Adaptive radiotherapy for advanced lung cancer ensures target coverage and decreases lung dose

Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy for Non-Small Cell Lung Cancer Using Varian Ethos Therapy System

We present a patient treated with personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) for non-small cell lung cancer (NSCLC) using the adaptive Varian Ethos™ system equipped with the novel HyperSight imaging platform. Three pulses of 12 Gy were separated by a pause of four weeks during which the tumor was given enough time to respond to treatment. Only initial planning computed tomography (CT) was acquired on a CT simulator (Siemens Somatom Definition Edge), whereas other pulses were adapted using online cone beam computed tomography (CBCT) images (iCBCT Acuros reconstruction) acquired while the patient was lying on the treatment couch and delivered immediately. Significant tumor reduction was achieved between pulses, resulting in improved organs-at-risk sparing. In addition, the on-couch plan optimization based on CBCT greatly reduced the patient's stay at the clinic and the duration of treatment preparation.

Daily CBCT-based dose calculations for enhancing the safety of dose-escalation in lung cancer radiotherapy

PURPOSE

Dose-escalation in lung cancer comes with a high risk of severe toxicity. This study aimed to calculate the delivered dose in a Scandinavian phase-III dose-escalation trial.

METHODS

The delivered dose was evaluated for 21 locally-advanced non-small cell lung cancer (LA-NSCLC) patients treated as part of the NARLAL2 dose-escalation trial. The patients were randomized between standard and escalated heterogeneous dose-delivery. Both treatment plans were created and approved before randomization. Daily cone-beam CT (CBCT) for patient positioning, and adaptive radiotherapy were mandatory. Standard and escalated plans, including adaptive re-plans, were recalculated on each daily CBCT and accumulated on the planning CT for each patient. Dose to the clinical target volume (CTV), organs at risk (OAR), and the effects of plan adaptions were evaluated for the accumulated dose and on each treated fraction scaled to full treatment.

RESULTS

For the standard treatment, plan adaptations reduced the number of patients with CTV-T underdosage from six to one, and the total number of fractions with CTV-T underdosage from 161 to 56; while for the escalated treatment, the number of patients was reduced from five to zero and number of fractions from 81 to 11. For dose-escalation, three patients had fractions exceeding trial constraints for heart, bronchi, or esophagus, and one had an accumulated heart dose above the constraints.

CONCLUSION

Dose-escalation for LA-NSCLC patients, using daily image guidance and adaptive radiotherapy, is dosimetrically safe for the majority of patients. Dose calculation on daily CBCTs is an efficient tool to monitor target coverage and OAR doses.

Optimising hypoxia PET imaging and its applications in guiding targeted radiation therapy for non-small cell lung cancer: a scoping review

INTRODUCTION

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death. Definitive treatment includes chemotherapy and radiation therapy. Tumour hypoxia impacts the efficacy of these treatment modalities. Novel positron-emission tomography (PET) imaging has been developed to non-invasively quantify hypoxic tumour subregions, and to guide personalised treatment strategies. This review evaluates the reliability of hypoxia imaging in NSCLC in relation to various tracers, its correlations to treatment-related outcomes, and to assess if this imaging modality can be meaningfully applied into radiation therapy workflows.

METHODS

A literature search was conducted on the Medline (Ovid) and Embase databases. Searches included terms related to 'hypoxia', 'positron-emission tomography', 'magnetic resonance imaging' and 'lung cancer'. Results were filtered to exclude studies prior to 2011, and animal studies were excluded. Only studies referring to a confirmed pathology of NSCLC were included, while disease staging was not a limiting factor. Full-text English language and translated literature examined included clinical trials, clinical cohort studies and feasibility studies.

RESULTS

Quantification of hypoxic volumes in a pre-treatment setting is of prognostic value, and indicative of treatment response. Dosimetric comparisons have highlighted potential to significantly dose escalate to hypoxic volumes without risk of additional toxicity. However, clinical data to support these strategies are lacking.

CONCLUSION

Heterogenous study design and non-standardised imaging parameters have led to a lack of clarity regarding the application of hypoxia PET imaging in NSCLC. PET imaging using nitroimidazole tracers is the most investigated method of non-invasively measuring tumour hypoxia and has potential to guide hypoxia-targeted radiation therapy. Further clinical research is required to elucidate the benefits versus risks of dose-escalation strategies.

Feasibility of Ethos adaptive treatments of lung tumors and associated quality assurance

MOTIVATION

Online adaptive radiotherapy with Ethos is based on the anatomy determined from daily cone beam computed tomography (CBCT) images. Dose optimization and computation are performed on the density map of a synthetic CT (sCT), a deformable registration of the initial planning CT (pCT) onto the current CBCT. Large density changes as present in the lung region are challenging the system.

METHODS

Treatment plans for Ethos were created and delivered for 1, 2, and 3 cm diameter lung lesions in an anthropomorphic phantom, combining different insets in the pCT and during adaptive and non-adaptive treatment sessions. Primary and secondary dose calculations as well as back-projected dose from portal images were evaluated.

RESULTS

Density changes due to changed insets were not considered in the sCTs. This resulted in errors in the dose; for example, -15.9% of the mean dose for a plan when changing from a 3 cm inset in the pCT to 1 cm at the time of treatment. Secondary dose calculation is based on the sCT and could therefore not reveal these dose errors. However, dose calculation on the CBCT, either as a recalculation in the treatment planning system or as pre-treatment quality assurance (QA) before the treatment, indicated the differences. EPID in-vivo QA also reported discrepancies between calculated and delivered dose distributions.

CONCLUSIONS

An incorrect density distribution in the sCT has an impact on the dose calculation accuracy in the adaptive treatment workflow with the Ethos system. Additional quality checks of the sCT can detect such errors.

Biocompatible and bioactivable terpolymer-lipid-MnO2 Nanoparticle-based MRI contrast agent for improving tumor detection and delineation

Early and precise detection of solid tumor cancers is critical for improving therapeutic outcomes. In this regard, magnetic resonance imaging (MRI) has become a useful tool for tumor diagnosis and image-guided therapy. However, its effectiveness is limited by the shortcomings of clinically available gadolinium-based contrast agents (GBCAs), i.e. poor tumor penetration and retention, and safety concerns. Thus, we have developed a novel nanoparticulate contrast agent using a biocompatible terpolymer and lipids to encapsulate manganese dioxide nanoparticles (TPL-MDNP). The TPL-MDNP accumulated in tumor tissue and produced paramagnetic Mn2+ ions, enhancing T1-weight MRI contrast via the reaction with H2O2 rich in the acidic tumor microenvironment. Compared to the clinically used GBCA, Gadovist®1.0, TPL-MDNP generated stronger T1-weighted MR signals by over 2.0-fold at 30 % less of the recommended clinical dose with well-defined tumor delineation in preclinical orthotopic tumor models of brain, breast, prostate, and pancreas. Importantly, the MRI signals were retained for 60 min by TPL-MDNP, much longer than Gadovist®1.0. Biocompatibility of TPL-MDNP was evaluated and found to be safe up to 4-fold of the dose used for MRI. A robust large-scale manufacturing process was developed with batch-to-batch consistency. A lyophilization formulation was designed to maintain the nanostructure and storage stability of the new contrast agent.

Clinical Workflow of Cone Beam Computer Tomography-Based Daily Online Adaptive Radiotherapy with Offline Magnetic Resonance Guidance: The Modular Adaptive Radiotherapy System (MARS)

PURPOSE

The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance.

METHODS

From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients.

RESULTS

In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n = 16), lung (n = 7), cervix (n = 5), bladder (n = 1) and endometrium (n = 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5-63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7-39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6-32.2), 0.4 min (IQR 0.3-1,0) and 5.3 min (IQR 4.5-6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases.

CONCLUSION

This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system.

Early radiologic and metabolic tumour response assessment during combined chemo-radiotherapy for locally advanced NSCLC

Background

The role of early treatment response for patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with concurrent chemo-radiotherapy (cCRT) is unclear. The study aims to investigate the predictive value of response to induction chemotherapy (iCX) and the correlation with pattern of failure (PoF).

Materials and methods

Patients with LA-NSCLC treated with cCRT were included for analyses (n = 276). Target delineations were registered from radiotherapy planning PET/CT to diagnostic PET/CT, in between which patients received iCX. Volume, sphericity, and SUVpeak were extracted from each scan. First site of failure was categorised as loco-regional (LR), distant (DM), or simultaneous LR+M (LR+M). Fine and Gray models for PoF were performed: a baseline model (including performance status (PS), stage, and histology), an image model for squamous cell carcinoma (SCC), and an image model for non-SCC. Parameters included PS, volume (VOL) of tumour, VOL of lymph nodes, ΔVOL, sphericity, SUVpeak, ΔSUVpeak, and oligometastatic disease.

Results

Median follow-up was 7.6 years. SCC had higher sub-distribution hazard ratio (sHR) for LRF (sHR = 2.771 [1.577:4.87], p < 0.01) and decreased sHR for DM (sHR = 0.247 [0.125:0.485], p  <  0.01). For both image models, high diagnostic SUVpeak increased risk of LRF (sHR = 1.059 [1.05:1.106], p < 0.01 for SCC, sHR = 1.12 [1.03:1.21], p < 0.01 for non-SCC). Patients with SCC and less decrease in VOL had higher sHR for DM (sHR = 1.025[1.001:1.048] pr. % increase, p = 0.038).

Conclusion

Poor response in disease volume was correlated with higher sHR of DM for SCC, no other clear correlation of response and PoF was observed. Histology significantly correlated with PoF with SCC prone to LRF and non-SCC prone to DM as first site of failure. High SUVpeak at diagnosis increased the risk of LRF for both histologies.

Outcome of conventional radiotherapy in small centrally located tumours or lymph nodes: minimal toxicity, remarkable survival but challenging loco-regional control

BACKGROUND

In peripheral lung tumours, stereotactic body radiotherapy (SBRT) is superior to conventional RT. SBRT has also shown high loco-regional control (LC) in centrally located tumours, but there is a high risk of severe toxicity. The STRICTSTARLung trial (NCT05354596) examines if risk-adapted SBRT for central tumours is feasible. In this study, we examined overall survival (OS), Disease-free survival (DSF), LC, and toxicity in patients with central tumours that could have been candidates for SBRT but received conventional RT.

MATERIAL AND METHODS

Retrospectively, we evaluated 49 lung cancer patients that between 2008 and 2021 received RT (60-70Gy in 2 Gy fractions) for a solitary tumour or lymph node with a diameter <5cm located <2cm from the bronchial tree, oesophagus, aorta or heart. All tumours were pathologically verified; 30 were primary lung tumours (T1b-T4) and 19 were solitary lymph nodes (T0N1-N2). Chemotherapy was administered as concomitant (29) or sequential (4). OS and LC were analysed using Kaplan Meier. Cox proportional hazards model for OS and disease-free survival (DFS) was performed including tumour volume, histology, sex, T- vs N-site and chemotherapy. Toxicity was scored.

RESULTS

In 42 patients, the tumour was located <1 cm to mediastinum. Median follow-up time was 44 months (range: 7-123). The median OS was 51 months. OS at 1-, 3- and 5-year was 88% (SE:5), 59% (SE:7) and 50% (SE:8). Loco-regional recurrences occurred in 16 patients resulting in 1-, and 3-year LC rates of 77% (SE:6) and 64% (SE:8). The majority occurred within 3 years after RT. Only stage showed significant impact on OS and DFS. No patients experienced grade 4-5 toxicity. Seven patients developed grade 3 toxicity (5 oesophageal stenosis, 2 pneumonitis).

CONCLUSION

Conventional RT for patients with small central lung tumours or solitary lymph nodes is feasible. Median OS was 51 months, and toxicity was low with no grade 4-5 events.

Different benefits of adaptive radiotherapy for different histologies of NSCLC

BACKGROUND

Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are the most frequent histological subtypes of non-small cell lung cancer (NSCLC). The aim of this study was to investigate how patients with AC and SCC benefit from image-guided adaptive radiotherapy (ART) with tumour match.

MATERIAL AND METHODS

Consecutive patients diagnosed with AC or SCC of the lung treated with definitive chemo-radiotherapy before and after the implementation of ART and tumour match were retrospectively included for analyses. Data collection included baseline patient and treatment characteristics in addition to clinical data on radiation pneumonitis (RP), failure, and survival. Patients were divided into four categories based on their histology and treatment before (n = 173 [89 AC and 84 SCC]) and after implementation of ART (n = 240 [141 AC and 99 SCC]).

RESULTS

Median follow-up was 5.7 years for AC and 6.3 years for SCC. Mean lung dose decreased for both histologies with ART, whereas mean heart dose only decreased for patients with AC. Incidences of grade 3 and 5 RP decreased for both histologies with ART. Loco-regional failure (LRF) rates decreased significantly for patients with SCC after ART (p = .04), no significant difference was observed for AC. Overall survival (OS) increased significantly for SCC after ART (p < .01): the 2-year OS increased from 31.0% (95% confidence interval [CI] [22.5-42.6]) to 54.5% (95% CI [45.6-65.3]). No significant effect on OS was observed for patients with AC.

CONCLUSION

ART and tumour match in the radiotherapeutic treatment of patients with locally advanced NSCLC primarily led to decreased LRF and improved OS for patients with SCC.

Comparison and evaluation of different deep learning models of synthetic CT generation from CBCT for nasopharynx cancer adaptive proton therapy

BACKGROUND

Cone-beam computed tomography (CBCT) scanning is used for patient setup in image-guided radiotherapy. However, its inaccurate CT numbers limit its applicability in dose calculation and treatment planning.

PURPOSE

This study compares four deep learning methods for generating synthetic CT (sCT) to determine which method is more appropriate and offers potential for further clinical exploration in adaptive proton therapy for nasopharynx cancer.

METHODS

CBCTs and deformed planning CT (dCT) from 75 patients (60/5/10 for training, validation and testing) were used to compare cycle-consistent Generative Adversarial Network (cycleGAN), Unet, Unet+cycleGAN and conditionalGenerative Adversarial Network (cGAN) for sCT generation. The sCT images generated by each method were evaluated against dCT images using mean absolute error (MAE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), spatial non-uniformity (SNU) and radial averaging in the frequency domain. In addition, dosimetric accuracy was assessed through gamma analysis, differences in water equivalent thickness (WET), and dose-volume histogram metrics.

RESULTS

The cGAN model has demonstrated optimal performance in the four models across various indicators. In terms of image quality under global condition, the average MAE has been reduced to 16.39HU, SSIM has increased to 95.24%, and PSNR has increased to 28.98. Regarding dosimetric accuracy, the gamma passing rate (2%/2 mm) has reached 99.02%, and the WET difference is only 1.28 mm. The D95 value of CTVs coverage and Dmax value of spinal cord, brainstem show no significant differences between dCT and sCT generated by cGAN model.

CONCLUSIONS

The cGAN model has been shown to be a more suitable approach for generating sCT using CBCT, considering its characteristics and concepts. The resulting sCT has the potential for application in adaptive proton therapy.

Repeated deep-inspiration breath-hold CT scans at planning underestimate the actual motion between breath-holds at treatment for lung cancer and lymphoma patients

PURPOSE/OBJECTIVE

Deep-inspiration breath-hold (DIBH) during radiotherapy may reduce dose to the lungs and heart compared to treatment in free breathing. However, intra-fractional target shifts between several breath-holds may decrease target coverage. We compared target shifts between four DIBHs at the planning-CT session with those measured on CBCT-scans obtained pre- and post-DIBH treatments.

MATERIAL/METHODS

Twenty-nine lung cancer and nine lymphoma patients were treated in DIBH. An external gating block was used as surrogate for the DIBH-level with a window of 2 mm. Four DIBH CT-scans were acquired: one for planning (CTDIBH3) and three additional (CTDIBH1,2,4) to assess the intra-DIBH target shifts at scanning by registration to CTDIBH3. During treatment, pre-treatment (CBCTpre) and post-treatment (CBCTpost) scans were acquired. For each pair of CBCTpre/post, the target intra-DIBH shift was determined. For lung cancer, tumour (GTV-Tlung) and lymph nodes (GTV-Nlung) were analysed separately. Group mean (GM), systematic and random errors, and GM for the absolute maximum shifts (GMmax) were calculated for the shifts between CTDIBH1,2,3,4 and between CBCTpre/post.

RESULTS

For GTV-Tlung, GMmax was larger at CBCT than CT in all directions. GMmax in cranio-caudal direction was 3.3 mm (CT)and 6.1 mm (CBCT). The standard deviations of the shifts in the left-right and cranio-caudal directions were larger at CBCT than CT. For GTV-Nlung and CTVlymphoma, no difference was found in GMmax or SD.

CONCLUSION

Intra-DIBH shifts at planning-CT session are generally smaller than intra-DIBH shifts observed at CBCTpre/post and therefore underestimate the intra-fractional DIBH uncertainty during treatment. Lung tumours show larger intra-fractional variations than lymph nodes and lymphoma targets.

Triggering daily online adaptive radiotherapy in the pelvis: Dosimetric effects and procedural implications of trigger parameter-value selection

BACKGROUND

Online adaptive radiotherapy (ART) can address dosimetric consequences of variations in anatomy by creating a new plan during treatment. However, ART is time- and labor-intensive and should be implemented in a resource-conscious way. Adaptive triggers composed of parameter-value pairs may direct the judicious use of online ART.

PURPOSE

This work analyzed our clinical experience using CBCT-based daily online ART to demonstrate how a conceptual framework based on adaptive triggers affects the dosimetric and procedural impact of ART.

METHODS

Sixteen patients across several pelvic sites were treated with CBCT-based daily online ART. Differences in standardized dose metrics were compared between the original plan, the original plan recalculated on the daily anatomy, and an adaptive plan. For each metric, trigger values were analyzed in terms of the proportion of treatments adapted and the distribution of metric values.

RESULTS

Target coverage metrics were compromised due to anatomic variation with the average change per treatment ranging from -0.90 to -0.05 Gy, -0.47 to -0.02 Gy, -0.31 to -0.01 Gy, and -12.45% to -2.65% for PTV D99%, PTV D95%, CTV D99%, and CTV V100%, respectively. These were improved using the adaptive plan (-0.03 to 0.01 Gy, -0.02 to 0.00 Gy, -0.03 to 0.00 Gy, and -4.70% to 0.00%, respectively). Increasingly strict triggers resulted in a non-linear increase in the proportion of treatments adapted and improved the distribution of metric values with diminishing returns. Some organ-at-risk (OAR) metrics were compromised by anatomic variation and improved using the adaptive plan, but changes in most OAR metrics were randomly distributed.

CONCLUSIONS

Daily online ART improved target coverage across multiple pelvic treatment sites and techniques. These effects were larger than those for OAR metrics, suggesting that maintaining target coverage was our primary benefit of CBCT-based daily online ART. Analyses like these can determine online ART triggers from a cost-benefit perspective.

Clinical evaluation of synthetic computed tomography methods in adaptive proton therapy of lung cancer patients

Background and purpose

Efficient workflows for adaptive proton therapy are of high importance. This study evaluated the possibility to replace repeat-CTs (reCTs) with synthetic CTs (sCTs), created based on cone-beam CTs (CBCTs), for flagging the need of plan adaptations in intensity-modulated proton therapy (IMPT) treatment of lung cancer patients.

Materials and methods

Forty-two IMPT patients were retrospectively included. For each patient, one CBCT and a same-day reCT were included. Two commercial sCT methods were applied; one based on CBCT number correction (Cor-sCT), and one based on deformable image registration (DIR-sCT). The clinical reCT workflow (deformable contour propagation and robust dose re-computation) was performed on the reCT as well as the two sCTs. The deformed target contours on the reCT/sCTs were checked by radiation oncologists and edited if needed. A dose-volume-histogram triggered plan adaptation method was compared between the reCT and the sCTs; patients needing a plan adaptation on the reCT but not on the sCT were denoted false negatives. As secondary evaluation, dose-volume-histogram comparison and gamma analysis (2%/2mm) were performed between the reCT and sCTs.

Results

There were five false negatives, two for Cor-sCT and three for DIR-sCT. However, three of these were only minor, and one was caused by tumour position differences between the reCT and CBCT and not by sCT quality issues. An average gamma pass rate of 93% was obtained for both sCT methods.

Conclusion

Both sCT methods were judged to be of clinical quality and valuable for reducing the amount of reCT acquisitions.

Pulmonary magnetic resonance-guided online adaptive radiotherapy of locally advanced: the PUMA trial

BACKGROUND

Patients with locally-advanced non-small-cell lung cancer (LA-NSCLC) are often ineligible for surgery, so that definitive chemoradiotherapy (CRT) represents the treatment of choice. Nevertheless, long-term tumor control is often not achieved. Intensification of radiotherapy (RT) to improve locoregional tumor control is limited by the detrimental effect of higher radiation exposure of thoracic organs-at-risk (OAR). This narrow therapeutic ratio may be expanded by exploiting the advantages of magnetic resonance (MR) linear accelerators, mainly the online adaptation of the treatment plan to the current anatomy based on daily acquired MR images. However, MR-guidance is both labor-intensive and increases treatment times, which raises the question of its clinical feasibility to treat LA-NSCLC. Therefore, the PUMA trial was designed as a prospective, multicenter phase I trial to demonstrate the clinical feasibility of MR-guided online adaptive RT in LA-NSCLC.

METHODS

Thirty patients with LA-NSCLC in stage III A-C will be accrued at three German university hospitals to receive MR-guided online adaptive RT at two different MR-linac systems (MRIdian Linac®, View Ray Inc. and Elekta Unity®, Elekta AB) with concurrent chemotherapy. Conventionally fractioned RT with isotoxic dose escalation up to 70 Gy is applied. Online plan adaptation is performed once weekly or in case of major anatomical changes. Patients are followed-up by thoracic CT- and MR-imaging for 24 months after treatment. The primary endpoint is twofold: (1) successfully completed online adapted fractions, (2) on-table time. Main secondary endpoints include adaptation frequency, toxicity, local tumor control, progression-free and overall survival.

DISCUSSION

PUMA aims to demonstrate the clinical feasibility of MR-guided online adaptive RT of LA-NSCLC. If successful, PUMA will be followed by a clinical phase II trial that further investigates the clinical benefits of this approach. Moreover, PUMA is part of a large multidisciplinary project to develop MR-guidance techniques.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05237453 .

CT-based radiomics nomogram may predict who can benefit from adaptive radiotherapy in patients with local advanced-NSCLC patients

BACKGROUND

Although adaptive radiotherapy (ART) has many advantages, ART is not universal in the clinical appliance due to the consumption of a lot of labor, and economic burden. It is necessary to explore a CT stimulation-based radiomics model for screening who can get more benefits from ART in locally advanced non-small cell lung cancer (NSCLC) patients.

METHOD

183 cases of NSCLC patients receiving concurrent chemoradiotherapy with an adaptive approach were enrolled as a primary cohort, while 28 cases from another hospital served as an independent external validation cohort. Tumor regression assessment was conducted based on GTV reduction (Criteria A) or according to RECIST Version 1.1(Criteria B). The radiomics features were extracted by the "PyRadiomics" package and further screened by the LASSO method. Then, logistic regression was used to establish the model. Bootstrap and external validation were applied to verify the stability of the model. The receiver operating characteristic (ROC) curve was delineated to assess the predictive efficacy of the radiomics model. Dose-volume histograms were quantitatively compared between the initial and composite ART plans. Clinical endpoints included overall survival (OS) and progression-free survival (PFS).

RESULT

There were no significant differences in clinical features between tumor regression-resistant (RR) and tumor regression-sensitivity (RS) groups. The AUC values of the Criteria A model and Criteria B model were 0.767 and 0.771, respectively. Bootstrapping validation and external validation confirmed the stability of models. In all patients, there was a significant benefit of ART in the lung, heart, cord, and esophagus compared to non-ART, particularly in RS patients. Furthermore, PFS and OS from ART were significantly longer in RS as defined by Criterion B than in RR patients with the same ART application.

CONCLUSION

CT-based radiomics can screen out the patients who can gain more benefits from ART, which contribute to guiding and popularizing the application of ART strategy in the clinic within economic benefits and feasibility.

Dosimetric benefits of adaptive radiation therapy for patients with stage III non-small cell lung cancer

BACKGROUND

Daily adaptive radiation therapy (ART) of patients with non-small cell lung cancer (NSCLC) lowers organs at risk exposure while maintaining the planning target volume (PTV) coverage. Thus, ART allows an isotoxic approach with increased doses to the PTV that could improve local tumor control. Herein we evaluate daily online ART strategies regarding their impact on relevant dose-volume metrics.

METHODS

Daily cone-beam CTs (1 × n = 28, 1 × n = 29, 11 × n = 30) of 13 stage III NSCLC patients were converted into synthetic CTs (sCTs). Treatment plans (TPs) were created retrospectively on the first-fraction sCTs (sCT₁) and subsequently transferred unaltered to the sCTs of the remaining fractions of each patient (sCT_2-n) (IGRT scenario). Two additional TPs were generated on sCT_2-n: one minimizing the lung-dose while preserving the D_95%(PTV) (isoeffective scenario), the other escalating the D_95%(PTV) with a constant V_20Gy(lung_ipsilateral) (isotoxic scenario).

RESULTS

Compared to the original TPs predicted dose, the median D_95%(PTV) in the IGRT scenario decreased by 1.6 Gy ± 4.2 Gy while the V_20Gy(lung_ipsilateral) increased in median by 1.1% ± 4.4%. The isoeffective scenario preserved the PTV coverage and reduced the median V_20Gy(lung_ipsilateral) by 3.1% ± 3.6%. Furthermore, the median V_5%(heart) decreased by 2.9% ± 6.4%. With an isotoxic prescription, a median dose-escalation to the gross target volume of 10.0 Gy ± 8.1 Gy without increasing the V_20Gy(lung_ipsilateral) and V_5%(heart) was feasible.

CONCLUSIONS

We demonstrated that even without reducing safety margins, ART can reduce lung-doses, while still reaching adequate target coverage or escalate target doses without increasing ipsilateral lung exposure. Clinical benefits by means of toxicity and local control of both strategies should be evaluated in prospective clinical trials.

Adaptive radiation therapy (art) for patients with limited-stage small cell lung cancer (LS-SCLC): A dosimetric evaluation

Background

Adaptive radiation therapy (ART) refers to redesigning of radiation therapy (RT) treatment plans with respect to dynamic changes in tumor size and location throughout the treatment course. In this study, we performed a comparative volumetric and dosimetric analysis to investigate the impact of ART for patients with limited-stage small cell lung cancer (LS-SCLC).

Methods

Twenty-four patients with LS-SCLC receiving ART and concomitant chemotherapy were included in the study. ART was performed by replanning of patients based on a mid-treatment computed tomography (CT)-simulation which was routinely scheduled for all patients 20-25 days after the initial CT-simulation. While the first 15 RT fractions were planned using the initial CT-simulation images, the latter 15 RT fractions were planned using the mid-treatment CT-simulation images acquired 20-25 days after the initial CT-simulation. In order to document the impact of ART, target and critical organ dose-volume parameters acquired from this adaptive radiation treatment planning (RTP) were compared with the RTP based solely on the initial CT-simulation to deliver the whole RT dose of 60 Gy.

Results

Statistically significant reduction was detected in gross tumor volume (GTV) and planning target volume (PTV) during the conventionally fractionated RT course along with statistically significant reduction in critical organ doses with incorporation of ART.

Conclusion

One-third of the patients in our study who were otherwise ineligible for curative intent RT due to violation of critical organ dose constraints could be treated with full dose irradiation by use of ART. Our results suggest significant benefit of ART for patients with LS-SCLC.

The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how

Adaptive radiotherapy (ART) is a new radiotherapy technology based on image-guided radiation therapy technology, used to avoid radiation overexposure to residual tumors and the surrounding normal tissues. Tumors undergoing the same radiation doses and modes can occur unequal shrinkage due to the variation of response times to radiation doses in different patients. To perform ART effectively, eligible patients with a high probability of benefits from ART need to be identified. Confirming the precise timetable for ART in every patient is another urgent problem to be resolved. Moreover, the outcomes of ART are different depending on the various image guidance used. This review discusses 'who, when and how' as the three key factors involved in the most effective implementation for the management of ART.

A traffic light protocol workflow for image-guided adaptive radiotherapy in lung cancer patients

BACKGROUND AND PURPOSE

Image-guided radiotherapy using cone beam-CT (CBCT) images is used to evaluate patient anatomy and positioning before radiotherapy. In this study we analyzed and optimized a traffic light protocol (TLP) used in lung cancer patients to identify patients requiring treatment adaptation.

MATERIALS AND METHODS

First, CBCT review requests of 243 lung cancer patients were retrospectively analyzed and divided into 6 pre-defined categories. Frequencies and follow-up actions were scored. Based on these results, the TLP was optimized and evaluated in the same way on 230 patients treated in 2018.

RESULTS

In the retrospective study, a total of 543 CBCT review requests were created during treatment in 193/243 patients due to changed anatomy of lung (24%), change of tumor volume (24%), review of match (18%), shift of the mediastinum (15%), shift of tumor (15%) and other (4%). The majority of requests (474, 87%) did not require further action. In 6% an adjustment of the match criteria sufficed; in 7% treatment plan adaptation was required. Plan adaptation was frequently seen in the categories changed anatomy of lung, change of tumor volume and shift of tumor outside the PTV. Shift of mediastinum outside PRV and shift of GTV outside CTV (but inside PTV) never required plan adaptation and were omitted to optimize the TLP, which reduced the CBCT review requests by 23%.

CONCLUSIONS

The original TLP selected patients that required a treatment adaptation, but with a high false positive rate. The optimized TLP reduced the amount of CBCT review requests, while still correctly identifying patients requiring adaptation.

A prediction model for dosimetric-based lung adaptive radiotherapy

PURPOSE

Anatomical changes occurred during the treatment course of radiation therapy for lung cancer patients may introduce clinically unacceptable dosimetric deviations from the planned dose. Adaptive radiotherapy (ART) can compensate these dosimetric deviations in subsequent treatments via plan adaption. Determining whether and when to trigger plan adaption during the treatment course is essential to the effectiveness and efficiency of ART. In this study, we aimed to develop a prediction model as an auxiliary decision-making tool for lung ART to identify the patients with intrathoracic anatomical changes that would potentially benefit from the plan adaptions during the treatment course.

METHODS

Seventy-one pairs of weekly cone-beam computer tomography (CBCT) and planning CT (pCT) from 17 advanced non-small cell lung cancer patients were enrolled in this study. To assess the dosimetric impacts brought by anatomical changes observed on each CBCT, dose distribution of the original treatment plan on the CBCT anatomy was calculated on a virtual CT generated by deforming the corresponding pCT to the CBCT, and compared to that of the original plan. A replan was deemed needed for the CBCT anatomy once the recalculated dose distribution violated our dosimetric-based trigger criteria. A three-dimensional region of significant anatomical changes (region of interest, ROI) between each CBCT and the corresponding pCT was identified and 16 morphological features of the ROI were extracted. Additionally, eight features from the overlapped volume histograms (OVHs) of patient anatomy were extracted for each patient to characterize the patient specific anatomy. Based on the 24 extracted features and the evaluated replanning needs of the pCT-CBCT pairs, a nonlinear supporting vector machine was used to build a prediction model to identify the anatomical changes on CBCTs that would trigger plan adaptions. The most relevant features were selected using the sequential backward selection (SBS) algorithm and a shuffling-and-splitting validation scheme was used for model evaluation.

RESULTS

Fifty-Five CBCT-pCT pairs were identified of having a ROI, among which 21 CBCT anatomies required plan adaptions. For these 21 positive cases, statistically significant improvements in the sparing of lung, esophagus and spinal cord were achieved by plan adaptions. A high model performance of 0.929 AUC and 0.851 accuracy was achieved with six selected features including five ROI shape features and one OVH feature. Without involving the OVH features in the feature selection process, the mean AUC and accuracy of the model significantly decreased to 0.826 and 0.779, respectively. Further investigation showed that poor prediction performance with AUC of 0.76 was achieved by the univariate model in solving this binary classification task.

CONCLUSION

We built a prediction model based on the features of patient anatomy and the anatomical changes captured by on-treatment CBCT imaging to trigger plan adaption for lung cancer patients. This model effectively associated the anatomical changes with the dosimetric impacts for lung ART. This model can be a promising tool to assist the clinicians in making decisions for plan adaptions during the treatment courses. This article is protected by copyright. All rights reserved.

Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate

Background

Hybrid magnetic resonance (MR)-Linac systems have recently been introduced into clinical practice. The systems allow online adaption of the treatment plan with the aim of compensating for interfractional anatomical changes. The aim of this study was to evaluate the dose volume histogram (DVH)-based dosimetric benefits of online adaptive MR-guided radiotherapy (oMRgRT) across different tumor entities and to investigate which subgroup of plans improved the most from adaption.

Methods

Fifty patients treated with oMRgRT for five different tumor entities (liver, lung, multiple abdominal lymph nodes, pancreas, and prostate) were included in this retrospective analysis. Various target volume (gross tumor volume GTV, clinical target volume CTV, and planning target volume PTV) and organs at risk (OAR) related DVH parameters were compared between the dose distributions before and after plan adaption.

Results

All subgroups clearly benefited from online plan adaption in terms of improved PTV coverage. For the liver, lung and abdominal lymph nodes cases, a consistent improvement in GTV coverage was found, while many fractions of the prostate subgroup showed acceptable CTV coverage even before plan adaption. The largest median improvements in GTV near-minimum dose (D_98%) were found for the liver (6.3%, p < 0.001), lung (3.9%, p < 0.001), and abdominal lymph nodes (6.8%, p < 0.001) subgroups. Regarding OAR sparing, the largest median OAR dose reduction during plan adaption was found for the pancreas subgroup (-87.0%). However, in the pancreas subgroup an optimal GTV coverage was not always achieved because sparing of OARs was prioritized.

Conclusion

With online plan adaptation, it was possible to achieve significant improvements in target volume coverage and OAR sparing for various tumor entities and account for interfractional anatomical changes.

Substantial Sparing of Organs at Risk with Modern Proton Therapy in Lung Cancer, but Altered Breathing Patterns Can Jeopardize Target Coverage

Simple Summary

Treatment of locally advanced non-small cell lung cancer (LA-NSCLC) is a fine balance between toxicity and cure. Modern proton therapy might offer a more gentle radiation treatment compared to state-of-the-art photon radiotherapy, but is also more susceptible to the influence of breathing motion and anatomical changes. In this study, the influence of such uncertainties on treatment delivery was thoroughly investigated. Modern proton therapy did indeed show potential to reduce the risk of toxicity for the heart and lungs. This potential was maintained under the influence of anatomical and delivery uncertainties. However, changes in breathing motion jeopardized the target dose distribution in a subset of patients. We therefore recommend imaging at onset or early in treatment to recognize these patients and adapt the treatment.

Abstract

Enhancing treatment of locally advanced non-small cell lung cancer (LA-NSCLC) by using pencil beam scanning proton therapy (PBS-PT) is attractive, but little knowledge exists on the effects of uncertainties occurring between the planning (Plan) and the start of treatment (Start). In this prospective simulation study, we investigated the clinical potential for PBS-PT under the influence of such uncertainties. Imaging with 4DCT at Plan and Start was carried out for 15 patients that received state-of-the-art intensity-modulated radiotherapy (IMRT). Three PBS-PT plans were created per patient: 3D robust single-field uniform dose (SFUD), 3D robust intensity-modulated proton therapy (IMPT), and 4D robust IMPT (4DIMPT). These were exposed to setup and range uncertainties and breathing motion at Plan, and changes in breathing motion and anatomy at Start. Target coverage and dose-volume parameters relevant for toxicity were compared. The organ at risk sparing at Plan was greatest with IMPT, followed by 4DIMPT, SFUD and IMRT, and persisted at Start. All plans met the preset criteria for target robustness at Plan. At Start, three patients had a lack of CTV coverage with PBS-PT. In conclusion, the clinical potential for heart and lung toxicity reduction with PBS-PT was substantial and persistent. Altered breathing patterns between Plan and Start jeopardized target coverage for all PBS-PT techniques.

Survival benefits for non-small cell lung cancer patients treated with adaptive radiotherapy

INTRODUCTION

Tumor match and adaptive radiotherapy based on on-treatment imaging increases the precision of RT. This allows a reduction of treatment volume and, consequently, of the dose to organs at risk. We investigate the clinical benefits of tumor match and adaptive radiotherapy for a cohort of non-small cell lung cancer patients (NSCLC).

METHODS

In 2013, tumor match and adaptive radiotherapy based on daily cone-beam CT scans was introduced to ensure adaption of the radiotherapy treatment plan for all patients with significant anatomical changes during radiotherapy. Before 2013, the daily cone-beam CT scans were matched on the vertebra and anatomical changes were not evaluated systematically. To estimate the effect of tumor match and adaptive radiotherapy, 439 consecutive NSCLC patients treated with definitive chemo-radiotherapy (50-66 Gy/25-33 fractions, 2010-2018) were investigated retrospectively. They were split in two groups, pre-ART (before tumor match and adaptive radiotherapy, 184 patients), and ART (after tumor match and adaptive radiotherapy, 255 patients) and compared with respect to clinical, treatment-specific and dosimetric variables (χ2 tests, Mann Whitney U tests), progression, survival and radiation pneumonits (CTCAEv3). Progression-free and overall survival as well as radiation pneumonitis were compared with log-rank tests. Hazard ratios were estimated from Cox proportional hazard regression.

RESULTS

No significant differences in stage (p = 0.36), histology (p = 0.35), PS (p = 0.12) and GTV volumes (p = 0.24) were observed. Concomitant chemotherapy was administered more frequently in the ART group (78%) compared to preART (64%), p < 0.001. Median[range] PTV volumes decreased from 456 [71;1262] cm3 (preART) to 270 [31;1166] cm3 (ART), p < 0.001, thereby significantly reducing mean doses to lungs (median, preART 16.4 [1.9;24.7] Gy, ART 12.1 [1.7;19.4] Gy, p < 0.001) and heart (median, preART 8.0 [0.1;32.1] Gy, ART 4.4 [0.1;33.9] Gy, p < 0.001). The incidence of RP at nine months decreased significantly with ART (50% to 20% for symptomatic RP (≥G2), 21% to 7% for severe RP (≥G3), 6% to 0.4% for lethal RP (G5), all p < 0.001). The two-year progression free survival increased from 22% (preART) to 30% (ART), while the overall survival increased from 43% (preART) to 56% (ART). The median overall survival time increased from 20 (preART) to 28 months (ART).

CONCLUSION

Tumor match and adaptive radiotherapy significantly decreased radiation pneumonitis, while maintaining loco-regional control. Further, we observed a significantly improved progression-free and overall survival.

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Operating procedures, risk management and challenges during implementation of adaptive and non-adaptive MR-guided radiotherapy: 1-year single-center experience

BACKGROUND

Main purpose was to describe procedures and identify challenges in the implementation process of adaptive and non-adaptive MR-guided radiotherapy (MRgRT), especially new risks in workflow due to the new technique. We herein report the single center experience for the implementation of (MRgRT) and present an overview on our treatment practice.

METHODS

Descriptive statistics were used to summarize clinical and technical characteristics of treatment and patient characteristics including sites treated between April 2019 and end of March 2020 after ethical approval. A risk analysis was performed to identify risks of the online adaptive workflow.

RESULTS

A summary of the processes on the MR-Linac including workflows, quality assurance and possible pitfalls is presented. 111 patients with 124 courses were treated during the first year of MR-guided radiotherapy. The most commonly treated site was the abdomen (42% of all treatment courses). 73% of the courses were daily online adapted and a high number of treatment courses (75%) were treated with stereotactic body irradiation. Only 4/382 fractions could not be treated due to a failing online adaptive quality assurance. In the risk analysis for errors, the two risks with the highest risk priority number were both in the contouring category, making it the most critical step in the workflow.

CONCLUSION

Although challenging, establishment of MRgRT as a routinely used technique at our department was successful for all sites and daily o-ART was feasible from the first day on. However, ongoing research and reports will have to inform us on the optimal indications for MRgRT because careful patient selection is necessary as it continues to be a time-consuming treatment technique with restricted availability. After risk analysis, the most critical workflow category was the contouring process, which resembles the need of experienced staff and safety check paths.

Dynamic stochastic deep learning approaches for predicting geometric changes in head and neck cancer

Objective.Modern radiotherapy stands to benefit from the ability to efficiently adapt plans during treatment in response to setup and geometric variations such as those caused by internal organ deformation or tumor shrinkage. A promising strategy is to develop a framework, which given an initial state defined by patient-attributes, can predict future states based on pre-learned patterns from a well-defined patient population.Approach.Here, we investigate the feasibility of predicting patient anatomical changes, defined as a joint state of volume and daily setup changes, across a fractionated treatment schedule using two approaches. The first is based on a new joint framework employing quantum mechanics in combination with deep recurrent neural networks, denoted QRNN. The second approach is developed based on a classical framework, which models patient changes as a Markov process, denoted MRNN. We evaluated the performance characteristics of these two approaches on a dataset of 125 head and neck cancer patients, which was supplemented by synthetic data generated using a generative adversarial network. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) scores.Main results.The MRNN framework had slightly better performance than the QRNN framework, with MRNN (QRNN) validation AUC scores of 0.742±0.021 (0.675±0.036), 0.709±0.026 (0.656±0.021), 0.724±0.036 (0.652±0.044), and 0.698±0.016 (0.605±0.035) for system state vector sizes of 4, 6, 8, and 10, respectively. Of these, only the results from the two higher order states had statistically significant differences(p<0.05).A similar trend was also observed when the models were applied to an external testing dataset of 20 patients, yielding MRNN (QRNN) AUC scores of 0.707 (0.623), 0.687 (0.608), 0.723 (0.669), and 0.697 (0.609) for states vectors sizes of 4, 6, 8, and 10, respectively.Significance.These results suggest that both stochastic models have potential value in predicting patient changes during the course of adaptive radiotherapy.

Early prediction of tumour-response to radiotherapy in NSCLC patients

Objective. In this study we developed an automatic method to predict tumour volume and shape in weeks 3 and 4 of radiotherapy (RT), using cone-beam computed tomography (CBCT) scans acquired up to week 2, allowing identification of large tumour changes.Approach. 240 non-small cell lung cancer (NSCLC) patients, treated with 55 Gy in 20 fractions, were collected. CBCTs were rigidly registered to the planning CT. Intensity values were extracted in each voxel of the planning target volume across all CBCT images from days 1, 2, 3, 7 and 14. For each patient and in each voxel, four regression models were fitted to voxel intensity; applying linear, Gaussian, quadratic and cubic methods. These models predicted the intensity value for each voxel in weeks 3 and 4, and the tumour volume found by thresholding. Each model was evaluated by computing the root mean square error in pixel value and structural similarity index metric (SSIM) for all patients. Finally, the sensitivity and specificity to predict a 30% change in volume were calculated for each model.Main results. The linear, Gaussian, quadratic and cubic models achieved a comparable similarity score, the average SSIM for all patients was 0.94, 0.94, 0.90, 0.83 in week 3, respectively. At week 3, a sensitivity of 84%, 53%, 90% and 88%, and specificity of 99%, 100%, 91% and 42% were observed for the linear, Gaussian, quadratic and cubic models respectively. Overall, the linear model performed best at predicting those patients that will benefit from RT adaptation. The linear model identified 21% and 23% of patients in our cohort with more than 30% tumour volume reduction to benefit from treatment adaptation in weeks 3 and 4 respectively.Significance. We have shown that it is feasible to predict the shape and volume of NSCLC tumours from routine CBCTs and effectively identify patients who will respond to treatment early.

Møller D, Assenholt MS, Hansen R, Nyvang L, Ravkilde T, Thomsen MS, Hoffmann L. Density calibrated cone beam CT as a tool for adaptive radiotherapy

BACKGROUND

Visual inspections of anatomical changes observed on daily cone-beam CT (CBCT) images are often used as triggers for radiotherapy plan adaptation to avoid unacceptable dose levels to the target or OARs. Direct CBCT dose calculations would improve the ability to adapt only those plans where dosimetric changes are observed. This study investigates the accuracy of dose calculations on CBCTs.

MATERIALS AND METHODS

Calibration curves were obtained for CBCT imagers at nine identical accelerators. CBCT scans of a phantom with different density inserts were recorded for two scan modes (Head-Neck and Pelvis) and mean calibration curves were calculated. Subsequently, CBCT scans of the phantom with six different density inserts were recorded, the dose distributions on the CBCTs were calculated and compared to dose on the planning CT (pCT). The uncertainty was quantified by the dosimetric difference between the pCT and the CBCT. The two mean calibration curves were used to calculate the daily delivered CBCT dose for ten Head-Neck-, eleven Lung-, and ten pelvic patients. Additional patient calculations were performed using low-HU empirically corrected calibration curves. Patient doses were compared on target coverage and mean dose, and D1cc for OARs.

RESULTS

The dose differences between pCT and CBCT for phantom data were small for all DVH parameters, with mean deviations below ±0.6% for both CBCT modes. For patient data, it was found that low-HU corrected calibration curves performed the best. The mean deviations for the mean dose and coverage of the target were 0.2%±0.7% and 0.1%±0.6%, across all patient groups.

CONCLUSION

Dose calculation on CBCT images results in target coverage and mean dose with an accuracy of the order of 1%, which makes this acceptable for clinical use. The CBCT mode specific calibration curves can be used at all identical imaging devices and for all patient groups.

The Impact of Intra-thoracic Anatomical Changes upon the Delivery of Lung Stereotactic Ablative Radiotherapy

AIMS

So far, the impact of intra-thoracic anatomical changes (ITACs) on patients treated with stereotactic ablative radiotherapy (SABR) for early-stage non-small cell lung cancer is unknown. Studying these is important, as ITACs have the potential to impact the workflow and reduce treatment quality. The aim of this study was to assess and categorise ITACs, as detected on cone beam computed tomography scans (CBCT), and their subsequent impact upon treatment in lung cancer patients treated with SABR.

MATERIALS AND METHODS

CBCTs from 100 patients treated with SABR for early non-small cell lung cancer were retrospectively reviewed. The presence of the following ITACs was assessed: atelectasis, infiltrative change, pleural effusion, baseline shift and gross tumour volume (GTV) increase and decrease. ITACs were graded using a traffic light protocol. This was adapted from a tool previously developed to assesses potential target undercoverage or organ at risk overdose. The frequency of physics or clinician review was noted. A linear mixed effects model was used to assess the relationship between ITAC grade and set-up time (time from first CBCT to beam delivery).

RESULTS

ITACs were observed in 22% of patients. Twenty-one per cent of these were categorised as 'red', implying a risk of underdosage to the GTV. Most were 'yellow' (51%), indicating little impact upon planning target volume coverage of the GTV. Physics or clinician review was required in 10% of all treatment fractions overall. Three patients needed their treatment replanned. The mixed effect model analysis showed that ITACs cause a significant prolongation of set-up time (Χ2(3) = 9.22, P = 0.02).

CONCLUSION

Most ITACs were minor, but associated with unplanned physics or clinician review, representing a potentially significant resource burden. ITACs also had a significant impact upon set-up time, with consequences for the wider workflow and intra-fraction motion. Detailed guidance on the management of ITACs is needed to provide support for therapeutic radiographers delivering lung SABR.

Validation of in-house knowledge-based planning model for predicting change in target coverage during VMAT radiotherapy to in-operable advanced-stage NSCLC patients

Objectives. anatomical changes are inevitable during the course of radiotherapy treatments and, if significant, can severely alter expected dose distributions and affect treatment outcome. Adaptive radiotherapy (ART) is employed to maintain the planned distribution and minimise detriment to predicted treatment outcome. Typically, patients who may benefit from adaptive planning are identified via a re-planning process, i.e., re-simulation, re-contouring, re-planning and treatment plan quality assurance (QA). This time-intensive process significantly increases workload, can introduce delays and increases unnecessary stress to those patients who will not actually gain benefit. We consider it crucial to develop efficient models to predict changes to target coverage and trigger ART, without the need for re-planning.Methods.knowledge-based planning (KBP) models were developed using data for 20 patients' (400 fractions) to predict changes in PTV V₉₅coverageΔV95PTV.Initially, this change in coverage was calculated on the synthetic computerised tomography (sCT) images produced using the Velocity adaptive radiotherapy software. Models were developed using patient (cell death bio-marker) and treatment fraction (PTV characteristic) specific parameters to predictΔV95PTVand verified using five patients (100 fractions) data.Results. three models were developed using combinations of patient and fraction specific terms. The prediction accuracy of the model developed using biomarker (PD-L1 expression) and the difference in 'planning' and 'fraction' PTV centre of the mass (characterised by mean square difference, MSD) had the higher prediction accuracy, predicting theΔV95PTVwithin ± 1.0% for 77% of the total fractions; with 59% for the model developed using, PTV size, PD-L1 and MSD and 48% PTV size and MSD respectively.Conclusion. the KBP models can predictΔV95PTVvery effectively and efficiently for advanced-stage NSCLC patients treated using volumetric modulated arc therapy and to identify patients who may benefit from adaption for a specific fraction.

Improved adaptive radiotherapy to adjust for anatomical alterations during curative treatment for locally advanced lung cancer

Anatomical changes during chemoradiation for lung cancer may decrease dose to the target or increase dose to organs at risk. To assess our ability to identify clinically significant anatomical alterations, we followed 67 lung cancer patients by daily cone-beam CT scans to ensure correct patient positioning and observe anatomical alterations. We also re-calculated the original dose distribution on a planned control CT scan obtained halfway during the treatment course to identify anatomical changes that potentially affected doses to the target or organs at risk. Of 66 patients who completed the treatment, 12 patients needed adaptation, two patients were adapted twice. We conclude that daily cone-beam CT and routines at the treatment machine discover relevant anatomical changes during curative radiotherapy for patients with lung cancer without additional imaging.

A method for predictive modeling of tumor regression for lung adaptive radiotherapy

PURPOSE

The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer.

METHODS

A predictive algorithm was developed as a decision support tool to determine the potential utility of mid-treatment adaptive radiotherapy based on anatomic changes observed on 1158 daily CBCT images across 43 patients. The anatomic changes on each axial slice within specified regions-of-interest were quantified into a single value utilizing imaging similarity criteria comparing the daily CBCT to the initial simulation CT. The range of the quantified metrics for each fraction across all axial slices are reduced to specified quantiles, which are used as the predictive input to train a logistic regression algorithm. A "ground-truth" of the need for adaptive radiotherapy based on tumor regression was evaluated systematically on each of the daily CBCTs and used as the classifier in the logistic regression algorithm. Accuracy of the predictive model was assessed utilizing both a tenfold cross validation and an independent validation dataset, with the sensitivity, specificity, and fractional accuracy compared to the ground-truth.

RESULTS

The sensitivity and specificity for the individual daily fractions ranged from 87.9%-94.3% and 91.9%-98.6% for a probability threshold of 0.2-0.5, respectively. The corresponding average treatment fraction difference between the model predictions and assessed ART "ground-truth" ranged from -2.25 to -0.07 fractions, with the model predictions consistently predicting the potential need for ART earlier in the treatment course. By initially utilizing a lower probability threshold, the higher sensitivity minimizes the chance of false negative by alerting the clinician to review a higher number of questionable cases.

CONCLUSIONS

The proposed methodology accurately predicted the first fraction at which individual patients may benefit from ART based on quantified anatomic changes observed in the on-treatment volumetric imaging. The generalizability of the proposed method has potential to expand to additional modes of adaptive radiotherapy for lung cancer patients with observed underlying anatomic changes.

A comparison of two methods for segmentation of functional volumes in radiotherapy planning of lung cancer patients

BACKGROUND

In radiotherapy (RT) of lung cancer, dose to functional lung (FL) volumes segmented with two different methods (perfusion SPECT (Q-SPECT) and 4D-CT (4D) ventilation (V)) have been shown to correlate with the incidence of radiation pneumonitis (RP). This study aims to compare the FL volumes identified by both methods.

MATERIAL AND METHODS

Thirty lung cancer patients had a 4D and Q-SPECT prior to treatment. Seventeen of these patients also had a ventilation SPECT (V-SPECT). FL sub-volumes were segmented automatically, using cut-off values. The volumes were compared in terms of overlap fraction (OF) relative to the minimal volume, and intersection fraction (IF) of the FL volume relative to the total lung volume (V_Lung).

RESULTS

Cut-off values suggested in literature for Q-SPECT and 4D-V resulted in volumes differing in size by a median 18% [6%;31%], and a median OF and IF of 0.48 [0.23;0.70] and 0.09 [0.02;0.25], respectively. Segmenting volumes of comparable size of about 1/3 of V_Lung (FL-m(1/3), m = method) resulted in a median OF and IF of 0.43 [0.23;0.58] and 0.12 [0.06;0.19], respectively. Twenty-five patients (83%) had a reasonable overlap between FL-Q(1/3) and FL-4D-V(1/3) volumes, with OF values above 0.33. IF increased significantly (p = .036) compared to using fixed cut-off values. Similarly, volumes of comparable size of about 1/3 V_Lung were produced for V-SPECT, and FL-Q(1/3), FL-V(1/3), and FL-4D-V(1/3) were compared. The overlaps and intersections of FL-V(1/3) with FL-Q(1/3) volumes were significantly (p<.001) larger than the corresponding overlaps and intersections of FL-Q(1/3) with FL-4D(1/3) and FL-V(1/3) with FL-4D(1/3).

CONCLUSION

The Q-SPECT and 4D-V methods do not segment entirely the same FL volumes. A reasonable overlap of the volumes along with the findings of other studies that both correlate to RP incidence, suggests that a combination of both volumes, e.g. using the IF, may be useful in RT treatment planning.

Adaptive intensity-modulated radiotherapy with simultaneous integrated boost for stage III non-small cell lung cancer: Is a routine adaptation beneficial?

PURPOSE

Tumor and anatomical changes during radiotherapy have been observed in stage III non-small cell lung cancer (NSCLC) from many previous studies. We hypothesized that a routinely scheduled adaptive radiotherapy would have clinical important dose benefits to lower the risk of toxicities, without increasing the tumor recurrences.

METHODS

We retrospectively reviewed 92 consecutive patients with inoperable stage III NSCLC between November 2017 and March 2019. All eligible patients should received simultaneously integrated boost (SIB) using intensity-modulated radiation therapy (IMRT). A mid-treatment CT simulation and a new adapted plan were routinely given after the first 20 fractions. The organs at risk (OARs) were delineated per RTOG 1106 atlas. Dose-volume histograms were quantitatively compared between the initial and composite adaptive plans. Logistic regression was applied to analyze the dose-response relationship. Clinical endpoints included acute symptomatic radiation pneumonitis (RP2) and esophagitis (RE2), local and regional tumor control, and progression-free survival (PFS).

RESULTS

Sixty-four eligible patients received adaptive SIB-IMRT were consecutively included. The GTVs reduced by a median of -38.2% after 42 to 44 Gy in 20 fractions of radiotherapy. By adapting to tumor and anatomical changes, dosimetric parameters of OARs decreased significantly. The mean lung dose decreased by an average of -74.8 cGy, and mean esophagus dose was lower by 183.1 cGy. We found grade 2 or higher acute RP in 11 patients (17.2%), and RE2 in 28 patients (43.8%). Commonly used lung and esophagus dose metrics were significantly associated with RP2 and RE2. The adaptation could reduce RP2 probability by 3%, and RE2 risk by 5%. Subgroups with higher OARs dose or larger tumor shrinkage may get more dose and toxicities benefits. The estimated median PFS was 12.5 months from the start of radiotherapy.

CONCLUSIONS

We demonstrated that the routinely adaptive SIB-IMRT strategy could significantly reduce the dose to surrounding normal tissues, potentially lower the associated acute RP and RE, without increasing the risk of tumor recurrences.

MR-Guided Radiotherapy: The Perfect Partner for Immunotherapy?

During the last years, preclinical and clinical studies have emerged supporting the rationale to integrate radiotherapy and immunotherapy. Radiotherapy may enhance the effects of immunotherapy by improving tumor antigen release, antigen presentation, and T-cell infiltration. Recently, magnetic resonance guided radiotherapy (MRgRT) has become clinically available. Compared to conventional radiotherapy techniques, MRgRT firstly allows for daily on-table treatment adaptation, which enables both dose escalation for increasing tumor response and superior sparing of radiosensitive organs-at-risk for reducing toxicity. The current review focuses on the potential of combining MR-guided adaptive radiotherapy with immunotherapy by providing an overview on the current status of MRgRT, latest developments in preclinical and clinical radio-immunotherapy, and the unique opportunities and challenges for MR-guided radio-immunotherapy. MRgRT might especially assist in answering open questions in radio-immunotherapy regarding optimal radiation dose, fractionation, timing of immunotherapy, appropriate irradiation volumes, and response prediction.

Cone-Beam-CT Guided Adaptive Radiotherapy for Locally Advanced Non-small Cell Lung Cancer Enables Quality Assurance and Superior Sparing of Healthy Lung

Purpose

To evaluate the potential of cone-beam-CT (CB-CT) guided adaptive radiotherapy (ART) for locally advanced non-small cell lung cancer (NSCLC) for sparing of surrounding organs-at-risk (OAR).

Materials and Methods

In 10 patients with locally advanced NSCLC, daily CB-CT imaging was acquired during radio- (n = 4) or radiochemotherapy (n = 6) for simulation of ART. Patients were treated with conventionally fractionated intensity-modulated radiotherapy (IMRT) with total doses of 60–66 Gy (pPlan) (311 fraction CB-CTs). OAR were segmented on every daily CB-CT and the tumor volumes were modified weekly depending on tumor changes. Doses actually delivered were recalculated on daily images (dPlan), and voxel-wise dose accumulation was performed using a deformable registration algorithm. For simulation of ART, treatment plans were adapted using the new contours and re-optimized weekly (aPlan).

Results

CB-CT showed continuous tumor regression of 1.1 ± 0.4% per day, leading to a residual gross tumor volume (GTV) of 65.3 ± 13.4% after 6 weeks of radiotherapy (p = 0.005). Corresponding PTVs decreased to 83.7 ± 7.8% (p = 0.005). In the actually delivered plans (dPlan), both conformity (p = 0.005) and homogeneity (p = 0.059) indices were impaired compared to the initial plans (pPlan). This resulted in higher actual lung doses than planned: V_20Gy was 34.6 ± 6.8% instead of 32.8 ± 4.9% (p = 0.066), mean lung dose was 19.0 ± 3.1 Gy instead of 17.9 ± 2.5 Gy (p = 0.013). The generalized equivalent uniform dose (gEUD) of the lung was 18.9 ± 3.1 Gy instead of 17.8 ± 2.5 Gy (p = 0.013), leading to an increased lung normal tissue complication probability (NTCP) of 15.2 ± 13.9% instead of 9.6 ± 7.3% (p = 0.017). Weekly plan adaptation enabled decreased lung V_20Gy of 31.6 ± 6.2% (−3.0%, p = 0.007), decreased mean lung dose of 17.7 ± 2.9 Gy (−1.3 Gy, p = 0.005), and decreased lung gEUD of 17.6 ± 2.9 Gy (−1.3 Gy, p = 0.005). Thus, resulting lung NTCP was reduced to 10.0 ± 9.5% (−5.2%, p = 0.005). Target volume coverage represented by conformity and homogeneity indices could be improved by weekly plan adaptation (CI: p = 0.007, HI: p = 0.114) and reached levels of the initial plan (CI: p = 0.721, HI: p = 0.333).

Conclusion

IGRT with CB-CT detects continuous GTV and PTV changes. CB-CT-guided ART for locally advanced NSCLC is feasible and enables superior sparing of healthy lung at high levels of plan conformity.

Patterns of practice for adaptive and real-time radiation therapy (POP-ART RT) part II: Offline and online plan adaption for interfractional changes

PURPOSE

The POP-ART RT study aims to determine to what extent and how intrafractional real-time respiratory motion management (RRMM), and plan adaptation for interfractional anatomical changes (ART) are used in clinical practice and to understand barriers to implementation. Here we report on part II: ART using more than one plan per target per treatment course.

MATERIALS AND METHODS

A questionnaire on the current practice of ART, wishes for expansion or implementation, and barriers to implementation was distributed worldwide. Four types of ART were discriminated: daily online replanning, online plan library, protocolled offline replanning (all three based on a protocol), and ad-hoc offline replanning.

RESULTS

The questionnaire was completed by 177 centres from 40 countries. ART was used by 61% of respondents (31% with protocol) for a median (range) of 3 (1-8) tumour sites. CBCT/MVCT was the main imaging modality except for online daily replanning (11 users) where 10 users used MR. Two thirds of respondents wished to implement ART for a new tumour site; 40% of these had plans to do it in the next 2 years. Human/material resources and technical limitations were the main barriers to further use and implementation.

CONCLUSIONS

ART was used for a broad range of tumour sites, mainly with ad-hoc offline replanning and for a median of 3 tumour sites. There was a large interest in implementing ART for more tumour sites, mainly limited by human/material resources and technical limitations. Daily online replanning was primarily performed on MR-linacs.

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PURPOSE

Image-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.

METHODS

Using a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.

RESULTS

The mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.

CONCLUSIONS

The presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.

Image-guided Radiotherapy to Manage Respiratory Motion: Lung and Liver

Organ motion as a result of respiratory and cardiac motion poses significant challenges for the accurate delivery of radiotherapy to both the thorax and the upper abdomen. Modern imaging techniques during radiotherapy simulation and delivery now permit better quantification of organ motion, which in turn reduces tumour and organ at risk position uncertainty. These imaging advances, coupled with respiratory correlated radiotherapy delivery techniques, have led to the development of a range of approaches to manage respiratory motion. This review summarises the key strategies of image-guided respiratory motion management with a focus on lung and liver radiotherapy.

Geometric and Dosimetric Evaluation of a Commercially Available Auto-segmentation Tool for Gross Tumour Volume Delineation in Locally Advanced Non-small Cell Lung Cancer: a Feasibility Study

AIMS

To quantify the reliability of a commercially available auto-segmentation tool in locally advanced non-small cell lung cancer using serial four-dimensional computed tomography (4DCT) scans during conventionally fractionated radiotherapy.

MATERIALS AND METHODS

Eight patients with serial 4DCT scans (n = 44) acquired over the course of radiotherapy were assessed. Each 4DCT had a physician-defined primary tumour manual contour (MC). An auto-contour (AC) and a user-adjusted auto-contour (UA-AC) were created for each scan. Geometric agreement of the AC and the UA-AC to the MC was assessed using the dice similarity coefficient (DSC), the centre of mass (COM) shift from the MC and the structure volume difference from the MC. Bland Altman analysis was carried out to assess agreement between contouring methods. Dosimetric reliability was assessed by comparison of planning target volume dose coverage on the MC and UA-AC. The time trend analysis of the geometric accuracy measures from the initial planning scan through to the final scan for each patient was evaluated using a Wilcoxon signed ranks test to assess the reliability of the UA-AC over the duration of radiotherapy.

RESULTS

User adjustment significantly improved all geometric comparison metrics over the AC alone. Improved agreement was observed in smaller tumours not abutting normal soft tissue and median values for geometric comparisons to the MC for DSC, tumour volume difference and COM offset were 0.80 (range 0.49-0.89), 0.8 cm³ (range 0.0-5.9 cm³) and 0.16 cm (range 0.09-0.69 cm), respectively. There were no significant differences in dose metrics measured from the MC and the UA-AC after Bonferroni correction. Variation in geometric agreement between the MC and the UA-AC were observed over the course of radiotherapy with both DSC (P = 0.035) and COM shift from the MC (ns) worsening. The median tumour volume difference from the MC improved at the later time point.

CONCLUSIONS

These findings suggest that the UA-AC can produce geometrically and dosimetrically acceptable contours for appropriately selected patients with non-small cell lung cancer. Larger studies are required to confirm the findings.

Image guidance in radiation therapy for better cure of cancer

The key goal and main challenge of radiation therapy is the elimination of tumors without any concurring damages of the surrounding healthy tissues and organs. Radiation doses required to achieve sufficient cancer-cell kill exceed in most clinical situations the dose that can be tolerated by the healthy tissues, especially when large parts of the affected organ are irradiated. High-precision radiation oncology aims at optimizing tumor coverage, while sparing normal tissues. Medical imaging during the preparation phase, as well as in the treatment room for localization of the tumor and directing the beam, referred to as image-guided radiotherapy (IGRT), is the cornerstone of precision radiation oncology. Sophisticated high-resolution real-time IGRT using X-rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. IGRT is the most convincing success story of radiation oncology over the last decades, and it remains a major driving force of innovation, contributing to the development of personalized oncology, for example, through the use of real-time imaging biomarkers for individualized dose delivery.

Mid-position treatment strategy for locally advanced lung cancer: a dosimetric study

OBJECTIVE

The internal target volume (ITV) strategy generates larger planning target volumes (PTVs) in locally advanced non-small cell lung cancer (LA-NSCLC) than the Mid-position (Mid-p) strategy. We investigated the benefit of the Mid-p strategy regarding PTV reduction and dose to the organs at risk (OARs).

METHODS

44 patients with LA-NSCLC were included in a randomized clinical study to compare ITV and Mid-p strategies. GTV were delineated by a physician on maximum intensity projection images and on Mid-p images from four-dimensional CTs. CTVs were obtained by adding 6 mm uniform margin for microscopic extension. CTV to PTV margins were calculated using the van Herk's recipe for setup and delineation errors. For the Mid-p strategy, the mean target motion amplitude was added as a random error. For both strategies, three-dimensional conformal plans delivering 60-66 Gy to PTV were performed. PTVs, dose-volume parameters for OARs (lung, esophagus, heart, spinal cord) were reported and compared.

RESULTS

With the Mid-p strategy, the median of volume reduction was 23.5 cm3 (p = 0.012) and 8.8 cm3 (p = 0.0083) for PTVT and PTVN respectively; the median mean lung dose reduction was 0.51 Gy (p = 0.0057). For 37.1% of the patients, delineation errors led to smaller PTV with the ITV strategy than with the Mid-p strategy.

CONCLUSION

PTV and mean lung dose were significantly reduced using the Mid-p strategy. Delineation uncertainty can unfavorably impact the advantage.

ADVANCES IN KNOWLEDGE

To the best of our knowledge, this is the first dosimetric comparison study between ITV and Mid-p strategies for LA-NSCLC.

Current radiotherapy techniques in NSCLC: challenges and potential solutions

Introduction: Radiotherapy is an important therapeutic strategy in the management of non-small cell lung cancer (NSCLC). In recent decades, technological implementations and the introduction of image guided radiotherapy (IGRT) have significantly increased the accuracy and tolerability of radiation therapy.Area covered: In this review, we provide an overview of technological opportunities and future prospects in NSCLC management.Expert opinion: Stereotactic body radiotherapy (SBRT) is now considered the standard approach in patients ineligible for surgery, while in operable cases, it is still under debate. Additionally, in combination with systemic treatment, SBRT is an innovative option for managing oligometastatic patients and features encouraging initial results in clinical outcomes. To date, in inoperable locally advanced NSCLC, the radical dose prescription has not changed (60 Gy in 30 fractions), despite the median overall survival progressively increasing. These results arise from technological improvements in precisely hitting target treatment volumes and organ at risk sparing, which are associated with better treatment qualities. Finally, for the management of NSCLC, proton and carbon ion therapies and the recent development of MR-Linac are new, intriguing technological approaches under investigation.