formula: see text] and 32% for D[Formula: see text] (all p<.001)).

CONCLUSIONS

The first system for fully automated generation of clinically deliverable robotic plans was built. Autoplanning did largely enhance robotic plan quality, compared to manual planning. Using autoplanning for both the robotic system and VMAT, superiority of non-coplanar robotic treatment compared to coplanar VMAT for prostate SBRT was demonstrated.

Auto- versus human-driven plan in mediastinal Hodgkin lymphoma radiation treatment

Background

Technological advances in Hodgkin lymphoma (HL) radiation therapy (RT) by high conformal treatments potentially increase control over organs-at-risk (OARs) dose distribution. However, plan optimization remains a time-consuming task with great operator dependent variability. Purpose of the present study was to devise a fully automated pipeline based on the Pinnacle³ Auto-Planning (AP) algorithm for treating female supradiaphragmatic HL (SHL) patients.

Methods

CT-scans of 10 female patients with SHL were considered. A “butterfly” (BF) volumetric modulated arc therapy was optimized using SmartArc module integrated in Pinnacle³ v. 9.10 using Collapsed Cone Convolution Superposition algorithm (30 Gy in 20 fractions). Human-driven (Manual-BF) and AP-BF optimization plans were generated. For AP, an optimization objective list of Planning Target Volume (PTV)/OAR clinical goals was first implemented, starting from a subset of 5 patients used for algorithm training. This list was then tested on the remaining 5 patients (validation set). In addition to the BF technique, the AP engine was applied to a 2 coplanar disjointed arc (AP-ARC) technique using the same objective list. For plan evaluation, dose-volume-histograms of PTVs and OARs were extracted; homogeneity and conformity indices (HI and CI), OARs dose-volume metrics and odds for different toxicity endpoints were computed. Non-parametric Friedman and Dunn tests were used to identify significant differences between groups.

Results

A single AP objective list for SHL was obtained. Compared to the manual plan, both AP-plans offer comparable CIs while AP-ARC also achieved comparable HIs. All plans fulfilled the clinical dose criteria set for OARs: both AP solutions performed at least as good as Manual-BF plan. In particular, AP-ARC outperformed AP-BF in terms of heart sparing involving a lower risk of coronary events and radiation-induced lung fibrosis. Hands-on planning time decreased by a factor of 10 using AP on average.

Conclusions

Despite the high interpatient PTV (size and position) variability, it was possible to set a standard SHL AP optimization list with a high level of generalizability. Using the implemented list, the AP module was able to limit OAR doses, producing clinically acceptable plans with stable quality without additional user input. Overall, the AP engine associated to the arc technique represents the best option for SHL.

Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer

Background

Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinically were evaluated for advanced head and neck cancer (HNC).

Methods

Three radiation oncology departments compared 5 different ATPS: 1) Automatic Interactive Optimizer (AIO) in combination with RapidArc (in-house developed and Varian Medical Systems); 2) Auto-Planning (AP) (Philips Radiation Oncology Systems); 3) RapidPlan version 13.6 (RP1) with HNC model from University Hospital A (Varian Medical Systems, Palo Alto, USA); 4) RapidPlan version 13.7 (RP2) combined with scripting for automated setup of fields with HNC model from University Hospital B; 5) Raystation multicriteria optimization algorithm version 5 (RS) (Laboratories AB, Stockholm, Sweden). Eight randomly selected HNC cases from institution A and 8 from institution B were used. PTV coverage, mean and maximum dose to the organs at risk and effective planning time were compared. Ranking was done based on 3 Gy increments for the parallel organs.

Results

All planning systems achieved the hard dose constraints for the PTVs and serial organs for all patients. Overall, AP achieved the best ranking for the parallel organs followed by RS, AIO, RP2 and RP1. The oral cavity mean dose was the lowest for RS (31.3 ± 17.6 Gy), followed by AP (33.8 ± 17.8 Gy), RP1 (34.1 ± 16.7 Gy), AIO (36.1 ± 16.8 Gy) and RP2 (36.3 ± 16.2 Gy). The submandibular glands mean dose was 33.6 ± 10.8 Gy (AP), 35.2 ± 8.4 Gy (AIO), 35.5 ± 9.3 Gy (RP2), 36.9 ± 7.6 Gy (RS) and 38.2 ± 7.0 Gy (RP1). The average effective planning working time was substantially different between the five ATPS (in minutes): < 2 ± 1 for AIO and RP2, 5 ± 1 for AP, 15 ± 2 for RP1 and 340 ± 48 for RS, respectively.

Conclusions

All ATPS were able to achieve all planning DVH constraints and the effective working time was kept bellow 20 min for each ATPS except for RS. For the parallel organs, AP performed the best, although the differences were small.

Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations

Radiotherapy treatment planning of complex radiotherapy techniques, such as intensity modulated radiotherapy and volumetric modulated arc therapy, is a resource-intensive process requiring a high level of treatment planner intervention to ensure high plan quality. This can lead to variability in the quality of treatment plans and the efficiency in which plans are produced, depending on the skills and experience of the operator and available planning time. Within the last few years, there has been significant progress in the research and development of intensity modulated radiotherapy treatment planning approaches with automation support, with most commercial manufacturers now offering some form of solution. There is a rapidly growing number of research articles published in the scientific literature on the topic. This paper critically reviews the body of publications up to April 2018. The review describes the different types of automation algorithms, including the advantages and current limitations. Also included is a discussion on the potential issues with routine clinical implementation of such software, and highlights areas for future research.

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

Standard of care radiotherapy in LA-NSCLC is 60-66 Gy in 30-33 fractions. However outcomes for these patients are poor with 5-year survival in the range of 10-20%. Randomised controlled trials have shown that dose escalation in a linear fashion does not improve outcomes for all patients, thus there is a need to tailor the prescription to the individual patient. This review assesses the strategies published to personalise the radiation therapy dose prescription in LA-NSCLC. A systematic and scoping search of the literature was performed to identify studies that met the inclusion criteria. 19 relevant studies were identified ranging from prospective clinical trials to mathematically modelled concept studies. Heterogeneity existed between all clinical studies. Nine heterogeneous publications proposed methodology to adapt the dose prescription to the individual patient. A number of encouraging strategies have been identified but fall short of the evidence level required to influence clinical practice.

Late toxicity in the randomized multicenter HYPRO trial for prostate cancer analyzed with automated treatment planning

PURPOSE/OBJECTIVE

Assess to what extent the use of automated treatment planning would have reduced organ-at-risk dose delivery observed in the randomized HYPRO trial for prostate cancer, and estimate related toxicity reductions. Investigate to what extent improved plan quality for hypofractionation scheme as achieved with automated planning can potentially reduce observed enhanced toxicity for the investigated hypofractionation scheme to levels observed for conventional fractionation scheme.

MATERIAL/METHODS

For 725 trial patients, VMAT plans were generated with an algorithm for automated multi-criterial plan generation (autoVMAT). All clinically delivered plans (CLINICAL), generated with commonly applied interactive trial-and-error planning were also available for the investigations. Analyses were based on dose-volume histograms (DVH) and predicted normal tissue complication probabilities (NTCP) for late gastrointestinal (GI) toxicity.

RESULTS

Compared to CLINICAL, autoVMAT plans had similar or higher PTV coverage, while large and statistically significant OAR sparing was achieved. Mean doses in the rectum, anus and bladder were reduced by 7.8 ± 4.7 Gy, 7.9 ± 6.0 Gy and 4.2 ± 2.9 Gy, respectively (p < 0.001). NTCPs for late grade ≥2 GI toxicity, rectal bleeding and stool incontinence were reduced from 23.3 ± 9.1% to 19.7 ± 8.9%, from 9.7 ± 2.8% to 8.2 ± 2.8%, and from 16.8 ± 8.5% to 13.1 ± 7.2%, respectively (p < 0.001). Reductions in rectal bleeding NTCP were observed for all published Equivalent Uniform Dose volume parameters, n. AutoVMAT allowed hypofractionation with predicted toxicity similar to conventional fractionation with CLINICAL plans.

CONCLUSION

Compared to CLINICAL, autoVMAT had superior plan quality, with meaningful NTCP reductions for both conventional fractionation and hypofractionation schemes. AutoVMAT plans might reduce toxicity for hypofractionation to levels that were clinically observed (and accepted) for conventional fractionation. This may be relevant when considering clinical use of the investigated hypofractionation schedule with relatively high fraction dose (3.4 Gy).

Automatic replanning of VMAT plans for different treatment machines: A template-based approach using constrained optimization

PURPOSE

To investigate a new automatic template-based replanning approach combined with constrained optimization, which may be highly useful for a rapid plan transfer for planned or unplanned machine breakdowns. This approach was tested for prostate cancer (PC) and head-and-neck cancer (HNC) cases.

METHODS

The constraints of a previously optimized volumetric modulated arc therapy (VMAT) plan were used as a template for automatic plan reoptimization for different accelerator head models. All plans were generated using the treatment planning system (TPS) Hyperion. Automatic replanning was performed for 16 PC cases, initially planned for MLC1 (4 mm MLC) and reoptimized for MLC2 (5 mm) and MLC3 (10 mm) and for 19 HNC cases, replanned from MLC2 to MLC3. EUD, D_mean, D_2%, and D_98% were evaluated for targets; for OARs EUD and D_2% were analyzed. Replanning was considered successful if both plans fulfilled equal constraints.

RESULTS

All prostate cases were successfully replanned. The mean relative target EUD deviation was -0.15% and -0.57% for replanning to MLC2 and MLC3, respectively. OAR sparing was successful in all cases. Replanning of HNC cases from MLC2 to MLC3 was successful in 16/19 patients with a mean decrease of -0.64% in PTV60 EUD. In three cases target doses were substantially decreased by up to -2.58% (PTV60) and -3.44% (PTV54), respectively. Nevertheless, OAR sparing was always achieved as planned.

CONCLUSIONS

Automatic replanning of VMAT plans for a different treatment machine by using pre-existing constraints as a template for a reoptimization is feasible and successful in terms of equal constraints.

Non-coplanar VMAT combined with non-uniform dose prescription markedly reduces lung dose in breath-hold lung SBRT

BACKGROUND AND PURPOSE

In this retrospective treatment planning study, the effect of a uniform and non-uniform planning target volume (PTV) dose coverage as well as a coplanar and non-coplanar volumetric modulated arc therapy (VMAT) delivery approach for lung stereotactic body radiation therapy (SBRT) in deep inspiration breath-hold (DIBH) were compared.

MATERIALS AND METHODS

For 46 patients with lesions in the peripheral lungs, three different treatment plans were generated: First, a coplanar 220° VMAT sequence with a uniform PTV dose prescription (UC). Second, a coplanar 220° VMAT treatment plan with a non-uniform dose distribution in the PTV (nUC). Third, a non-coplanar VMAT dose delivery with four couch angles (0°, ±35°, 90°) and a non-uniform prescription (nUnC) was used. All treatment plans were optimized for pareto-optimality with respect to PTV coverage and ipsilateral lung dose. Treatment sequences were delivered on a flattening-filter-free linear accelerator and beam-on times were recorded. Dosimetric comparison between the three techniques was performed.

RESULTS

For the three scenarios (UC, nUC, nUnC), median gross tumor volume (GTV) doses were 63.4 ± 2.5, 74.4 ± 3.6, and 77.9 ± 3.8 Gy, and ipsilateral V10Gy lung volumes were 15.7 ± 6.1, 13.9 ± 4.7, and 12.0 ± 5.1%, respectively. Normal tissue complication probability of the ipsilateral lung was 3.9, 3.1, and 2.8%, respectively. The number of monitor units were 5141 ± 1174, 4104 ± 786, and 3657 ± 710 MU and the corresponding beam-on times were 177 ± 54, 143 ± 29, and 148 ± 26 s.

CONCLUSION

For SBRT treatments in DIBH, a non-uniform dose prescription in the PTV, combined with a non-coplanar VMAT arc arrangement, significantly spares the ipsilateral lung while increasing dose to the GTV without major treatment time increase.

Automated VMAT planning for postoperative adjuvant treatment of advanced gastric cancer

Background

Postoperative/adjuvant radiotherapy of advanced gastric cancer involves a large planning target volume (PTV) with multi-concave shapes which presents a challenge for volumetric modulated arc therapy (VMAT) planning. This study investigates the advantages of automated VMAT planning for this site compared to manual VMAT planning by expert planners.

Methods

For 20 gastric cancer patients in the postoperative/adjuvant setting, dual-arc VMAT plans were generated using fully automated multi-criterial treatment planning (autoVMAT), and compared to manually generated VMAT plans (manVMAT). Both automated and manual plans were created to deliver a median dose of 45 Gy to the PTV using identical planning and segmentation parameters. Plans were evaluated by two expert radiation oncologists for clinical acceptability. AutoVMAT and manVMAT plans were also compared based on dose-volume histogram (DVH) and predicted normal tissue complication probability (NTCP) analysis.

Results

Both manVMAT and autoVMAT plans were considered clinically acceptable. Target coverage was similar (manVMAT: 96.6 ± 1.6%, autoVMAT: 97.4 ± 1.0%, p = 0.085). With autoVMAT, median kidney dose was reduced on average by > 25%; (for left kidney from 11.3 ± 2.1 Gy to 8.9 ± 3.5 Gy (p = 0.002); for right kidney from 9.2 ± 2.2 Gy to 6.1 ± 1.3 Gy (p <  0.001)). Median dose to the liver was lower as well (18.8 ± 2.3 Gy vs. 17.1 ± 3.6 Gy, p = 0.048). In addition, Dmax of the spinal cord was significantly reduced (38.3 ± 3.7 Gy vs. 31.6 ± 2.6 Gy, p <  0.001). Substantial improvements in dose conformity and integral dose were achieved with autoVMAT plans (4.2% and 9.1%, respectively; p <  0.001). Due to the better OAR sparing in the autoVMAT plans compared to manVMAT plans, the predicted NTCPs for the left and right kidney and the liver-PTV were significantly reduced by 11.3%, 12.8%, 7%, respectively (p ≤ 0.001). Delivery time and total number of monitor units were increased in autoVMAT plans (from 168 ± 19 s to 207 ± 26 s, p = 0.006) and (from 781 ± 168 MU to 1001 ± 134 MU, p = 0.003), respectively.

Conclusions

For postoperative/adjuvant radiotherapy of advanced gastric cancer, involving a complex target shape, automated VMAT planning is feasible and can substantially reduce the dose to the kidneys and the liver, without compromising the target dose delivery.

Electronic supplementary material

The online version of this article (10.1186/s13014-018-1032-z) contains supplementary material, which is available to authorized users.

Automated volumetric modulated arc therapy planning for whole pelvic prostate radiotherapy

Background

For several tumor entities, automated treatment planning has improved plan quality and planning efficiency, and may enable adaptive treatment approaches. Whole-pelvic prostate radiotherapy (WPRT) involves large concave target volumes, which present a challenge for volumetric arc therapy (VMAT) optimization. This study evaluates automated VMAT planning for WPRT-VMAT and compares the results with manual expert planning.

Methods

A system for fully automated multi-criterial plan generation was configured for each step of sequential-boost WPRT-VMAT, with final “autoVMAT” plans being automatically calculated by the Monaco treatment planning system (TPS; Elekta AB, Stockholm, Sweden). Configuration was based on manually generated VMAT plans (manualVMAT) of 5 test patients, the planning protocol, and discussions with the treating physician on wishes for plan improvements. AutoVMAT plans were then generated for another 30 evaluation patients and compared to manualVMAT plans. For all 35 patients, manualVMAT plans were optimized by expert planners using the Monaco TPS.

Results

AutoVMAT plans exhibited strongly improved organ sparing and higher conformity compared to manualVMAT. On average, mean doses (D_mean) of bladder and rectum were reduced by 10.7 and 4.5 Gy, respectively, by autoVMAT. Prostate target coverage (V_95%) was slightly higher (+0.6%) with manualVMAT. In a blinded scoring session, the radiation oncologist preferred autoVMAT plans to manualVMAT plans for 27/30 patients. All treatment plans were considered clinically acceptable. The workload per patient was reduced by > 70 min.

Conclusion

Automated VMAT planning for complex WPRT dose distributions is feasible and creates treatment plans that are generally dosimetrically superior to manually optimized plans.

Electronic supplementary material

The online version of this article (10.1007/s00066-017-1246-2) contains supplementary material, which is available to authorized users.