Dosimetric predictors of radiation-induced lung injury

Application of dose-gradient function in reducing radiation induced lung injury in breast cancer radiotherapy

OBJECTIVE

Try to create a dose gradient function (DGF) and test its effectiveness in reducing radiation induced lung injury in breast cancer radiotherapy.

MATERIALS AND METHODS

Radiotherapy plans of 30 patients after breast-conserving surgery were included in the study. The dose gradient function was defined as DGH=VDVp3, then the area under the DGF curve of each plan was calculated in rectangular coordinate system, and the minimum area was used as the trigger factor, and other plans were triggered to optimize for area reduction. The dosimetric parameters of target area and organs at risk in 30 cases before and after re-optimization were compared.

RESULTS

On the premise of ensuring that the target dose met the clinical requirements, the trigger factor obtained based on DGF could further reduce the V5, V10, V20, V30 and mean lung dose (MLD) of the ipsilateral lung in breast cancer radiotherapy, P < 0.01. And the D2cc and mean heart dose (MHD) of the heart were also reduced, P < 0.01. Besides, the NTCPs of the ipsilateral lung and the heart were also reduced, P < 0.01.

CONCLUSION

The trigger factor obtained based on DGF is efficient in reducing radiation induced lung injury in breast cancer radiotherapy.

An analysis of the impact of different levels of inspiratory volume using active breathing control on the intrafraction motion and dose coverage of target volumes in patients undergoing thoracic radiotherapy

PURPOSE

To determine whether the level of inspiratory volume affect the extent to which active breathing control (ABC) reduces intrafraction motion and the dose coverage of target volumes in patients receiving external beam radiation therapy (EBRT) to the thoracic region MATERIALS/METHODS: 20 patients undergoing thoracic radiotherapy enrolled in a prospective study using ABC for respiratory motion management and volumetric-modulated arc therapy (VMAT) as the treatment technique. They were randomized to one of two groups, the control group of 80% inspiratory volume and the other test group of 70%. At least one set of repeated CBCTs was done weekly. All images including CBCTs and Planning CTs were sent to MIM softwareTM for analysis of intrafraction motion using Dice Similarity Coefficient (DSC). The target dose conformality was assessed using conformation number (CN). Intention-to-treat analysis was employed for statistical purpose.

RESULTS

The DSC for the 70% and 80% inspiratory volume group were 0.93 and 0.92, respectively. For the 70% group, there was a significant negative correlation (p < 0.05) between DSC and time between two CBCTs, but not for the 80% group. The average percentage change in CN for the 70% and 80% group was 10.91% and 8.14%, respectively, and their difference was significant (p < 0.05). Furthermore, the actual change in volume had a significant positive correlation (p < 0.05) with the percentage change in CN for the 70% inspiratory volume group but not the 80% group.

CONCLUSION

More evidence suggests that the target volumes from the 80% inspiratory volume group have less intrafraction motion compared to the 70% group. The findings from the percentage change in CN suggest that there could potentially be less tumor motion for higher levels of inspiratory volume and this could possibly contribute to why intrafraction motion is less for the 80% inspiratory volume group.

Preoperative spirometry and BMI in deep inspiration breath-hold radiotherapy: the early detection of cardiac and lung dose predictors without radiation exposure

Background

This study aimed to investigate preoperative spirometry and BMI as early predictors of the mean heart and lung dose (MHD, MLD) in deep inspiration breath-hold (DIBH) radiotherapy.

Methods

Left-sided breast cancer patients underwent breast-conserving surgery followed by DIBH radiotherapy enrolled. Patients who were not available for preoperative spirometry were excluded. One hundred eligible patients were performed free-breathing (FB-) CT and DIBH-CT for plan comparison. We completed the correlative and multivariate analysis to develop the linear regression models for dose prediction. The residuals were calculated to explore the unpreferable subgroups and compare the prediction accuracy.

Results

Among the parameters, vital capacity (VC) and BMI showed the strongest negative correlation with MHD (r = − 0.33) and MLD (r = − 0.34), respectively. They were also significant in multivariate analysis (P < 0.001). Elderly and less VC were independent predictors of increasing absolute residuals (AR). The VC model showed no significant difference in AR compared to the model using the CT parameter of lung volume in FB (LV-FB): median AR of the LV-FB model vs. the VC model was 0.12 vs. 0.11 Gy (P = 0.79). On the other hand, the median AR of the MLD model was 0.38 Gy, showing no specific subgroups of larger AR.

Conclusion

Preoperative spirometry and BMI are significant predictors of MHD and MLD, respectively. Although elderly and low-VC patients may have larger predictive variations, spirometry might be a substitute for LV-FB as a predictor of MHD.

Organs at risk radiation dose constraints

Dose constraints are essential for performing dosimetry, especially for intensity modulation and for radiotherapy under stereotaxic conditions. We present the update of the recommendations of the French society of oncological radiotherapy for the use of these doses in classical current practice but also for reirradiation.

Imaging of the post-radiation chest in lung cancer

Radiation therapy using conventional fractionated external-beam or high-precision dose techniques including three-dimensional conformal radiotherapy, stereotactic body radiation therapy, intensity-modulated radiation therapy, and proton therapy, is a key component in the treatment of patients with lung cancer. Knowledge of the radiation technique used, radiation treatment plan, expected temporal evolution of radiation-induced lung injury and patient-specific parameters, such as previous radiotherapy, concurrent chemoradiotherapy, and/or immunotherapy, is important in imaging interpretation. This review discusses factors that affect the development and severity of radiation-induced lung injury and its radiological manifestations with emphasis on the differences between conventional radiation and high-precision dose radiotherapy techniques.

Autophagy markers as mediators of lung injury-implication for therapeutic intervention

Lung injury is characterized by inflammatory processes demonstrated as loss of function of the pulmonary capillary endothelial and alveolar epithelial cells. Autophagy is an intracellular digestion system that work as an inducible adaptive response to lung injury which is a resultant of exposure to various stress agents like hypoxia, ischemia-reperfusion and xenobiotics which may be manifested as acute lung injury (ALI), acute respiratory distress syndrome (ARDS), chronic lung injury (CLI), bronchopulmonary dysplasia (BPD), chronic obstructive pulmonary disease (COPD), asthma, ventilator-induced lung injury (VILI), ventilator-associated lung injury (VALI), pulmonary fibrosis (PF), cystic fibrosis (CF) and radiation-induced lung injury (RILI). Numerous regulators like LC3B-II, Beclin 1, p62, HIF1/BNIP3 and mTOR play pivotal role in autophagy induction during lung injury possibly for progression/inhibition of the disease state. The present review focuses on the critical autophagic mediators and their potential cross talk with the lung injury pathophysiology thereby bringing to limelight the possible therapeutic interventions.

Automatic feathering algorithm for VMAT craniospinal irradiation: A comprehensive comparison with other VMAT planning strategies

In craniospinal irradiation, field matching is very sensitive to intrafraction positional uncertainties in cranio-caudal direction, which could lead to severe overdoses/underdoses inside the planning target volume. During the last decade, significant efforts were made to develop volumetric-modulated arc therapy strategies, which were less sensitive to setup uncertainties. In this study, a treatment planning system-integrated method, named automatic feathering (AF) algorithm, was compared against other volumetric-modulated arc therapy strategies. Three patients were retrospectively included. Five different planning techniques were compared, including overlap (O), staggered overlap (SO), gradient optimization (GO), overlap with AF algorithm turned on (O-AF), and staggered overlap with AF algorithm turned on (SO-AF). Three overlapping lengths were considered (5 cm, 7.5 cm, and 10 cm). The middle isocenter was shifted of ±1 mm, ±3 mm, and ±5 mm to simulate setup uncertainties. Plan robustness against simulated uncertainties was evaluated by calculating near maximum and near minimum dose differences between shifted and nonshifted plans (ΔD_2%, ΔD_98%). Dose differences among combinations of techniques and junction lengths were tested using Wilcoxon signed-rank test. Higher ΔD_2% and ΔD_98% were obtained using the overlap technique (ΔD_2% = 15.4%, ΔD_98% = 15.0%). O-AF and SO-AF provided comparable plan robustness to GO technique. Their performance improved significantly for grater overlapping length. For 10-cm overlap and 5-mm shift, GO, O-AF, and SO-AF yielded to the better plan robustness (5.7% < ΔD_2% < 6.0%, 6.1% < ΔD_98% < 7.6%). SO provided an intermediate plan robustness (9.8% < ΔD_2% < 10.8%, 8.9% < ΔD_98% < 10.3%). The addition of AF to the overlap technique significantly improves plan robustness especially if larger overlapping lengths are used. Using the AF algorithm, plans become as robust as plans optimized with more sophisticated and time-consuming approaches (like GO).

The Role of Machine Learning in Knowledge-Based Response-Adapted Radiotherapy

With the continuous increase in radiotherapy patient-specific data from multimodality imaging and biotechnology molecular sources, knowledge-based response-adapted radiotherapy (KBR-ART) is emerging as a vital area for radiation oncology personalized treatment. In KBR-ART, planned dose distributions can be modified based on observed cues in patients' clinical, geometric, and physiological parameters. In this paper, we present current developments in the field of adaptive radiotherapy (ART), the progression toward KBR-ART, and examine several applications of static and dynamic machine learning approaches for realizing the KBR-ART framework potentials in maximizing tumor control and minimizing side effects with respect to individual radiotherapy patients. Specifically, three questions required for the realization of KBR-ART are addressed: (1) what knowledge is needed; (2) how to estimate RT outcomes accurately; and (3) how to adapt optimally. Different machine learning algorithms for KBR-ART application shall be discussed and contrasted. Representative examples of different KBR-ART stages are also visited.

Lung Cancer: Posttreatment Imaging: Radiation Therapy and Imaging Findings

Over the last few decades, advances in radiation therapy technology have markedly improved radiation delivery. Advancements in treatment planning with the development of image-guided radiotherapy and techniques such as proton therapy, allow precise delivery of high doses of radiation conformed to the tumor. These advancements result in improved locoregional control while reducing radiation dose to surrounding normal tissue. The radiologic manifestations of these techniques can differ from radiation induced lung disease seen with traditional radiation therapy. Awareness of these radiologic manifestations and correlation with radiation treatment plans are important to differentiate expected radiation induced lung injury from recurrence, infection and drug toxicity.

Lung Cancer: Posttreatment Imaging: Radiation Therapy and Imaging Findings

In this review, we discuss the different radiation delivery techniques available to treat non-small cell lung cancer, typical radiologic manifestations of conventional radiotherapy, and different patterns of lung injury and temporal evolution of the newer radiotherapy techniques. More sophisticated techniques include intensity-modulated radiotherapy, stereotactic body radiotherapy, proton therapy, and respiration-correlated computed tomography or 4-dimensional computed tomography for radiotherapy planning. Knowledge of the radiation treatment plan and technique, the completion date of radiotherapy, and the temporal evolution of radiation-induced lung injury is important to identify expected manifestations of radiation-induced lung injury and differentiate them from tumor recurrence or infection.

Imaging of Radiation Treatment of Lung Cancer

Radiation therapy is an important modality in the treatment of patients with lung cancer. Recent advances in delivering radiotherapy were designed to improve loco-regional tumor control by focusing higher doses on the tumor. More sophisticated techniques in treatment planning include 3-dimensional conformal radiation therapy, intensity-modulated radiotherapy, stereotactic body radiotherapy, and proton therapy. These methods may result in nontraditional patterns of radiation injury and various radiologic appearances that can be mistaken for recurrence, infection and other lung diseases. Knowledge of radiological manifestations, awareness of new radiation delivery techniques and correlation with radiation treatment plans are essential in order to correctly interpret imaging in these patients.

Dosimetric and clinical predictors of radiation-induced lung toxicity in esophageal carcinoma

Aims and background

Radiation-induced lung toxicity occurs frequently in patients with esophageal carcinoma. This study aims to evaluate the clinical and three-dimensional dosimetric parameters associated with lung toxicity after radiotherapy for esophageal carcinoma.

Methods and study design

The records of 56 patients treated for esophageal carcinoma were reviewed. The Radiation Therapy Oncology Group criteria for grading of lung toxicity were followed. Spearman's correlation test, the chi-square test and logistic regression analyses were used for statistical analysis.

Results

Ten of the 56 patients developed acute toxicity. The toxicity grades were grade 2 in 7 patients and grade 3 in 3 patients; none of the patients developed grade 4 or worse toxicity. One case of toxicity occurred during radiotherapy and 9 occurred 2 weeks to 3 months after radiotherapy. The median time was 2.0 months after radiotherapy. Fourteen patients developed late irradiated lung injury, 3 after 3.5 months, 7 after 9 months, and 4 after 14 months. Radiographic imaging demonstrated patchy consolidation (n = 5), atelectasis with parenchymal distortion (n = 6), and solid consolidation (n = 3). For acute toxicity, the irradiated esophageal volume, number of fields, and most dosimetric parameters were predictive. For late toxicity, chemotherapy combined with radiotherapy and other dosimetric parameters were predictive. No obvious association between the occurrence of acute and late injury was observed.

Conclusions

The percent of lung tissue receiving at least 25 Gy (V25), the number of fields, and the irradiated length of the esophagus can be used as predictors of the risk of acute toxicity. Lungs V30, as well as chemotherapy combined with radiotherapy, are predictive of late lung injury.

Exposure of the lungs in breast cancer radiotherapy: A systematic review of lung doses published 2010-2015

BACKGROUND AND PURPOSE

We report a systematic review of lung radiation doses from breast cancer radiotherapy.

METHODS AND MATERIALS

Studies describing breast cancer radiotherapy regimens published during 2010-2015 and reporting lung dose were included. Doses were compared between different countries, anatomical regions irradiated, techniques and use of breathing adaptation.

RESULTS

471 regimens from 32 countries were identified. The average mean ipsilateral lung dose (MLDipsi) was 9.0 Gy. MLDipsi for supine radiotherapy with no breathing adaption was 8.4 Gy for whole breast/chest wall (WB/CW) radiotherapy, 11.2 Gy when the axilla/supraclavicular fossa was irradiated, and 14.0 Gy with the addition of internal mammary chain irradiation; breathing adaptation reduced MLDipsi by 1 Gy, 2 Gy and 3 Gy respectively (p < 0.005). For WB/CW radiotherapy, MLDipsi was lowest for tangents in prone (1.2 Gy) or lateral decubitus (0.8 Gy) positions. The highest MLDipsi was for IMRT in supine position (9.4 Gy). The average mean contralateral lung dose (MLDcont) for WB/CW radiotherapy was higher for IMRT (3.0 Gy) than for tangents (0.8 Gy).

CONCLUSIONS

Lung doses from breast cancer radiotherapy varied substantially worldwide, even between studies describing similar regimens. Lymph node inclusion and IMRT use increased exposure, while breathing adaptation and prone/lateral decubitus positioning reduced it.

Radiogenomics and radiotherapy response modeling

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

Perspectives on making big data analytics work for oncology

Oncology, with its unique combination of clinical, physical, technological, and biological data provides an ideal case study for applying big data analytics to improve cancer treatment safety and outcomes. An oncology treatment course such as chemoradiotherapy can generate a large pool of information carrying the 5Vs hallmarks of big data. This data is comprised of a heterogeneous mixture of patient demographics, radiation/chemo dosimetry, multimodality imaging features, and biological markers generated over a treatment period that can span few days to several weeks. Efforts using commercial and in-house tools are underway to facilitate data aggregation, ontology creation, sharing, visualization and varying analytics in a secure environment. However, open questions related to proper data structure representation and effective analytics tools to support oncology decision-making need to be addressed. It is recognized that oncology data constitutes a mix of structured (tabulated) and unstructured (electronic documents) that need to be processed to facilitate searching and subsequent knowledge discovery from relational or NoSQL databases. In this context, methods based on advanced analytics and image feature extraction for oncology applications will be discussed. On the other hand, the classical p (variables)≫n (samples) inference problem of statistical learning is challenged in the Big data realm and this is particularly true for oncology applications where p-omics is witnessing exponential growth while the number of cancer incidences has generally plateaued over the past 5-years leading to a quasi-linear growth in samples per patient. Within the Big data paradigm, this kind of phenomenon may yield undesirable effects such as echo chamber anomalies, Yule-Simpson reversal paradox, or misleading ghost analytics. In this work, we will present these effects as they pertain to oncology and engage small thinking methodologies to counter these effects ranging from incorporating prior knowledge, using information-theoretic techniques to modern ensemble machine learning approaches or combination of these. We will particularly discuss the pros and cons of different approaches to improve mining of big data in oncology.

Toward a planning scheme for emission guided radiation therapy (EGRT): FDG based tumor tracking in a metastatic breast cancer patient

PURPOSE

Emission guided radiation therapy (EGRT) is a new modality that uses PET emissions in real-time for direct tumor tracking during radiation delivery. Radiation beamlets are delivered along positron emission tomography (PET) lines of response (LORs) by a fast rotating ring therapy unit consisting of a linear accelerator (Linac) and PET detectors. The feasibility of tumor tracking and a primitive modulation method to compensate for attenuation have been demonstrated using a 4D digital phantom in our prior work. However, the essential capability of achieving dose modulation as in conventional intensity modulated radiation therapy (IMRT) treatments remains absent. In this work, the authors develop a planning scheme for EGRT to accomplish sophisticated intensity modulation based on an IMRT plan while preserving tumor tracking.

METHODS

The planning scheme utilizes a precomputed LOR response probability distribution to achieve desired IMRT planning modulation with effects of inhomogeneous attenuation and nonuniform background activity distribution accounted for. Evaluation studies are performed on a 4D digital patient with a simulated lung tumor and a clinical patient who has a moving breast cancer metastasis in the lung. The Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm. The IMRT plan is optimized for a planning target volume (PTV) that encompasses the tumor motion using the MOSEK package and a Pinnacle3™ workstation (Philips Healthcare, Fitchburg, WI) for digital and clinical patients, respectively. To obtain the emission data for both patients, the Geant4 application for tomographic emission (GATE) package and a commercial PET scanner are used. As a comparison, 3D and helical IMRT treatments covering the same PTV based on the same IMRT plan are simulated.

RESULTS

3D and helical IMRT treatments show similar dose distribution. In the digital patient case, compared with the 3D IMRT treatment, EGRT achieves a 15.1% relative increase in dose to 95% of the gross tumor volume (GTV) and a 31.8% increase to 50% of the GTV. In the patient case, EGRT yields a 15.2% relative increase in dose to 95% of the GTV and a 20.7% increase to 50% of the GTV. The organs at risk (OARs) doses are kept similar or lower for EGRT in both cases. Tumor tracking is observed in the presence of planning modulation in all EGRT treatments.

CONCLUSIONS

As compared to conventional IMRT treatments, the proposed EGRT planning scheme allows an escalated target dose while keeping dose to the OARs within the same planning limits. With the capabilities of incorporating planning modulation and accurate tumor tracking, EGRT has the potential to greatly improve targeting in radiation therapy and enable a practical and effective implementation of 4D radiation therapy for planning and delivery.

Contribution of three-dimensional conformal intensity-modulated radiation therapy for women affected by bulky stage II supradiaphragmatic Hodgkin disease

Purpose

To analyze the outcome and dose distribution of intensity-modulated radiation therapy (IMRT) by helical tomotherapy in women treated for large supradiaphragmatic Hodgkin’s disease.

Material and methods

A total of 13 patients received adjuvant radiation at a dose of 30 Gy to the initially involved sites with a boost of 6 Gy to those areas suspected of harboring residual disease on the simulation CT scan.

Results

With a median follow-up of 23 months, the two-year progression-free survival was 91.6%, and the 2- and 3-year overall survivals were 100%. We did not report any heart or lung acute side effects. The conformity index of PTV (Planning Target Volume) was better for IMRT than for 3D-CRT (p=0.001). For the breasts, lungs, heart, thyroid and esophagus, the volume distributions favored the IMRT plans. For the breasts, the V_20Gy, V_25Gy and V_30Gy were 1.5, 2.5 and 3.5 times lower, respectively, for IMRT than for 3D-CRT. For the lung tissues, the V_20Gy and V_30Gy were 2 times and 4.5 times lower, respectively, for IMRT than for 3D-CRT. For the heart, the V_20Gy and V_30Gy were 1.4 and 2 times lower, respectively, for IMRT than for 3D-CRT. For the esophagus, the V_35Gy was 1.7 lower for IMRT than for 3D-CRT, and for the thyroid, the V_30Gy was 1.2 times lower for IMRT.

Conclusion

IMRT by helical tomotherapy improved the PTV coverage and dramatically decreased the dose in organs at risk. The treatment was well tolerated, but a longer follow-up is necessary to prove a translation of these dosimetric improvements in the outcome of the patients.

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.

Radiation-related treatment effects across the age spectrum: differences and similarities or what the old and young can learn from each other

Radiation related effects in children and adults limit the delivery of effective radiation doses and result in long-term morbidity affecting function and quality of life. Improvements in our understanding of the etiology and biology of these effects, including the influence of clinical variables, dosimetric factors, and the underlying biological processes have made treatment safer and more efficacious. However, the approach to studying and understanding these effects differs between children and adults. Using the pulmonary and skeletal organ systems as examples, comparisons are made across the age spectrum for radiation related effects, including pneumonitis, pulmonary fibrosis, osteonecrosis, and fracture. Methods for dosimetric analysis, incorporation of imaging and biology as well a length of follow-up are compared, contrasted, and discussed for both organ systems in children and adults. Better understanding of each age specific approach and how it differs may improve our ability to study late effects of radiation across the ages.

Incidence and correlates of radiation pneumonitis in pediatric patients with partial lung irradiation

PURPOSE

To provide a radiation pneumonitis risk estimate and investigate the correlation of clinical and dosimetric factors in pediatric patients receiving chest irradiation.

METHODS AND MATERIALS

A total of 122 patients diagnosed with sarcoma or Hodgkin lymphoma who received radiotherapy to the chest were evaluated for symptomatic radiation pneumonitis (Common Toxicity Criteria Grade 1 with respiratory symptom or higher grade). Pneumonitis data were collected from either prospective toxicity screenings as part of a clinical trial or through chart review. Dosimetric parameters including V(10)-V(25), mean lung dose, binned lung dose, and tissue complication probability models were used, as well as clinical features to correlate with the development of pneumonitis.

RESULTS

The 1- and 2-year cumulative incidence of symptomatic radiation pneumonitis for all patients was 8.2% and 9.1%, respectively. Nine patients experienced symptomatic Grade 1 toxicity, and 2 experienced Grade 2. From univariate analysis, chemotherapy containing bleomycin (chi(2) test, p = 0.027) and V(24) (logistic regression, p = 0.019) were the clinical and dosimetric factors that resulted in statistically significant differences in the occurrence of pneumonitis. The probability of pneumonitis increased more dramatically with increasing V(24) in patients receiving bleomycin than in those who did not. Adult tissue complication models did not differentiate pediatric patients with radiation pneumonitis from those without.

CONCLUSIONS

The incidence of symptomatic radiation pneumonitis in pediatric patients is low and its severity mild. Parameters frequently used in adult radiation oncology provide some guidance as to risk, but pediatric patients warrant their own specific models for risk assessment, incorporating dosimetry and clinical factors.

Predicting radiotherapy outcomes using statistical learning techniques

Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model variables. These models have the capacity to predict on unseen data.

Bioinformatics methods for learning radiation-induced lung inflammation from heterogeneous retrospective and prospective data

Radiotherapy outcomes are determined by complex interactions between physical and biological factors, reflecting both treatment conditions and underlying genetics. Recent advances in radiotherapy and biotechnology provide new opportunities and challenges for predicting radiation-induced toxicities, particularly radiation pneumonitis (RP), in lung cancer patients. In this work, we utilize datamining methods based on machine learning to build a predictive model of lung injury by retrospective analysis of treatment planning archives. In addition, biomarkers for this model are extracted from a prospective clinical trial that collects blood serum samples at multiple time points. We utilize a 3-way proteomics methodology to screen for differentially expressed proteins that are related to RP. Our preliminary results demonstrate that kernel methods can capture nonlinear dose-volume interactions, but fail to address missing biological factors. Our proteomics strategy yielded promising protein candidates, but their role in RP as well as their interactions with dose-volume metrics remain to be determined.

Helical tomotherapy for simultaneous multitarget radiotherapy for pulmonary metastasis

PURPOSE

To retrospectively evaluate our experience with tomotherapy for simultaneous multitarget radiotherapy in patients with pulmonary metastases.

METHODS AND MATERIALS

Thirty-one patients were treated with tomotherapy for pulmonary metastases. We defined gross tumor volume (GTV) in computed tomography scans, and the margin of the planning target volume was 1 to 1.5 cm from the GTV. The median doses prescribed were 50 Gy and 40 Gy delivered in 10 fractions over 2 weeks to the 95% isodose volume of the GTV and planning target volume, respectively. Prior to each treatment, online corrections were made in the three axes, and rotation was done after registration of the megavoltage and simulation computed tomography scans. Survival was calculated from the completion of tomotherapy, using the Kaplan-Meier method and log rank test.

RESULTS

The overall survival rate at 12 months was 60.5%, and the median survival time was 16.0 months. A rating of 1 or below on the Eastern Cooperative Oncology Group scale, a breast or colon cancer as the primary cancer, primary lesions that were completely controlled, and a response maintained at 3 months after tomotherapy were shown by univariate analysis to be statistically significant favorable prognostic factors. Progression-free survival rates at 1 and 2 years were 39.6% and 27.7%, respectively. The posttreatment failure rate was 64.5%, the local failure rate was 9.7%, the regional failure rate was 51.6%, and the synchronous local and regional failure rate was 3.2%. Grades I and II radiation-related toxicity levels were observed in 41.9% and 16.0% of patients, respectively. There were no treatment-related deaths.

CONCLUSIONS

Tomotherapy could be offered to patients as a safe and effective treatment in select patients with lung metastases. However, large-scale, prospective clinical trials should be done to confirm our results.

Using patient data similarities to predict radiation pneumonitis via a self-organizing map

This work investigates the use of the self-organizing map (SOM) technique for predicting lung radiation pneumonitis (RP) risk. SOM is an effective method for projecting and visualizing high-dimensional data in a low-dimensional space (map). By projecting patients with similar data (dose and non-dose factors) onto the same region of the map, commonalities in their outcomes can be visualized and categorized. Once built, the SOM may be used to predict pneumonitis risk by identifying the region of the map that is most similar to a patient's characteristics. Two SOM models were developed from a database of 219 lung cancer patients treated with radiation therapy (34 clinically diagnosed with Grade 2+ pneumonitis). The models were: SOM(all) built from all dose and non-dose factors and, for comparison, SOM(dose) built from dose factors alone. Both models were tested using ten-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Models SOM(all) and SOM(dose) yielded ten-fold cross-validated ROC areas of 0.73 (sensitivity/specificity = 71%/68%) and 0.67 (sensitivity/specificity = 63%/66%), respectively. The significant difference between the cross-validated ROC areas of these two models (p < 0.05) implies that non-dose features add important information toward predicting RP risk. Among the input features selected by model SOM(all), the two with highest impact for increasing RP risk were: (a) higher mean lung dose and (b) chemotherapy prior to radiation therapy. The SOM model developed here may not be extrapolated to treatment techniques outside that used in our database, such as several-field lung intensity modulated radiation therapy or gated radiation therapy.

Predicting Risk of Radiation-Induced Lung Injury

Radiation-induced lung injury (RILI) is the most common, dose-limiting complication of thoracic radio- and radiochemotherapy. Unfortunately, predicting which patients will suffer from this complication is extremely difficult. Ideally, individual phenotype- and genotype-based risk profiles should be able to identify patients who are resistant to RILI and who could benefit from dose escalation in chemoradiotherapy. This could result in better local control and overall survival. We review the risk predictors that are currently in clinical use--dosimetric parameters of radiotherapy such as normal tissue complication probability, mean lung dose, V20 and V30--as well as biomarkers that might individualize risk profiles. These biomarkers comprise a variety of proinflammatory and profibrotic cytokines and molecules including transforming growth factor beta1 that are implicated in development and persistence of RILI. Dosimetric parameters of radiotherapy show a low negative predictive value of 60% to 80%. Depending on the studied molecule, negative predictive value of biomarkers is approximately 50%. The predictive power of biomarkers might be increased if they are coupled with radiogenomics, e.g., genotyping analysis of single nucleotide polymorphisms in transforming growth factor beta1, transforming growth factor beta1 pathway genes, and other cytokines. Genetic variability and the complexity of RILI and its underlying molecular mechanisms make identification of biological risk predictors challenging. Further investigations are needed to develop more effective risk predictors of RILI.

Changes in Expression of Injury After Irradiation of Increasing Volumes in Rat Lung

PURPOSE

To improve the cure rates of thoracic malignancies by radiation dose escalation, very accurate insight is required in the dose delivery parameters that maximally spare normal lung function. Radiation-induced lung complications are classically divided into an early pneumonitic and a late fibrotic phase. This study investigated the relative dose-volume sensitivity, underlying pathologic findings, and consequentiality of early to late pathologic features.

METHODS AND MATERIALS

We used high-precision, graded dose-volume lung irradiations and followed the time dependency of the morphologic sequelae in relation to overall respiratory function.

RESULTS

Two distinct pathologic lesions were identified in the early postirradiation period (6-12 weeks): vascular inflammation and parenchymal inflammation. Vascular inflammation occurred at single doses as low as 9 Gy. This translated into early respiratory dysfunction only when a large lung volume had been irradiated and was reversible with time. Parenchymal inflammation was seen after higher doses only (onset at 16 Gy), progressed into later fibrotic remodeling but did not translate into dysfunction at a 25% lung volume even after single doses up to 36 Gy.

CONCLUSION

Our data imply that a low dose scattered over a large lung volume causes more early toxicity than an extreme dose confined to a small volume. Such findings are crucial for clinical treatment planning of dose escalations and choices for modern radiotherapy techniques.

NTCP modelling and pulmonary function tests evaluation for the prediction of radiation induced pneumonitis in non-small-cell lung cancer radiotherapy

This work aims to evaluate the predictive strength of the relative seriality, parallel and Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) models regarding the incidence of radiation pneumonitis (RP), in a group of patients following lung cancer radiotherapy and also to examine their correlation with pulmonary function tests (PFTs). The study was based on 47 patients who received radiation therapy for stage III non-small-cell lung cancer. For each patient, lung dose volume histograms (DVHs) and the clinical treatment outcome were available. Clinical symptoms, radiological findings and pulmonary function tests incorporated in a post-treatment follow-up period of 18 months were used to assess the manifestation of radiation induced complications. Thirteen of the 47 patients were scored as having radiation induced pneumonitis, with RTOG criteria grade 3 and 28 of the 47 with RTOG criteria grade 2. Using this material, different methods of estimating the likelihood of radiation effects were evaluated, by analysing patient data based on their full dose distributions and associating the calculated complication rates with the clinical follow-up records. Lungs were evaluated as a paired organ as well as individual lungs. Of the NTCP models examined in the overall group considering the dose distribution in the ipsilateral lung, all models were able to predict radiation induced pneumonitis only in the case of grade 2 radiation pneumonitis score, with the LKB model giving the best results (chi2-test: probability of agreement between the observed and predicted results Pchi(chi2)=0.524 using the 0.05 significance level). The NTCP modelling considering lungs as a paired organ did not give statistically acceptable results. In the case of lung cancer radiotherapy, the application of different published radiobiological parameters alters the NTCP results, but not excessively as in the case of breast cancer radiotherapy. In this relatively small group of lung cancer patients, no positive statistical correlation could be established between the incidence of radiation pneumonitis as estimated by NTCP models and the pulmonary function test evaluation. However, the use of PFTs as markers or predictors for the incidence or severity of radiation induced pneumonitis must be investigated further.

The atlas of complication incidence: a proposal for a new standard for reporting the results of radiotherapy protocols

We present a new method of reporting the results of radiotherapy protocols. The dose-volume atlas of complication incidence is a comprehensive and unbiased summary of the dose-volume exposures and complications occurring in patients after treatment. This new tool provides clear and systematic information about the safety of regions of dose-volume exposure previously treated that can be used when considering new treatments. Actuarial and model-dependent versions of the atlas are described. By using the raw data in the appropriate forms of the atlas, logistic regression, Kaplan-Meier, and Cox proportional hazards analysis can be performed, allowing for the independent calculation of dose-volume response. The data required are simple enough that provided compatible definitions of dose, volume, and complications are used, atlases from different protocols are potentially additive, facilitating the meta-analysis of inter-interinstitutional data. If this method were adopted as a standard for reporting the outcome of treatment protocols, a potentially synergistic increase in the utility of each protocol could result.

Clinical dose-volume histogram analysis in predicting radiation pneumonitis in Hodgkin's lymphoma

PURPOSE

To quantify the incidence of radiation pneumonitis (RP) in a modern Hodgkin's lymphoma (HL) cohort, and to identify any clinically relevant parameters that may influence the risk of RP.

METHODS AND MATERIALS

Between January 2003 and February 2005, 64 consecutive HL patients aged 18 years or older receiving radical mediastinal radiation therapy (RT) were retrospectively reviewed. Symptomatic cases of radiation pneumonitis were identified. Dose-volume histogram parameters, including V(13), V(20), V(30), and mean lung dose (MLD), were quantified.

RESULTS

At a median follow-up of 2.1 years, the actuarial survival for all patients was 91% at 3 years. There were 2 (2/64) cases of Radiation Therapy Oncology Group (RTOG) Grade 2 RP (incidence 3.1%). Both index cases with corresponding V(20) values of 47.0% and 40.7% were located in the upper quartile (2/16 cases), defined by a V(20) value of > or =36%, an incidence of 12.5% (p = 0.03). Similarly for total MLD, both index cases with values of 17.6 Gy and 16.4 Gy, respectively, were located in the upper quartile defined by MLD > or =14.2 Gy, an incidence of 11.8% (2/17 cases, p = 0.02).

CONCLUSIONS

Despite relatively high V(20) values in this study of HL patients, the incidence of RP was only 3%, lower compared with the lung cancer literature. We suggest the following clinically relevant parameters be considered in treatment plan assessment: a V(20) greater than 36% and an MLD greater than 14 Gy, over and above which the risk of RTOG Grade 2 or greater RP would be considered clinically significant.

Does transforming growth factor-beta1 predict for radiation-induced pneumonitis in patients treated for lung cancer?

The purpose of the study was to reassess the utility of transforming growth factor-beta-1 (TGF-beta1) together with dosimetric and tumor parameters as a predictor for radiation pneumonitis (RP). Of the 121 patients studied, 32 (26.4%) developed grade > or =1 RP, and 27 (22.3%) developed grade > or =2 RP. For the endpoint of grade > or =1 RP, those with V30>30% and an end-RT/baseline TGF-beta1 ratio> or =1 had a significantly higher incidence of RP than did those with V30>30% and an end-RT/baseline TGF-beta1 ratio<1. For most other patient groups, there were no clear associations between TGF-beta1 values and rates of RP. These findings suggest that TGF-beta1 is generally not predictive for RP except for the group of patients with a high V30.

Multivariable modeling of radiotherapy outcomes, including dose–volume and clinical factors

PURPOSE

The probability of a specific radiotherapy outcome is typically a complex, unknown function of dosimetric and clinical factors. Current models are usually oversimplified. We describe alternative methods for building multivariable dose-response models.

METHODS

Representative data sets of esophagitis and xerostomia are used. We use a logistic regression framework to approximate the treatment-response function. Bootstrap replications are performed to explore variable selection stability. To guard against under/overfitting, we compare several analytical and data-driven methods for model-order estimation. Spearman's coefficient is used to evaluate performance robustness. Novel graphical displays of variable cross correlations and bootstrap selection are demonstrated.

RESULTS

Bootstrap variable selection techniques improve model building by reducing sample size effects and unveiling variable cross correlations. Inference by resampling and Bayesian approaches produced generally consistent guidance for model order estimation. The optimal esophagitis model consisted of 5 dosimetric/clinical variables. Although the xerostomia model could be improved by combining clinical and dose-volume factors, the improvement would be small.

CONCLUSIONS

Prediction of treatment response can be improved by mixing clinical and dose-volume factors. Graphical tools can mitigate the inherent complexity of multivariable modeling. Bootstrap-based variable selection analysis increases the reliability of reported models. Statistical inference methods combined with Spearman's coefficient provide an efficient approach to estimating optimal model order.

Is intensity-modulated radiotherapy better than conventional radiation treatment and three-dimensional conformal radiotherapy for mediastinal masses in patients with Hodgkin's disease, and is there a role for beam orientation optimization and dose constraints assigned to virtual volumes?

PURPOSE

To evaluate the role of beam orientation optimization and the role of virtual volumes (VVs) aimed at protecting adjacent organs at risk (OARs), and to compare various intensity-modulated radiotherapy (IMRT) setups with conventional treatment with anterior and posterior fields and three-dimensional conformal radiotherapy (3D-CRT).

METHODS AND MATERIALS

Patients with mediastinal masses in Hodgkin's disease were treated with combined modality therapy (three to six cycles of adriamycin, bleomycin, vinblastine, and dacarbazine [ABVD] before radiation treatment). Contouring and treatment planning were performed with Somavision and CadPlan Helios (Varian Systems, Palo Alto, CA). The gross tumor volume was determined according to the prechemotherapy length and the postchemotherapy width of the mediastinal tumor mass. A 10-mm isotropic margin was added for the planning target volume (PTV). Because dose constraints assigned to OARs led to unsatisfactory PTV coverage, VVs were designed for each patient to protect adjacent OARs. The prescribed dose was 40 Gy to the PTV, delivered according to guidelines from International Commission on Radiation Units and Measurements Report No. 50. Five different IMRT treatment plans were compared with conventional treatment and 3D-CRT.

RESULTS

Beam orientation was important with respect to the amount of irradiated normal tissues. The best compromise in terms of PTV coverage and protection of normal tissues was obtained with five equally spaced beams (5FEQ IMRT plan) using dose constraints assigned to VVs. When IMRT treatment plans were compared with conventional treatment and 3D-CRT, dose conformation with IMRT was significantly better, with greater protection of the heart, coronary arteries, esophagus, and spinal cord. The lungs and breasts in women received a slightly higher radiation dose with IMRT compared with conventional treatments. The greater volume of normal tissue receiving low radiation doses could be a cause for concern.

CONCLUSIONS

The 5FEQ IMRT plan with dose constraints assigned to the PTV and VV allows better dose conformation than conventional treatment and 3D-CRT, notably with better protection of the heart and coronary arteries. Of concern is the "spreading out" of low doses to the rest of the patient's body.

Preliminary report of the 6-minute walk test as a predictor of radiation-induced pulmonary toxicity

PURPOSE

To assess the 6-minute walk test (6MWT) as a predictor of radiation therapy-induced lung injury (RTLI).

METHODS AND MATERIALS

The 6MWT is a simple, economical, and reproducible test that measures both how far a person can walk in 6 min and any associated changes in vital signs. As part of a prospective trial to study RTLI, a pre-RT 6MWT was performed in 41 patients. The predictive capacities of pre-RT 6MWT, forced expiratory volume in 1 s (FEV1), and single-breath diffusing capacity for carbon monoxide (DLCO) for the development of RTLI were assessed with receiver operating curve (ROC) techniques. To evaluate the 6MWT, alone or with mean lung dose (MLD) of radiation, as a predictor of RTLI, the rates of RTLI in patient subgroups defined by 6MWT results were compared by using Fisher's exact test.

RESULTS

Thirty-one patients with > or =3 months' follow-up were evaluable. The median baseline 6MWT result was 1400 ft. Of 31 patients, 7 developed Grade > or =2 RTLI. Of 15 patients with an MLD >18 Gy (the median), 5 developed RTLI, compared with 2 of 16 with MLD < or =18 Gy (p = 0.22). Among those with an MLD < or =18 Gy, the RTLI rates were 0 of 8 and 2 of 8 for 6MWT results > or =1400 ft or <1400 ft, respectively, p = 0.46. The ROC area under the curve for individual metrics was as follows: FEV1 0.66, MLD 0.70, DLCO 0.61, and 6MWT 0.47. Combining FEV1 with 6MWT increased the ROC to 0.71, suggesting that the ratio might be a better predictor than the individual values. Patients with a high 6MWT/FEV1 ratio had a lower rate of RTLI than those with a relatively low ratio.

CONCLUSIONS

The 6MWT might provide prognostic information beyond pulmonary function tests and dosimetric parameters in predicting RTLI. Additional work is needed to better assess the utility of these functional metrics.

Challenges in defining radiation pneumonitis in patients with lung cancer

PURPOSE

To assess the difficulty of assigning a definitive clinical diagnosis of radiation (RT)-induced lung injury in patients irradiated for lung cancer.

METHODS

Between 1991 and 2003, 318 patients were enrolled in a prospective study to evaluate RT-induced lung injury. Only patients with lung cancer who had a longer than 6-month follow-up (251 patients) were considered in the current analysis. Of these, 47 of 251 patients had Grade >/=2 (treated with steroids) increasing shortness of breath after RT, thought possibly consistent with pneumonitis/fibrosis. The treating physician, and one to three additional reviewing physicians, evaluated the patients or their medical records, or both. The presence or absence of confounding clinical factors that made the diagnosis of RT-induced uncertain lung injury were recorded.

RESULTS

Thirty-one of 47 patients (66%) with shortness of breath had "classic" pneumonitis, i.e., they responded to steroids and had a definitive diagnosis of pneumonitis. In 13 of 47 patients (28%), the diagnosis of RT-induced toxicity was confounded by possible infection; exacerbation of preexisting lung disease (chronic obstructive pulmonary disease); tumor regrowth/progression; and cardiac disease in 6, 8, 5, and 1 patients, respectively (some of the patients had multiple confounding factors and were counted more than once). An additional 3 patients (6%) had progressive shortness of breath and an overall clinical course more consistent with fibrosis. All 3 had evidence of bronchial stenosis by bronchoscopy.

CONCLUSIONS

Scoring of radiation pneumonitis was challenging in 28% of patients treated for lung cancer owing to confounding medical conditions. Recognition of this uncertainty is needed and may limit our ability to understand RT-induced lung injury.

Correlation of dosimetric factors and radiation pneumonitis for non-small-cell lung cancer patients in a recently completed dose escalation study

PURPOSE

To determine dosimetric factors for lung, lung subregions, and heart that correlate with radiation pneumonitis (Radiation Therapy Oncology Group Grade 3 or more) in the 78 evaluable patients from a Phase I dose escalation study (1991-2003) of three-dimensional conformal radiation therapy (3D-CRT) of non-small-cell lung cancer.

METHODS AND MATERIALS

There were 10 > or = Grade 3 pneumonitis cases within 6 months after treatment. Dose-volume factors analyzed for univariate correlation with > or = Grade 3 pneumonitis were mean dose (MD), effective uniform dose (d(eff)), normal tissue complication probability (NTCP), parallel model f(dam) and V(D) for 5 < or = D < or = 60 Gy for whole, ipsilateral, contralateral, upper and lower halves of the lungs and heart D05, and mean and maximum doses.

RESULTS

The most significant variables (0.005 < p < 0.006) were ipsilateral lung V(D) for D < 20 Gy. Also significant (p < 0.05) for ipsilateral lung were V(D) for D < 50 Gy, MD, f(dam) and d(eff); for total lung V(D) (D < 50 Gy), MD, f(dam), d(eff) and NTCP; for lower lung V(D) (D < 60 Gy), MD, f(dam) and d(eff). All variables for upper and contralateral lung were insignificant, as were heart variables.

CONCLUSIONS

Previously reported correlations between severe pneumonitis and whole lung V13 and with other dose-volume factors of total lung and lower lung are confirmed. The most significant correlations were for (V05-V13) in ipsilateral lung.

Nonsurgical Therapy for Stages I and II Non–Small Cell Lung Cancer

For patients who have stages I and II non-small cell lung cancer (NSCLC) and who are unable or unwilling to undergo surgical resection, nonsurgical treatment modalities have been used with curative intent. Conventionally fractionated radiotherapy has been the mainstay of nonsurgical therapy; however, advances in technology and the clinical application of radiobiologic principles have allowed more accurately targeted treatment that delivers higher effective doses to the tumor, while respecting the tolerance of surrounding normal tissues. This article discusses nonsurgical approaches to the treatment of early-stage NSCLC, including several promising techniques, such as radiation dose escalation, altered radiation fractionation, stereotactic radiotherapy, and radiofrequency ablation.

Can the use of amifostine improve cure rates for patients with advanced non-small cell lung cancer?

Concurrent chemoradiation, probably plus systemic chemotherapy, currently offers the best treatment strategy in stage IIIA/IIIB non-small cell lung cancer. However, such approaches do not control local disease well, perhaps because of inadequate radiation dose. While few studies have explored higher than standard radiation doses (ie, 60 Gy), the major fear is that higher doses increase patient morbidity without improving cure rates. A University of North Carolina (Chapel Hill, NC) phase I/II trial suggests that at least 74 Gy can be given safely to patients with cytotoxic drugs, with a suggestion of improved survival. Moreover, other trial data have suggested that the cytoprotective and radioprotective agent amifostine can be used to reduce esophagitis and possibly pneumonitis in patients treated with conventional radiation doses. We describe herein a proposed clinical trial designed to test: (1) the hypothesis that higher radiation doses can lead to a survival advantage in patients with non-small cell lung cancer, and (2) the value of amifostine as a cytoprotective agent in the high-radiation dose range.

Dose-volumetric parameters for predicting severe radiation pneumonitis after three-dimensional conformal radiation therapy for lung cancer

PURPOSE

To retrospectively evaluate dose-volumetric parameters for association with risk of severe (grade >/=3) radiation pneumonitis (RP) in patients after three-dimensional (3D) conformal radiation therapy for lung cancer.

MATERIALS AND METHODS

The study was approved by the institutional review board, which did not require informed consent. Data from 76 patients (66 men, 10 women; median age, 60 years; range, 35-79 years) with histologically proved lung cancer treated curatively with 3D conformal radiation therapy between August 2001 and October 2002 were retrospectively analyzed. Twenty patients underwent surgery before radiation therapy; 57 patients received chemotherapy. Median total radiation dose of 60 Gy (range, 54-66 Gy) was delivered in 30 (range, 27-33) fractions over 6 weeks. RP was scored by using Radiation Therapy Oncology Group criteria. Clinical parameters were analyzed. Dose-volumetric parameters analyzed were percentage of lung volume that received a dose of 20 Gy or more (V20), 30 Gy or more (V30), 40 Gy or more (V40), or 50 Gy or more (V50); mean lung dose (MLD); normal tissue complication probability (NTCP); and total dose. Fisher exact test was performed to compare clinical parameters between patients who developed severe RP and those who did not. Univariate and multivariate logistic regression analyses were performed to evaluate data for association between dose-volumetric parameters and severe RP. Pearson chi(2) test was used to assess data for correlations among dose-volumetric parameters. P < or = .05 was considered to indicate statistically significant difference.

RESULTS

Of 76 patients, 30 (39%) did not develop RP; 23 (30%) developed RP of grade 1; 11 (14%), grade 2; 11 (14%), grade 3; and 1 (1%), grade 4. None had grade 5 RP. Age (< 60 vs > or =60), sex, Karnofsky performance status (< 70 vs > or =70), forced expiratory volume in 1 second, presence of weight loss, preexisting lung disease, history of thoracic surgery, and history of chemotherapy did not significantly differ between patients who developed severe RP and those who did not. In univariate analyses, MLD, V20, V30, V40, V50, and NTCP were associated with severe RP (P < .05). In multivariate analysis, MLD was the only variable associated with severe RP.

CONCLUSION

MLD is a useful indicator of risk for development of severe RP after 3D conformal radiation therapy in patients with lung cancer.

An artificial neural network for predicting the incidence of radiation pneumonitis

A method to predict radiation-induced pneumonitis (RP) using an artificial neural network (ANN) was investigated. A retrospective study was applied to the clinical data from 142 patients who have been treated with three-dimensional conformal radiotherapy for tumors in the thoracic region. These data were classified, based on their treatment outcome, into two patient clusters: with RP (Np=26) and without RP (Np= 116). An ANN was designed as a classifier. To perform the classification, a patient-treatment outcome with RP was assigned a value of 1, and a patient treatment outcome without RP was assigned a value of -1. The input of the ANN was limited to the patient lung dose-volume data only. A volume vector (VD) that describes patient lung subvolumes receiving more than a set of threshold doses was used as the network input variable. A zero value was used as the threshold to set the output value into -1 or 1. Three ANNs (ANN_1, ANN_2, and ANN_3), each with three layers, were trained to perform this classification function and to show the effect of training data on the ANN performance. Radial basis function was applied as the hidden layer neuron activation function and a sigmoid function was selected as the output layer neuron function. Backpropagation with a conjugate gradient algorithm was used to train the network. ANN_1 was trained and tested by using the leave-one-out method. ANN_2 was trained by randomly selecting 2/3 of the patient data, and tested by the remaining 1/3 of the data. ANN_3 was trained by a user selecting 2/3 of the patient data, and tested by the remaining 1/3 of the data. The predictive accuracy was verified as the area under a receiver operator characteristic (ROC) curve. The correct classification rates of 73% for RP cases, and 99% for non-RP cases were obtained from ANN_1. The corresponding correct classification rates of 44% for RP cases, and 89% for non-RP cases were obtained from ANN_2. From the ANN_3 test phase, the corresponding correct classification rates of 55% for RP cases, and 95% non-RP cases were achieved. The area under ROC curve was 0.85+/-0.05, 0.68+/-0.10, and 0.81+/-0.09 for ANN_1, ANN _2, and ANN_3, respectively, within its asymmetric 95% confidence interval. The sensitivity was 95%, 57%, and 71%, and the specificity was 94%, 88%, and 90% for ANN_1, ANN_2, and ANN_3, respectively. Preliminary results suggest that the ANN approach provides a useful tool for the prediction of radiation-induced lung pneumonitis, using the patient lung dose-volume information.

Regional differences in lung radiosensitivity after radiotherapy for non-small-cell lung cancer

PURPOSE

To study regional differences in lung radiosensitivity by evaluating the incidence of radiation pneumonitis (RP) in relation to regional dose distributions.

METHODS AND MATERIALS

Registered chest CT and single photon emission CT lung perfusion scans were obtained in 106 patients before curative or radical radiotherapy for non-small-cell lung cancer. The mean lung dose (MLD) was calculated. The single photon-emission CT perfusion data were used to weigh the MLD with perfusion, resulting in the mean perfusion-weighted lung dose. In addition, the lungs were geometrically divided into different subvolumes. The mean regional dose (MRD) for each region was calculated and weighted with the perfusion of each region to obtain the mean perfusion-weighted regional dose. RP was defined as respiratory symptoms requiring steroids. The incidence of RP for patients with tumors in a specific subvolume was calculated. The normal tissue complication probability (NTCP) parameter values for the TD(50), and an offset NTCP parameter for tumor location were fitted for both lungs and for each lung subvolume to the observed data using maximum likelihood analysis.

RESULTS

The incidence of RP correlated significantly with the MLD and MRD of the posterior, caudal, ipsilateral, central, and peripheral lung subvolumes (p between 0.05 and 0.002); no correlation was seen for the anterior, cranial, and contralateral regions Similarly, a statistically significant correlation was observed between the incidence of RP and the perfusion-weighted MLD and perfusion-weighted MRD for all regions, except the anterior lung region. For this region, the dose-effect relation improved remarkably after weighting the local dose with the local perfusion. A statistically significant difference (p = 0.01) in the incidence of RP was found between patients with cranial and caudal tumors (11% and 40%, respectively). Therefore, a dose-independent offset NTCP parameter for caudal tumors was included in the NTCP model, improving most correlations significantly, confirming that patients with caudal tumors have a greater probability of developing RP.

CONCLUSION

The incidence of RP correlated significantly with the MLD and MRD of most lung regions, except for the anterior, cranial, and contralateral regions. Weighting the local dose with the local perfusion improved the dose-effect relation for the anterior lung region. Irradiation of caudally located lung tumors resulted in a greater risk of RP than irradiation of tumors located in other parts of the lungs.

Carboplatin/Paclitaxel or Carboplatin/Vinorelbine Followed by Accelerated Hyperfractionated Conformal Radiation Therapy: Report of a Prospective Phase I Dose Escalation Trial From the Carolina Conformal Therapy Consortium

Purpose

To prospectively determine the maximum-tolerated dose of accelerated hyperfractionated conformal radiotherapy (RT; 1.6 Gy bid) for unresectable locally advanced lung cancer (IIB to IIIA/B) following induction carboplatin/paclitaxel (C/T) or carboplatin/vinorelbine (C/N).

Methods

Induction chemotherapy, C/T or C/N, was followed by escalating doses of conformally-planned RT (73.6 to 86.4 Gy in 6.4-Gy increments). Concurrent boost methods delivered 1.6 and 1.25 Gy bid to the gross and clinical target volumes, respectively.

Results

Between November 1997 and February 2002, 44 patients were enrolled (median age, 59 years; 59% male; stage III, 98%; median tumor size, 4 cm). Thirty-nine patients completed induction chemotherapy: 19 had a partial response, seven progressed, 15 had no response, and three were not assessable. Chemotherapy-associated toxicities were similar in the two chemotherapy groups. The incidence of grade ≥ 3 RT-induced toxicity was 1/13, 2/14, and 4/12 at 73.6, 80, and 86.4 Gy, respectively, thus defining the maximum tolerated dose at ≈80 Gy. Toxicities were in both lung and esophagus and were similar in the two chemotherapy arms. With a median followup of 34 months in the survivors, the actuarial 2-year survival was 47%, the median survival was 18 months. Fifteen patients had tumor relapse: 5 local failures in the high-dose volume, 2 regional failures outside of the high-dose volume, and 8 distant metastases.

Conclusion

High-dose conformal twice-daily radiation therapy to approximately 80 Gy appears tolerable in well-selected patients with unresectable lung cancer following either C/T or C/N. Dose-limiting toxicities are mainly pulmonary and esophageal.

A feasibility study on the prediction of tumour location in the lung from skin motion

The system for predicting tumour location from skin motion induced by respiration was designed to reduce the effects of target movement. Fluoroscopic studies on 34 sites in the lungs and 14 sites in the diaphragm were performed so that the motions of skin markers and organs could be observed simultaneously. While patients were lying down in the simulator with radio-opaque markers on their skin, fluoroscopic images both in the anterior-posterior (AP) view and in the lateral view were sent to an analysing computer and recorded. The results that showed a strong correlation (0.77+/-0.12) between the patients' skin and tumour movement, especially for the sites located in the lower lung fields or in the diaphragm. With the prediction from skin motion, the uncertainties of the position of tumours due to respiratory movement could be reduced by up to 1.47 cm in the lower lung fields in the superior-inferior (SI) direction. This study revealed that it is possible to trace the exact location of tumours in the lungs by observing skin motion in most cases (up to 88%).

A modified technique for craniospinal irradiation in children designed to reduce acute and late radiation toxicity

Craniospinal irradiation is an important technique for the treatment of a number of paediatric malignancies. The conventional technique uses photons for all fields and does not exploit the benefits of CT and computer planning systems. The present paper describes a modification of the conventional technique in which both photons and electrons are used for the spinal field (mixed-beam technique). Computed tomography images and a planning computer are used for the selection of field junctions, electron beam energy and dosimetry. The intention of the technique is to reduce radiotherapy toxicity. A discussion of the potential benefits is presented.