Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regression; however, CPH may be too simplistic as it assumes a linear relationship between covariables and the outcome. Alternative, non-linear machine learning (ML)-based approaches, such as random survival forests (RSFs) and, more recently, deep learning (DL) have been proposed; however, these techniques are largely black-box in nature, limiting explainability. We compared CPH, RSF and DL to predict overall survival (OS) of non-small cell lung cancer (NSCLC) patients receiving radiotherapy using pre-treatment covariables. We employed explainable techniques to provide insights into the contribution of each covariable on OS prediction. MATERIALS AND METHODS: The dataset contained 471 stage I-IV NSCLC patients treated with radiotherapy. We built CPH, RSF and DL OS prediction models using several baseline covariable combinations. 10-fold Monte-Carlo cross-validation was employed with a split of 70%:10%:20% for training, validation and testing, respectively. We primarily evaluated performance using the concordance index (C-index) and integrated Brier score (IBS). Local interpretable model-agnostic explanation (LIME) values, adapted for use in survival analysis, were computed for each model. RESULTS: The DL method exhibited a significantly improved C-index of 0.670 compared to the CPH and a significantly improved IBS of 0.121 compared to the CPH and RSF approaches. LIME values suggested that, for the DL method, the three most important covariables in OS prediction were stage, administration of chemotherapy and oesophageal mean radiation dose. CONCLUSION: We show that, using pre-treatment covariables, a DL approach demonstrates superior performance over CPH and RSF for OS prediction and use explainable techniques to provide transparency and interpretability.

Stereotactic arrhythmia radioablation: A multicenter pre-post intervention safety evaluation of the implantable cardioverter-defibrillator function.

BACKGROUND: Stereotactic arrhythmia radioablation (STAR) appears to be beneficial in selected patients with therapy-refractory ventricular tachycardia (VT). However, high-dose radiotherapy used for STAR-treatment may affect functioning of the patients' implantable cardioverter defibrillator (ICD) by direct effects of radiation on ICD components or cardiac tissue. Currently, the effect of STAR on ICD functioning remains unknown. METHODS: A retrospective pre-post multicenter study evaluating ICD functioning in the 12-month before and after STAR was performed. Patients with (non)ischemic cardiomyopathies with therapy-refractory VT and ICD who underwent STAR were included and the occurrence of ICD-related adverse events was collected. Evaluated ICD parameters included sensing, capture threshold and impedance. A linear mixed-effects model was used to investigate the association between STAR, radiotherapy dose and changes in lead parameters over time. RESULTS: In total, 43 patients (88% male) were included in this study. All patients had an ICD with an additional right atrial lead in 34 (79%) and a ventricular lead in 17 (40%) patients. Median ICD-generator dose was 0.1 Gy and lead tip dose ranged from 0-32 Gy. In one patient (2%), a reset occurred during treatment, but otherwise, STAR and radiotherapy dose were not associated with clinically relevant alterations in ICD leads parameters. CONCLUSIONS: STAR treatment did not result in major ICD malfunction. Only one radiotherapy related adverse event occurred during the study follow-up without patient harm. No clinically relevant alterations in ICD functioning were observed after STAR in any of the leads. With the reported doses STAR appears to be safe.

PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation.

Functional lung imaging modalities such as hyperpolarized gas MRI ventilation enable visualization and quantification of regional lung ventilation; however, these techniques require specialized equipment and exogenous contrast, limiting clinical adoption. Physiologically-informed techniques to map proton (1H)-MRI ventilation have been proposed. These approaches have demonstrated moderate correlation with hyperpolarized gas MRI. Recently, deep learning (DL) has been used for image synthesis applications, including functional lung image synthesis. Here, we propose a 3D multi-channel convolutional neural network that employs physiologically-informed ventilation mapping and multi-inflation structural 1H-MRI to synthesize 3D ventilation surrogates (PhysVENeT). The dataset comprised paired inspiratory and expiratory 1H-MRI scans and corresponding hyperpolarized gas MRI scans from 170 participants with various pulmonary pathologies. We performed fivefold cross-validation on 150 of these participants and used 20 participants with a previously unseen pathology (post COVID-19) for external validation. Synthetic ventilation surrogates were evaluated using voxel-wise correlation and structural similarity metrics; the proposed PhysVENeT framework significantly outperformed conventional 1H-MRI ventilation mapping and other DL approaches which did not utilize structural imaging and ventilation mapping. PhysVENeT can accurately reflect ventilation defects and exhibits minimal overfitting on external validation data compared to DL approaches that do not integrate physiologically-informed mapping.

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regional lung ventilation with exceptional detail within a single breath. However, this modality requires specialized equipment and exogenous contrast, which limits widespread clinical adoption. CT ventilation imaging employs various metrics to model regional ventilation from non-contrast CT scans acquired at multiple inflation levels and has demonstrated moderate spatial correlation with hyperpolarized gas MRI. Recently, deep learning (DL)-based methods, utilizing convolutional neural networks (CNNs), have been leveraged for image synthesis applications. Hybrid approaches integrating computational modeling and data-driven methods have been utilized in cases where datasets are limited with the added benefit of maintaining physiological plausibility. PURPOSE: To develop and evaluate a multi-channel DL-based method that combines modeling and data-driven approaches to synthesize hyperpolarized gas MRI lung ventilation scans from multi-inflation, non-contrast CT and quantitatively compare these synthetic ventilation scans to conventional CT ventilation modeling. METHODS: In this study, we propose a hybrid DL configuration that integrates model- and data-driven methods to synthesize hyperpolarized gas MRI lung ventilation scans from a combination of non-contrast, multi-inflation CT and CT ventilation modeling. We used a diverse dataset comprising paired inspiratory and expiratory CT and helium-3 hyperpolarized gas MRI for 47 participants with a range of pulmonary pathologies. We performed six-fold cross-validation on the dataset and evaluated the spatial correlation between the synthetic ventilation and real hyperpolarized gas MRI scans; the proposed hybrid framework was compared to conventional CT ventilation modeling and other non-hybrid DL configurations. Synthetic ventilation scans were evaluated using voxel-wise evaluation metrics such as Spearman's correlation and mean square error (MSE), in addition to clinical biomarkers of lung function such as the ventilated lung percentage (VLP). Furthermore, regional localization of ventilated and defect lung regions was assessed via the Dice similarity coefficient (DSC). RESULTS: We showed that the proposed hybrid framework is capable of accurately replicating ventilation defects seen in the real hyperpolarized gas MRI scans, achieving a voxel-wise Spearman's correlation of 0.57 ± 0.17 and an MSE of 0.017 ± 0.01. The hybrid framework significantly outperformed CT ventilation modeling alone and all other DL configurations using Spearman's correlation. The proposed framework was capable of generating clinically relevant metrics such as the VLP without manual intervention, resulting in a Bland-Altman bias of 3.04%, significantly outperforming CT ventilation modeling. Relative to CT ventilation modeling, the hybrid framework yielded significantly more accurate delineations of ventilated and defect lung regions, achieving a DSC of 0.95 and 0.48 for ventilated and defect regions, respectively. CONCLUSION: The ability to generate realistic synthetic ventilation scans from CT has implications for several clinical applications, including functional lung avoidance radiotherapy and treatment response mapping. CT is an integral part of almost every clinical lung imaging workflow and hence is readily available for most patients; therefore, synthetic ventilation from non-contrast CT can provide patients with wider access to ventilation imaging worldwide.

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1 H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters. PURPOSE: Develop a generalizable CNN for lung segmentation in 1 H-MRI, robust to pathology, acquisition protocol, vendor, and center. STUDY TYPE: Retrospective. POPULATION: A total of 809 1 H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6-85); 42% females) and 31 healthy participants (median age (range): 34 (23-76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1 H-MRI. ASSESSMENT: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. STATISTICAL TESTS: Kruskal-Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland-Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant. RESULTS: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880-0.987), Average HD of 1.63 mm (0.65-5.45) and XOR of 0.079 (0.025-0.240) on the testing set and a DSC of 0.973 (0.866-0.987), Average HD of 1.11 mm (0.47-8.13) and XOR of 0.054 (0.026-0.255) on external validation data. DATA CONCLUSION: The 3D CNN generated accurate 1 H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI.

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and quantification of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. Here, we evaluate several 3D convolutional neural networks to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 759 helium-3 (3He) or xenon-129 (129Xe) volumetric scans and corresponding expert segmentations from 341 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined 3He and 129Xe MRI scans using a 3D nn-UNet outperformed other DL methods, achieving a mean ± SD Dice coefficient of 0.963 ± 0.018, average boundary Hausdorff distance of 1.505 ± 0.969 mm, Hausdorff 95th percentile of 5.754 ± 6.621 mm and relative error of 0.075 ± 0.039. Moreover, limited differences in performance were observed between 129Xe and 3He scans in the testing set. Combined training on 129Xe and 3He yielded statistically significant improvements over the conventional methods (p < 0.0001). In addition, we observed very strong correlation and agreement between DL and expert segmentations, with Pearson correlation of 0.99 (p < 0.0001) and Bland-Altman bias of - 0.8%. The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and artefacts. This approach is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing.

Postoperative radiotherapy versus no postoperative radiotherapy in patients with completely resected non-small-cell lung cancer and proven mediastinal N2 involvement (Lung ART): an open-label, randomised, phase 3 trial.

BACKGROUND: In patients with non-small-cell lung cancer (NSCLC), the use of postoperative radiotherapy (PORT) has been controversial since 1998, because of one meta-analysis showing a deleterious effect on survival in patients with pN0 and pN1, but with an unclear effect in patients with pN2 NSCLC. Because many changes have occurred in the management of patients with NSCLC, the role of three-dimensional (3D) conformal PORT warrants further investigation in patients with stage IIIAN2 NSCLC. The aim of this study was to establish whether PORT should be part of their standard treatment. METHODS: Lung ART is an open-label, randomised, phase 3, superiority trial comparing mediastinal PORT to no PORT in patients with NSCLC with complete resection, nodal exploration, and cytologically or histologically proven N2 involvement. Previous neoadjuvant or adjuvant chemotherapy was allowed. Patients aged 18 years or older, with an WHO performance status of 0-2, were recruited from 64 hospitals and cancer centres in five countries (France, UK, Germany, Switzerland, and Belgium). Patients were randomly assigned (1:1) to either the PORT or no PORT (control) groups via a web randomisation system, and minimisation factors were the institution, administration of chemotherapy, number of mediastinal lymph node stations involved, histology, and use of pre-treatment PET scan. Patients received PORT at a dose of 54 Gy in 27 or 30 daily fractions, on five consecutive days a week. Three dimensional conformal radiotherapy was mandatory, and intensity-modulated radiotherapy was permitted in centres with expertise. The primary endpoint was disease-free survival, analysed by intention to treat at 3 years; patients from the PORT group who did not receive radiotherapy and patients from the control group with no follow-up were excluded from the safety analyses. This trial is now closed. This trial is registered with ClinicalTrials.gov number, NCT00410683. FINDINGS: Between Aug 7, 2007, and July 17, 2018, 501 patients, predominantly staged with 18F-fluorodeoxyglucose (18F-FDG) PET (456 [91%]; 232 (92%) in the PORT group and 224 (90%) in the control group), were enrolled and randomly assigned to receive PORT (252 patients) or no PORT (249 patients). At the cutoff date of May 31, 2019, median follow-up was 4·8 years (IQR 2·9-7·0). 3-year disease-free survival was 47% (95% CI 40-54) with PORT versus 44% (37-51) without PORT, and the median disease-free survival was 30·5 months (95% CI 24-49) in the PORT group and 22·8 months (17-37) in the control group (hazard ratio 0·86; 95% CI 0·68-1·08; p=0·18). The most common grade 3-4 adverse events were pneumonitis (13 [5%] of 241 patients in the PORT group vs one [<1%] of 246 in the control group), lymphopenia (nine [4%] vs 0), and fatigue (six [3%] vs one [<1%]). Late-grade 3-4 cardiopulmonary toxicity was reported in 26 patients (11%) in the PORT group versus 12 (5%) in the control group. Two patients died from pneumonitis, partly related to radiotherapy and infection, and one patient died due to chemotherapy toxicity (sepsis) that was deemed to be treatment-related, all of whom were in the PORT group. INTERPRETATION: Lung ART evaluated 3D conformal PORT after complete resection in patients who predominantly had been staged using (18F-FDG PET-CT and received neoadjuvant or adjuvant chemotherapy. 3-year disease-free survival was higher than expected in both groups, but PORT was not associated with an increased disease-free survival compared with no PORT. Conformal PORT cannot be recommended as the standard of care in patients with stage IIIAN2 NSCLC. FUNDING: French National Cancer Institute, Programme Hospitalier de Recherche Clinique from the French Health Ministry, Gustave Roussy, Cancer Research UK, Swiss State Secretary for Education, Research, and Innovation, Swiss Cancer Research Foundation, Swiss Cancer League.

Observational cohort study in older women with early breast cancer: Use of radiation therapy and impact on health-related quality of life and mortality.

BACKGROUND: Radiotherapy reduces in-breast recurrence risk in early breast cancer (EBC) in older women. This benefit may be small and should be balanced against treatment effect and holistic patient assessment. This study described treatment patterns according to fitness and impact on health-related quality-of-life (HRQoL). METHODS: A multicentre, observational study of EBC patients aged ≥ 70 years, undergoing breast-conserving surgery (BCS) or mastectomy, was undertaken. Associations between radiotherapy use, surgery, clinico-pathological parameters, fitness based on geriatric parameters and treatment centre were determined. HRQoL was measured using the European Organisation for the Research and Treatment of Cancer (EORTC) questionnaires. RESULTS: In 2013-2018 2811 women in 56 UK study centres underwent surgery with a median follow-up of 52 months. On multivariable analysis, age and tumour risk predicted radiotherapy use. Among healthier patients (based on geriatric assessments) with high-risk tumours, 534/613 (87.1%) having BCS and 185/341 (54.2%) having mastectomy received radiotherapy. In less fit individuals with low-risk tumours undergoing BCS, 149/207 (72.0%) received radiotherapy. Radiotherapy effects on HRQoL domains, including breast symptoms and fatigue were seen, resolving by 18 months. CONCLUSION: Radiotherapy use in EBC patients ≥ 70 years is affected by age and recurrence risk, whereas geriatric parameters have limited impact regardless of type of surgery. There was geographical variation in treatment, with some fit older women with high-risk tumours not receiving radiotherapy, and some older, low-risk, EBC patients receiving radiotherapy after BCS despite evidence of limited benefit. The impact on HRQoL is transient.

Bridging The Age Gap: observational cohort study of effects of chemotherapy and trastuzumab on recurrence, survival and quality of life in older women with early breast cancer.

BACKGROUND: Chemotherapy improves outcomes for high risk early breast cancer (EBC) patients but is infrequently offered to older individuals. This study determined if there are fit older patients with high-risk disease who may benefit from chemotherapy. METHODS: A multicentre, prospective, observational study was performed to determine chemotherapy (±trastuzumab) usage and survival and quality-of-life outcomes in EBC patients aged ≥70 years. Propensity score-matching adjusted for variation in baseline age, fitness and tumour stage. RESULTS: Three thousands four hundred sixteen women were recruited from 56 UK centres between 2013 and 2018. Two thousands eight hundred eleven (82%) had surgery. 1520/2811 (54%) had high-risk EBC and 2059/2811 (73%) were fit. Chemotherapy was given to 306/1100 (27.8%) fit patients with high-risk EBC. Unmatched comparison of chemotherapy versus no chemotherapy demonstrated reduced metastatic recurrence risk in high-risk patients(hazard ratio [HR] 0.36 [95% CI 0.19-0.68]) and in 541 age, stage and fitness-matched patients(adjusted HR 0.43 [95% CI 0.20-0.92]) but no benefit to overall survival (OS) or breast cancer-specific survival (BCSS) in either group. Chemotherapy improved survival in women with oestrogen receptor (ER)-negative cancer (OS: HR 0.20 [95% CI 0.08-0.49];BCSS: HR 0.12 [95% CI 0.03-0.44]).Transient negative quality-of-life impacts were observed. CONCLUSIONS: Chemotherapy was associated with reduced risk of metastatic recurrence, but survival benefits were only seen in patients with ER-negative cancer. Quality-of-life impacts were significant but transient. TRIAL REGISTRATION: ISRCTN 46099296.

Stereotactic ablative body radiotherapy in patients with oligometastatic cancers: a prospective, registry-based, single-arm, observational, evaluation study.

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is increasingly being used to treat oligometastatic cancers, but high-level evidence to provide a basis for policy making is scarce. Additional evidence from a real-world setting is required. We present the results of a national study of patients with extracranial oligometastases undergoing SABR, representing the largest dataset, to our knowledge, on outcomes in this population so far. METHODS: In 2015, National Health Service (NHS) England launched a Commissioning through Evaluation scheme that funded a prospective, registry-based, single-arm, observational, evaluation study of patients with solid cancer and extracranial oligometastases treated with SABR. Prescribed doses ranged from 24-60 Gy administered in three to eight fractions. The study was done at 17 NHS radiotherapy centres in England. Patients were eligible for the scheme if aged 18 years or older with confirmed primary carcinoma (excluding haematological malignancies), one to three extracranial metastatic lesions, a disease-free interval from primary tumour development to metastases of longer than 6 months (with the exception of synchronous colorectal liver metastases), a WHO performance status of 2 or lower, and a life expectancy of at least 6 months. The primary outcome was overall survival at 1 year and 2 years from the start of SABR treatment. The study is now completed. FINDINGS: Between June 15, 2015, and Jan 30, 2019, 1422 patients were recruited from 17 hospitals in England. The median age of the patients was 69 years (IQR 62-76), and the most common primary tumour was prostate cancer (406 [28·6%] patients). Median follow-up was 13 months (IQR 6-23). Overall survival was 92·3% (95% CI 90·5-93·9) at 1 year and 79·2% (76·0-82·1) at 2 years. The most common grade 3 adverse event was fatigue (28 [2·0%] of 1422 patients) and the most common serious (grade 4) event was increased liver enzymes (nine [0·6%]). Notreatment-related deaths were reported. INTERPRETATION: In patients with extracranial oligometastatic cancer, use of SABR was associated with high overall survival and low toxicity. 'The study findings complement existing evidence from a randomised, phase 2 trial, and represent high-level, real-world evidence supporting the use of SABR in this patient cohort, with a phase 3 randomised, controlled trial to confirm these findings underway. Based on the selection criteria in this study, SABR was commissioned by NHS England in March, 2020, as a treatment option for patients with oligometastatic disease. FUNDING: NHS England Commissioning through Evaluation scheme.

Bridging the Age Gap in breast cancer: Impact of chemotherapy on quality of life in older women with early breast cancer.

INTRODUCTION: Older patients with early breast cancer (EBC) derive modest survival benefit from chemotherapy but have increased toxicity risk. Data on the impact of chemotherapy for EBC on quality of life in older patients are limited, but this is a key determinant of treatment acceptance. We aimed to investigate its effect on quality of life in older patients enrolled in the Bridging the Age Gap study. MATERIALS AND METHODS: A prospective, multicentre, observational study of EBC patients ≥70 years old was conducted in 2013-2018 at 56 UK hospitals. Demographics, patient, tumour characteristics, treatments and adverse events were recorded. Quality of life was assessed using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaires (EORTC-QLQ) C30, BR23 and ELD 15 plus the Euroqol-5D (eq-5d) over 24 months and analysed at each time point using baseline adjusted linear regression analysis and propensity score-matching. RESULTS: Three thousand and four hundred sixteen patients were enrolled in the study; 1520 patients undergoing surgery and who had high-risk EBC were included in this analysis. 376/1520 (24.7%) received chemotherapy. At 6 months, chemotherapy had a significant negative impact in several EORTC-QLQ-C30 domains, including global health score, physical, role, social functioning, cognition, fatigue, nausea/vomiting, dyspnoea, appetite loss, diarrhoea and constipation. Similar trends were documented on other scales (EORTC-QLQ-BR23, EORTC-QLQ-ELD15 and EQ-5D-5L). Its impact was no longer significant at 18-24 months in unmatched and matched cohorts. CONCLUSIONS: The negative impact of chemotherapy on quality-of-life is clinically and statistically significant at 6 months but resolves by 18 months, which is crucial to inform decision-making for older patients contemplating chemotherapy. TRIAL REGISTRATION NUMBER ISRCTN: 46099296.

Radical accelerated radiotherapy for non-small cell lung cancer (NSCLC): A 5-year retrospective review of two dose fractionation schedules.

BACKGROUND AND PURPOSE: Numerous fractionation regimes are used for inoperable NSCLC patients not suitable for stereotactic ablative radiotherapy. Continuous hyperfractionated accelerated radiotherapy (CHART, 54 Gy, 36 fractions over 12 days) and hypofractionated accelerated radiotherapy (55 Gy, 20 fractions over 4 weeks) are recommended UK schedules. In this single-centre retrospective analysis, we compare both fractionation schemes for patients treated at our institution from 2010 to 15. MATERIALS AND METHODS: Clinical demographic, tumour and survival data were collected alongside radiotherapy dosimetric data from the Varian Eclipse Scripting application programming interface. Differences were assessed using independent samples t-tests. Multivariate survival analysis was performed using Cox regression. RESULTS: We identified 563 eligible patients; 43% received CHART and 57% hypofractionated radiotherapy. Median age was 71 years, 56% were male, 95% PET staged with 53% WHO performance status 0-1. 30%, 14%, 50% and 6% were stage I, II, III and IV, respectively. 38% of patients underwent induction chemotherapy. 99% completed their prescribed radiotherapy treatment. Overall response rate was 50% with a 6.5% 90-day mortality rate. Median disease-free survival was 19 months, 50% recurred locally. Median overall survival was 22.5 months with 48% alive at 2 years. Multivariate analysis identified histology, stage, performance status, chemotherapy and radiotherapy response as independent predictors of survival; no significant differences between radiotherapy regimes were observed. CONCLUSION: In our centre, CHART and hypofractionated accelerated radiotherapy produce similar outcomes. Dose escalation studies are in progress to develop these schedules to match outcomes reported in concurrent chemo-radiation studies.

Accelerated, Dose escalated, Sequential Chemoradiotherapy in Non-small-cell lung cancer (ADSCaN): a protocol for a randomised phase II study.

INTRODUCTION: Lung cancer is the most common cause of cancer mortality in the UK, and non-small-cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancers. Most patients present with inoperable disease; therefore, radiotherapy plays a major role in treatment. However, the majority of patients are not suitable for the gold standard treatment (concurrent chemoradiotherapy) due to performance status and comorbidities. Novel strategies integrating radiotherapy advances and radiobiological knowledge need to be evaluated in patients treated with sequential chemoradiotherapy. Four separate dose escalation accelerated radiotherapy schedules have been completed in UK (CHART-ED, IDEAL-CRT, I-START and Isotoxic IMRT). This study will compare these schedules with a UK standard sequential chemoradiotherapy schedule of 55 Gy in 20 fractions over 4 weeks. As it would be impossible to test all schedules in a phase III study, the aim is to use a combined randomised phase II screening/'pick the winner' approach to identify the best schedule to take into a randomised phase III study against conventionally fractionated radiotherapy. METHODS AND ANALYSIS: Suitable patients will have histologically/cytologically confirmed, stage III NSCLC and are able to undergo chemoradiotherapy treatment. The study will recruit 360 patients; 120 on the standard arm and 60 on each experimental arm. Patients will complete 2-4 cycles of platinum-based chemotherapy before being randomised to one of the radiotherapy schedules. The primary endpoint is progression-free survival, with overall survival, time to local-regional failure, toxicity and cost-effectiveness as secondary objectives. ETHICS AND DISSEMINATION: The study has received ethical approval (research ethics committee (REC) reference: 16/WS/0165) from the West of Scotland REC 1. The trial is conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Trial results will be published in a peer-reviewed journal and presented internationally. TRIAL REGISTRATION NUMBER: ISRCTN47674500.

Spatial Comparison of CT-Based Surrogates of Lung Ventilation With Hyperpolarized Helium-3 and Xenon-129 Gas MRI in Patients Undergoing Radiation Therapy.

PURPOSE: To develop and apply an image acquisition and analysis strategy for spatial comparison of computed tomography (CT)-ventilation images with hyperpolarized gas magnetic resonance imaging (MRI). METHODS AND MATERIALS: Eleven lung cancer patients underwent xenon-129 (129Xe) and helium-3 (3He) ventilation MRI and coregistered proton (1H) anatomic MRI. Expiratory and inspiratory breath-hold CTs were used for deformable image registration and calculation of 3 CT-ventilation metrics: Hounsfield unit (CTHU), Jacobian (CTJac), and specific gas volume change (CTSGV). Inspiration CT and hyperpolarized gas ventilation MRI were registered via same-breath anatomic 1H-MRI. Voxel-wise Spearman correlation coefficients were calculated between each CT-ventilation image and its corresponding 3He-/129Xe-MRI, and for the mean values in regions of interest (ROIs) ranging from fine to coarse in-plane dimensions of 5 × 5, 10 × 10, 15 × 15, and 20 × 20, located within the lungs as defined by the same-breath 1H-MRI lung mask. Correlation of 3He and 129Xe-MRI was also assessed. RESULTS: Spatial correlation of CT-ventilation against 3He/129Xe-MRI increased with ROI size. For example, for CTHU, mean ± SD Spearman coefficients were 0.37 ± 0.19/0.33 ± 0.17 at the voxel-level and 0.52 ± 0.20/0.51 ± 0.18 for 20 × 20 ROIs, respectively. Correlations were stronger for CTHU than for CTJac or CTSGV. Correlation of 3He with 129Xe-MRI was consistently higher than either gas against CT-ventilation maps over all ROIs (P < .05). No significant differences were observed between CT-ventilation versus 3He-MRI and CT-ventilation versus 129Xe-MRI. CONCLUSION: Comparison of ventilation-related measures from CT and registered hyperpolarized gas MRI is feasible at a voxel level using a dedicated acquisition and analysis protocol. Moderate correlation between CT-ventilation and MRI exists at a regional level. Correlation between MRI and CT is significantly less than that between 3He and 129Xe-MRI, suggesting that CT-ventilation surrogate measures may not be measuring lung ventilation alone.

Carboplatin in BRCA1/2-mutated and triple-negative breast cancer BRCAness subgroups: the TNT Trial.

Germline mutations in BRCA1/2 predispose individuals to breast cancer (termed germline-mutated BRCA1/2 breast cancer, gBRCA-BC) by impairing homologous recombination (HR) and causing genomic instability. HR also repairs DNA lesions caused by platinum agents and PARP inhibitors. Triple-negative breast cancers (TNBCs) harbor subpopulations with BRCA1/2 mutations, hypothesized to be especially platinum-sensitive. Cancers in putative 'BRCAness' subgroups-tumors with BRCA1 methylation; low levels of BRCA1 mRNA (BRCA1 mRNA-low); or mutational signatures for HR deficiency and those with basal phenotypes-may also be sensitive to platinum. We assessed the efficacy of carboplatin and another mechanistically distinct therapy, docetaxel, in a phase 3 trial in subjects with unselected advanced TNBC. A prespecified protocol enabled biomarker-treatment interaction analyses in gBRCA-BC and BRCAness subgroups. The primary endpoint was objective response rate (ORR). In the unselected population (376 subjects; 188 carboplatin, 188 docetaxel), carboplatin was not more active than docetaxel (ORR, 31.4% versus 34.0%, respectively; P = 0.66). In contrast, in subjects with gBRCA-BC, carboplatin had double the ORR of docetaxel (68% versus 33%, respectively; biomarker, treatment interaction P = 0.01). Such benefit was not observed for subjects with BRCA1 methylation, BRCA1 mRNA-low tumors or a high score in a Myriad HRD assay. Significant interaction between treatment and the basal-like subtype was driven by high docetaxel response in the nonbasal subgroup. We conclude that patients with advanced TNBC benefit from characterization of BRCA1/2 mutations, but not BRCA1 methylation or Myriad HRD analyses, to inform choices on platinum-based chemotherapy. Additionally, gene expression analysis of basal-like cancers may also influence treatment selection.

Comparison of 3 He and 129 Xe MRI for evaluation of lung microstructure and ventilation at 1.5T.

BACKGROUND: To support translational lung MRI research with hyperpolarized 129 Xe gas, comprehensive evaluation of derived quantitative lung function measures against established measures from 3 He MRI is required. Few comparative studies have been performed to date, only at 3T, and multisession repeatability of 129 Xe functional metrics have not been reported. PURPOSE/HYPOTHESIS: To compare hyperpolarized 129 Xe and 3 He MRI-derived quantitative metrics of lung ventilation and microstructure, and their repeatability, at 1.5T. STUDY TYPE: Retrospective. POPULATION: Fourteen healthy nonsmokers (HN), five exsmokers (ES), five patients with chronic obstructive pulmonary disease (COPD), and 16 patients with nonsmall-cell lung cancer (NSCLC). FIELD STRENGTH/SEQUENCE: 1.5T. NSCLC, COPD patients and selected HN subjects underwent 3D balanced steady-state free-precession lung ventilation MRI using both 3 He and 129 Xe. Selected HN, all ES, and COPD patients underwent 2D multislice spoiled gradient-echo diffusion-weighted lung MRI using both hyperpolarized gas nuclei. ASSESSMENT: Ventilated volume percentages (VV%) and mean apparent diffusion coefficients (ADC) were derived from imaging. COPD patients performed the whole MR protocol in four separate scan sessions to assess repeatability. Same-day pulmonary function tests were performed. STATISTICAL TESTS: Intermetric correlations: Spearman's coefficient. Intergroup/internuclei differences: analysis of variance / Wilcoxon's signed rank. Repeatability: coefficient of variation (CV), intraclass correlation (ICC) coefficient. RESULTS: A significant positive correlation between 3 He and 129 Xe VV% was observed (r = 0.860, P < 0.001). VV% was larger for 3 He than 129 Xe (P = 0.001); average bias, 8.79%. A strong correlation between mean 3 He and 129 Xe ADC was obtained (r = 0.922, P < 0.001). MR parameters exhibited good correlations with pulmonary function tests. In COPD patients, mean CV of 3 He and 129 Xe VV% was 4.08% and 13.01%, respectively, with ICC coefficients of 0.541 (P = 0.061) and 0.458 (P = 0.095). Mean 3 He and 129 Xe ADC values were highly repeatable (mean CV: 2.98%, 2.77%, respectively; ICC: 0.995, P < 0.001; 0.936, P < 0.001). DATA CONCLUSION: 129 Xe lung MRI provides near-equivalent information to 3 He for quantitative lung ventilation and microstructural MRI at 1.5T. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018.

Impact of field number and beam angle on functional image-guided lung cancer radiotherapy planning.

To investigate the effect of beam angles and field number on functionally-guided intensity modulated radiotherapy (IMRT) normal lung avoidance treatment plans that incorporate hyperpolarised helium-3 magnetic resonance imaging (3He MRI) ventilation data. Eight non-small cell lung cancer patients had pre-treatment 3He MRI that was registered to inspiration breath-hold radiotherapy planning computed tomography. IMRT plans that minimised the volume of total lung receiving ⩾20 Gy (V20) were compared with plans that minimised 3He MRI defined functional lung receiving ⩾20 Gy (fV20). Coplanar IMRT plans using 5-field manually optimised beam angles and 9-field equidistant plans were also evaluated. For each pair of plans, the Wilcoxon signed ranks test was used to compare fV20 and the percentage of planning target volume (PTV) receiving 90% of the prescription dose (PTV90). Incorporation of 3He MRI led to median reductions in fV20 of 1.3% (range: 0.2-9.3%; p = 0.04) and 0.2% (range: 0 to 4.1%; p = 0.012) for 5- and 9-field arrangements, respectively. There was no clinically significant difference in target coverage. Functionally-guided IMRT plans incorporating hyperpolarised 3He MRI information can reduce the dose received by ventilated lung without comprising PTV coverage. The effect was greater for optimised beam angles rather than uniformly spaced fields.

The relationship between smoking and quality of life in advanced lung cancer patients: a prospective longitudinal study.

PURPOSE: Smoking is a major cause of lung cancer, and continued smoking may compromise treatment efficacy and quality of life (health-related quality of life (HRQoL)) in patients with advanced lung cancer. Our aims were to determine (i) preference for treatments which promote quality over length of life depending on smoking status, (ii) the relationship between HRQoL and smoking status at diagnosis (T1), after controlling for demographic and clinical variables, and (iii) changes in HRQoL 6 months after diagnosis (T2) depending on smoking status. METHODS: Two hundred ninety-six patients with advanced lung cancer were given questionnaires to assess HRQoL (EORTC QLQ-C30), time-trade-off for life quality versus quantity (QQQ) and smoking history (current, former or never smoker) at diagnosis (T1) and 6 months later (T2). Medical data were extracted from case records. RESULTS: Questionnaires were returned by 202 (68.2 %) patients at T1 and 114 (53.3 %) at T2. Patients favoured treatments that would enhance quality of life over increased longevity. Those who continued smoking after diagnosis reported worse HRQoL than former smokers or those who never smoked. Smoking status was a significant independent predictor of coughing in T1 (worse in smokers) and cognitive functioning in T2 (better in never smokers). CONCLUSIONS: Smoking by patients with advanced lung cancer is associated with worse symptoms on diagnosis and poorer HRQoL for those who continue smoking. The results have implications to help staff explain the consequences of smoking to patients.