Quantification of radiation-induced lung damage with CT scans: the possible benefit for radiogenomics

Predicting Radiation-Induced Lung Injury in Patients With Lung Cancer: Challenges and Opportunities

Radiation-induced lung injury (RILI) is one of the main dose-limiting toxicities in radiation therapy (RT) for lung cancer. Approximately 10% to 20% of patients show signs of RILI of variable severity. The reason for the wide range of RILI severity and the mechanisms underlying its development are only partially understood. A number of clinical risk factors have been identified that can aid in clinical decision making. Technological advancements in RT and the use of strict organ-at-risk dose constraints have helped to reduce RILI. Predicting patients at risk for RILI may be further improved with a combination of cytokine assessments, γH2AX-assays in leukocytes, or epigenetic markers. A complicating factor is the lack of an objective definition of RILI. Tools such as computed tomography densitometry, fluorodeoxyglucose-positron emission tomography uptake, changes in lung function measurements, and exhaled breath analysis can be implemented to better define and quantify RILI. This can aid in the search for new biomarkers, which can be accelerated by omics techniques, single-cell RNA sequencing, mass cytometry, and advances in patient-specific in vitro cell culture models. An objective quantification of RILI combined with these novel techniques can aid in the development of biomarkers to better predict patients at risk and allow personalized treatment decisions.

The Normal, the Radiosensitive, and the Ataxic in the Era of Precision Radiotherapy: A Narrative Review

(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after exposure to a dose that induces no toxicity in the general population. Diagnosing iRS before radiotherapy could avoid unnecessary toxicities in patients with a grossly normal phenotype. Thus, we reviewed iRS diagnostic data and their impact on decision-making processes and the RT workflow; (2) Methods: following a description of radiation toxicities, we conducted a critical review of the current state of the knowledge on individual determinants of cellular/tissue radiation; (3) Results: tremendous advances in technology now allow minimally-invasive genomic, epigenetic and functional testing and a better understanding of iRS. Ongoing large translational studies implement various tests and enriched NTCP models designed to improve the prediction of toxicities. iRS testing could better support informed radiotherapy decisions for individuals with a normal phenotype who experience unusual toxicities. Ethics of medical decisions with an accurate prediction of personalized radiotherapy's risk/benefits and its health economics impact are at stake; (4) Conclusions: iRS testing represents a critical unmet need to design personalized radiotherapy protocols relying on extended NTCP models integrating iRS.

Longitudinal analyses and predictive factors of radiation-induced lung toxicity-related parameters after stereotactic radiotherapy for lung cancer

BACKGROUND AND PURPOSE

The purpose of this prospective study was to investigate changes in longitudinal parameters after stereotactic radiotherapy for lung cancer and to identify possible pretreatment factors related to radiation-induced lung toxicity and the decline in pulmonary function after radiotherapy.

MATERIALS AND METHODS

Protocol-specified examinations, including 4-D CT, laboratory tests, pulmonary function tests (PFTs) and body composition measurements, were performed before SRT and at 1 month, 4 months and 12 months after stereotactic radiotherapy. Longitudinal differences were tested by using repeated-measures analysis of variance. Correlations were examined by using the Pearson product-moment correlation coefficient (r).

RESULTS

Sixteen patients were analyzed in this study. During a median follow-up period of 26.6 months, grade 1 and 2 lung toxicity occurred in 11 patients and 1 patient, respectively. The mean Hounsfield units (HU) and standard deviation (SD) of the whole lung, as well as sialylated carbohydrate antigen KL-6 (KL-6) and surfactant protein-D (SP-D), peaked at 4 months after radiotherapy (p = 0.11, p<0.01, p = 0.04 and p<0.01, respectively). At 4 months, lung V20 Gy (%) and V40 Gy (%) were correlated with changes in SP-D, whereas changes in the mean HU of the lung were related to body mass index and lean body mass index (r = 0.54, p = 0.02; r = 0.57, p = 0.01; r = 0.69, p<0.01; and r = 0.69, p<0.01, respectively). The parameters of PFTs gradually declined over time. When regarding the change in PFTs from pretreatment to 12 months, lung V5 Gy (cc) showed significant correlations with diffusion capacity for carbon monoxide (DLCO), DLCO/alveolar volume and the relative change in DLCO (r = -0.72, p<0.01; r = -0.73, p<0.01; and r = -0.63, p = 0.01, respectively).

CONCLUSIONS

The results indicated that some parameters peaked at 4 months, but PFTs were the lowest at 12 months. Significant correlations between lung V5 Gy (cc) and changes in DLCO and DLCO/alveolar volume were observed.

Quantitative Analysis of Radiation-Associated Parenchymal Lung Change

We present a novel classification system of the parenchymal features of radiation-induced lung damage (RILD). We developed a deep learning network to automate the delineation of five classes of parenchymal textures. We quantify the volumetric change in classes after radiotherapy in order to allow detailed, quantitative descriptions of the evolution of lung parenchyma up to 24 months after RT, and correlate these with radiotherapy dose and respiratory outcomes. Diagnostic CTs were available pre-RT, and at 3, 6, 12 and 24 months post-RT, for 46 subjects enrolled in a clinical trial of chemoradiotherapy for non-small cell lung cancer. All 230 CT scans were segmented using our network. The five parenchymal classes showed distinct temporal patterns. Moderate correlation was seen between change in tissue class volume and clinical and dosimetric parameters, e.g., the Pearson correlation coefficient was ≤0.49 between V30 and change in Class 2, and was 0.39 between change in Class 1 and decline in FVC. The effect of the local dose on tissue class revealed a strong dose-dependent relationship. Respiratory function measured by spirometry and MRC dyspnoea scores after radiotherapy correlated with the measured radiological RILD. We demonstrate the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible.

A novel lung-avoidance planning strategy based on 4DCT ventilation imaging and CT density characteristics for stage III non-small-cell lung cancer patients

BACKGROUND

Functional planning based merely on 4DCT ventilation imaging has limitations. In this study, we proposed a radiotherapy planning strategy based on 4DCT ventilation imaging and CT density characteristics.

MATERIALS AND METHODS

For 20 stage III non-small-cell lung cancer (NSCLC) patients, clinical plans and lung-avoidance plans were generated. Through deformable image registration (DIR) and quantitative image analysis, a 4DCT ventilation map was calculated. High-, medium-, and low-ventilation regions of the lung were defined based on the ventilation value. In addition, the total lung was also divided into high-, medium-, and low-density areas according to the HU threshold. The lung-avoidance plan aimed to reduce the dose to functional and high-density lungs while meeting standard target and critical structure constraints. Standard and dose-function metrics were compared between the clinical and lung-avoidance plans.

RESULTS

Lung avoidance plans led to significant reductions in high-function and high-density lung doses, without significantly increasing other organ at risk (OAR) doses, but at the expense of a significantly degraded homogeneity index (HI) and conformity index (CI; p < 0.05) of the planning target volume (PTV) and a slight increase in monitor units (MU) as well as in the number of segments (p > 0.05). Compared with the clinical plan, the mean lung dose (MLD) in the high-function and high-density areas was reduced by 0.59 Gy and 0.57 Gy, respectively.

CONCLUSION

A lung-avoidance plan based on 4DCT ventilation imaging and CT density characteristics is feasible and implementable, with potential clinical benefits. Clinical trials will be crucial to show the clinical relevance of this lung-avoidance planning strategy.

In Silico Ventilation Within the Dose-Volume is Predictive of Lung Function Post-radiation Therapy in Patients with Lung Cancer

Lung cancer is a leading cause of death worldwide. Radiation therapy (RT) is one method to treat this disease. A common side effect of RT for lung cancer is radiation-induced lung damage (RILD) which leads to loss of lung function. RILD often compounds pre-existing smoking-related regional lung function impairment. It is difficult to predict patient outcomes due to large variability in individual response to RT. In this study, the capability of image-based modelling of regional ventilation in lung cancer patients to predict lung function post-RT was investigated. Twenty-five patient-based models were created using CT images to define the airway geometry, size and location of tumour, and distribution of emphysema. Simulated ventilation within the 20 Gy isodose volume showed a statistically significant negative correlation with the change in forced expiratory volume in 1 s 12-months post-RT (p = 0.001, R = - 0.61). Patients with higher simulated ventilation within the 20 Gy isodose volume had a greater loss in lung function post-RT and vice versa. This relationship was only evident with the combined impact of tumour and emphysema, with the location of the emphysema relative to the dose-volume being important. Our results suggest that model-based ventilation measures can be used in the prediction of patient lung function post-RT.

The dose-response characteristics of four NTCP models: using a novel CT-based radiomic method to quantify radiation-induced lung density changes

Multiple competing normal tissue complication probability (NTCP) models have been proposed for predicting symptomatic radiation-induced lung injury in human. In this paper we tested the efficacy of four common NTCP models applied quantitatively to sub-clinical X-ray computed tomography (CT)-density changes in the lung following radiotherapy. Radiotherapy planning datasets and follow-up chest CTs were obtained in eight patients treated for targets within the lung or hilar region. Image pixel-wise radiation dose exposure versus change in observable CT Hounsfield units was recorded for early (2-5 months) and late (6-9 months) time-points. Four NTCP models, Lyman, Logistic, Weibull and Poisson, were fit to the population data. The quality of fits was assessed by five statistical criteria. All four models fit the data significantly (p < 0.05) well at early, late and cumulative time points. The Lyman model fitted best for early effects while the Weibull Model fitted best for late effects. No significant difference was found between the fits of the models and with respect to parameters D₅₀ and γ₅₀. The D₅₀ estimates were more robust than γ₅₀ to image registration error. For analyzing population-based sub-clinical CT pixel intensity-based dose response, all four models performed well.

Regional lung avoidance by CT numbers to reduce radiation-induced lung damage risk in non-small-cell lung cancer: a simulation study

Background: Selective avoidance aims at sparing functional lung regions. Here, we preferentially direct radiation to irreversibly nonfunctional lung areas based on planning CT imaging to reduce functional lung damage.Materials and methods: For 12 stage I-IV NSCLC patients, 5 lung substructures were segmented on the planning CT, combining voxels <-900HU, -900HU to -801HU, -800HU to -701HU, -700HU to -601HU and ≥-600HU (Level 1 to 5). Two VMAT plans were optimized: a reference plan blinded from substructures and a selective avoidance plan (AV) imposing gradually stricter constraints on Level 1-5, based on previously validated associations between lung subvolume baseline density and density increase (ΔHU) after treatment. Characteristics of treatment plans were evaluated, including subvolumes, dose, and predicted ΔHU (with reported 95% CI reflecting prediction model uncertainty).Results: Segmented substructures were on average 477 cc, 1157 cc, 484 cc, 69 cc, and 123 cc (Level 1-5). AV plans could spare Level 3-5, e.g., mean dose decrease of 3.5 Gy (range 0.6 Gy; 6.0 Gy) for Level 5, p<.001. This significantly reduced the average lung mass with predicted ΔHU>20HU by 12.5 g (95% CI: 5.4-16.9) and 27.1 g (95% CI: 10.2-32.9) for a median and upper 10th percentile patient susceptibility for damage simulation, respectively.Conclusions: Lung damage avoidance based on CT density is feasible and easy to implement. A biomarker providing a reliable selection of patients with high susceptibility for lung damage will be crucial to show the clinical relevance of this avoidance planning strategy.

Assessing EGFR gene mutation status in non-small cell lung cancer with imaging features from PET/CT

OBJECTIVE

The aim of this study was to investigate whether quantitative and qualitative features extracted from PET/computed tomography (CT) can be used as imaging biomarkers for evaluating epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer patients.

METHODS

Eighty patients with stage II and III non-small cell lung cancer from January 2017 to December 2017 were included in this study. All patients underwent PET/CT examination before operation. Patients with 30 EGFR positive and 50 EGFR negative were confirmed by pathological verification and gene detection. Least absolute shrinkage and selection operator was used for analysis and selection of imaging features. Support vector machine was used to classify EGFR positive/negative using the selected features. Ten-fold cross validation was used to estimate the accuracy.

RESULTS

A total of 512 quantitative features (radiomic features) were extracted from PET/CT (256 for PET and 256 for CT), and 12 qualitative features (semantic features) were extracted from CT. A total of 35 features were finally retained after least absolute shrinkage and selection operator (31 quantitative features and 4 qualitative features). The 35 selected features were significantly associated with EGFR mutation status. A predictive model was built using PET/CT data. Its performance was revealed as 0.953 using the area under the receiver operating characteristic curve.

CONCLUSION

A predictive model using PET/CT images might be used to detect EGFR mutation status in non-small cell lung cancer patients.

Four-dimensional computed tomography-based biomechanical measurements of pulmonary function and their correlation with clinical outcome for lung stereotactic body radiation therapy patients

BACKGROUND

Functional image guided radiotherapy allows for the delivery of an equivalent dose to tumor targets while sparing high ventilation lung tissues. In this study, we investigate whether radiation dose to functional lung is associated with clinical outcome for stereotactic body radiation therapy (SBRT) patients.

METHODS

Four-dimensional computed tomography (4DCT) images were used to assess lung function. Deformable image registration (DIR) was performed from the end-inhale phase to the end-exhale phase with resultant displacement vectors used to calculate ventilation maps. In addition to the Jacobian-based ventilation we introduce a volumetric variation method (Rv) based on a biomechanical finite element method (FEM), to assess lung ventilation. Thirty NSCLC patients, treated with SBRT, were evaluated in this study. 4DCT images were used to calculate both Jacobian and Rv-based ventilation images. Areas under the receiver operating characteristic curve (AUC) were used to assess the predictive power of functional metrics. Metrics were calculated over the whole lung as well as high and low ventilated regions.

RESULTS

Ventilation in dose regions between 1 and 5 Gy had higher AUC values compared to other dose regions. Rv based ventilation imaging method also showed to be less spatially variant and less heterogeneous, and the resultant Rv metrics had higher AUC values for predicting grade 2+ dyspnea.

CONCLUSIONS

Low dose delivered to high ventilation areas may also increase the risk of compromised pulmonary function. Rv based ventilation images could be useful for the prediction of clinical toxicity for lung SBRT patients.

Changes of lung parenchyma density following high dose radiation therapy for thoracic carcinomas - an automated analysis of follow up CT scans

Background

An objective way to qualify the effect of radiotherapy (RT) on lung tissue is the analysis of CT scans after RT. In this analysis we focused on the changes in Hounsfield units (ΔHU) and the correlation with the corresponding radiation dose after RT.

Methods

Pre- and post-RT CT scans were matched and ΔHU was calculated using customized research software. ΔHU was calculated in 5-Gy-intervals and the correlation between ΔHU and the corresponding dose was calculated as well as the regression coefficients. Additionally the mean ΔHU and ΔHU in 5-Gy-intervals were calculated for each tumor entity.

Results

The mean density changes at 12 weeks and 6 months post RT were 28,16 HU and 32,83 HU. The correlation coefficient between radiation dose and ΔHU at 12 weeks and 6 months were 0,166 (p = 0,000) and 0,158 (p = 0,000). The resulting regression coefficient were 1439 HU/Gy (p = 0,000) and 1612 HU/Gy (p = 0,000). The individual regression coefficients for each patient range from − 2,23 HU/Gy to 7,46 HU/Gy at 12 weeks and − 0,45 HU/Gy to 10,51 HU/Gy at 6 months. When looking at the three tumor entities individually the highest ΔHU at 12 weeks was seen in patients with SCLC (38,13 HU) and at 6 month in those with esophageal carcinomas (40,98 HU).

Conclusion

For most dose intervals there was an increase of ΔHU with an increased radiation dose. This is reflected by a statistically significant, although low correlation coefficient. The regression coefficients of all patients show large interindividual differences.

4-Dimensional computed tomography-based ventilation and compliance images for quantification of radiation-induced changes in pulmonary function

INTRODUCTION

4-Dimensional computed tomography (4DCT)-based ventilation imaging is a promising technique for evaluating pulmonary function, but lung elasticity and mechanics are usually not part of the ventilation image analysis. In this study we demonstrate a 4DCT-based imaging technique that can be used to calculate regional lung compliance changes after radiotherapy (RT).

METHODS

Six lung cancer patients were included in this study. Four of the patients had 4DCT images acquired pre-RT, 3 and 9 months post-RT. Ventilation and compliance were calculated from the deformable image registration (DIR) of 4DCTs, performed from the end-inhale to the end-exhale breathing phase. Regional compliance was defined as the ratio of volumetric variation and associated stress in each voxel, representing lung elasticity and computed using a FEM-based framework. Ventilation, compliance and CT density were calculated for all pre-RT and post-RT 4DCTs and evaluation metrics were computed.

RESULTS

Average CT density changes were 13.6 ± 11.4HU after 3 months and 26.9 ± 15.8HU after 9 months. Ventilation was reduced at 3 months, but improved at 9 months in regions with dose ≥ 35 Gy, encompassing about 10% of the lung volume; compliance was reduced at both time-points. Radiation dose ≥ 35 Gy caused major change in lung density and ventilation, which was higher than that previously reported in the literature (i.e. 24 Gy).

CONCLUSION

Lung tissue response is diverse with respect to CT density, ventilation and compliance. Combination of ventilation and compliance with CT density could be beneficial for understanding radiation-induced lung damage and consequently could help develop improved treatment protocols for lung cancer patients.

Radiotherapy toxicity

Radiotherapy is used in >50% of patients with cancer, both for curative and palliative purposes. Radiotherapy uses ionizing radiation to target and kill tumour tissue, but normal tissue can also be damaged, leading to toxicity. Modern and precise radiotherapy techniques, such as intensity-modulated radiotherapy, may prevent toxicity, but some patients still experience adverse effects. The physiopathology of toxicity is dependent on many parameters, such as the location of irradiation or the functional status of organs at risk. Knowledge of the mechanisms leads to a more rational approach for controlling radiotherapy toxicity, which may result in improved symptom control and quality of life for patients. This improved quality of life is particularly important in paediatric patients, who may live for many years with the long-term effects of radiotherapy. Notably, signs and symptoms occurring after radiotherapy may not be due to the treatment but to an exacerbation of existing conditions or to the development of new diseases. Although differential diagnosis may be difficult, it has important consequences for patients.

Detection of Calcified Aortic Plaques in an Apolipoprotein E Animal Model Using a Human Computed Tomography System for Ultra-High-resolution Imaging: A Feasibility Study

PURPOSE

The purpose of this study was to prospectively evaluate the feasibility of detecting calcified aortic plaques in apolipoprotein E knockout (ApoE-KO) mice using a state-of-the-art human computed tomography (CT) system.

MATERIALS AND METHODS

Eleven ApoE-KO and 9 wild-type mice, all male, were examined in this study. After intraperitoneal injection of 6.6% ketamine all mice underwent 2 ultra-high-resolution CT protocols on a third-generation dual-source CT system at 120 kVp and 130 kVp tube voltage, both performed with a tube current time product of 1300 mAs. Images (0.4 mm) with an increment of 0.2 mm were reconstructed using an iterative reconstruction algorithm. Calcium detectability and scores (Agatston, volume, mass) were determined with a dedicated human calcium scoring software (CaScoring). After the CT examination, a calcium quantification assay of the aortae was performed to determine the aortic calcium content of each mouse. The CT scan time ranged between 40 and 48 seconds. All mice survived the procedure.

RESULTS

Calcified plaques could be detected in 8 of 11 ApoE-KO mice. Quantification of calcium levels showed significant differences between those with morphologic calcium plaques detected in CT and those without (3.44±1.6 μg Ca/mg vs. 0.33±0.35 μg Ca/mg; P<0.05). The receiver-operating characteristics analysis revealed a total calcium cut-off value of 0.71 μg Ca/mg for the detection using calcium score algorithms (specificity: 100% and sensitivity: 90%).

CONCLUSION

Using a state-of-the-art human CT protocol and an in-human-established calcium scoring system allows for the detection and quantification of calcified aortic plaques in ApoE-KO mice. These results may facilitate preclinical imaging for translational and longitudinal atherosclerotic research studies.

Novel CT-Based Objective Imaging Biomarkers of Long-Term Radiation-Induced Lung Damage

PURPOSE

Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long-term radiation-induced lung damage (RILD). However, there are still no objective criteria to quantify RILD, leading to variable reporting across centers and trials. We propose a set of objective imaging biomarkers for quantifying common radiologic findings observed 12 months after lung cancer radiation therapy.

METHODS AND MATERIALS

Baseline and 12-month computed tomography (CT) scans of 27 patients from a phase 1/2 clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, 12 quantitative imaging biomarkers were developed. The biomarkers describe basic CT findings, including parenchymal change, volume reduction, and pleural change. The imaging biomarkers were implemented as semiautomated image analysis pipelines and were assessed against visual assessment of the occurrence of each change.

RESULTS

Most of the biomarkers were measurable in each patient. The continuous nature of the biomarkers allows objective scoring of severity for each patient. For each imaging biomarker, the cohort was split into 2 groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in the 2 groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. Most of the biomarkers were not strongly correlated with each other, suggesting that each of the biomarkers is measuring a separate element of RILD pathology.

CONCLUSIONS

We developed objective CT-based imaging biomarkers that quantify the severity of radiologic lung damage after radiation therapy. These biomarkers are representative of typical radiologic findings of RILD.

Radiation-Induced Lung Density Changes on CT Scan for NSCLC: No Impact of Dose-Escalation Level or Volume

PURPOSE

Dose-escalation for patients with non-small cell lung cancer (NSCLC) in the positron emission tomography (PET)-boost trial (NCT01024829) exposes portions of normal lung tissue to high radiation doses. The relationship between lung parenchyma dose and density changes on computed tomography (CT) was analyzed.

MATERIALS AND METHODS

The CT scans of 59 patients with stage IB to III NSCLC, randomized between a boost to the whole primary tumor and an integrated boost to its 50% SUVmax (maximum standardized uptake value) volume. Patients were treated with concurrent or sequential chemoradiation or radiation only. Deformable registration mapped the 3-month follow-up CT to the planning CT. Hounsfield unit differences (ΔHU) were extracted to assess lung parenchyma density changes. Equivalent dose in 2 Gy fractions (EQD2)-ΔHU response was described sigmoidally, and regional response variation was studied by polar analysis. Prognostic factors of ΔHU were obtained through generalized linear modeling.

RESULTS

Saturation of ΔHU was observed above 60 Gy. No interaction was found between boost dose distribution (D_1cc and V_70Gy) and ΔHU at lower doses. ΔHU was lowest peripherally from the tumor and peaked posteriorly at 3 cm from the tumor border (3.1 HU/Gy). Right lung location was an independent risk factor for ΔHU (P = .02).

CONCLUSIONS

No apparent increase of lung density changes at 3-month follow-up was observed above 60 Gy EQD2 for patients with NSCLC treated with (concurrent or sequential chemo) radiation. The mild response observed peripherally in the lung parenchyma might be exploited in plan optimization routines minimizing lung damage.

Asymptomatic Late-phase Radiographic Changes Among Chest-Wall Patients Are Associated With a Proton RBE Exceeding 1.1

PURPOSE

Clinical practice assumes a fixed proton relative biological effectiveness (RBE) of 1.1, but in vitro experiments demonstrate higher RBEs at the distal edge of the proton spread-out Bragg peak, that is, in a region that falls within the lung for chest-wall patients. We performed retrospective qualitative and quantitative analyses of lung-density changes-indicative of asymptomatic fibrosis-for chest-wall patients treated with protons or photons. Our null hypothesis was that, assuming a fixed RBE of 1.1, these changes would be the same for the 2 cohorts, supporting current RBE practice. Our alternative hypothesis was that radiographic abnormalities would be greater for the proton cohort, suggesting an RBE > 1.1.

METHODS AND MATERIALS

We analyzed follow-up computed tomography (CT) scans for 20 proton and photon patients. All were prescribed 50.4 Gy (RBE) in 28 fractions, assuming a fixed RBE of 1.1 for protons and 1 for photons. Deformable registrations enabled us to calculate density changes in the normal lung, specifically (1) median Hounsfield unit (HU) values among posttreatment CT scans and (2) changes in median HU values between pretreatment and posttreatment CT scans, both as a function of grays (RBE). In addition, qualitative abnormality grading was performed by a radiologist.

RESULTS

Proton patients exhibited higher values of HU/Gy (RBE) (endpoint 1) and ΔHU/Gy (RBE) (endpoint 2): P = .049 and P = .00019, respectively, were obtained (likelihood ratio tests of full linear mixed-effects models against models without "modality"). Furthermore, qualitative radiologic scoring indicated a significant difference between the cohorts (Wilcoxon P = .018; median score, 3 of 9 for protons and 1.5 of 9 for photons).

CONCLUSIONS

Our data support the hypothesis that the proton RBE for lung-density changes exceeds 1.1. This RBE elevation could be attributable to (1) the late, normal tissue endpoint that we consider or (2) end-of-range proton linear energy transfer elevation-or a combination of the two. Regardless, our results suggest that variations in proton RBE prove important in vivo as well as in vitro.

Long term radiological features of radiation-induced lung damage

PURPOSE

To describe the radiological findings of radiation-induced lung damage (RILD) present on CT imaging of lung cancer patients 12 months after radical chemoradiation.

MATERIAL AND METHODS

Baseline and 12-month CT scans of 33 patients were reviewed from a phase I/II clinical trial of isotoxic chemoradiation (IDEAL CRT). CT findings were scored in three categories derived from eleven sub-categories: (1) parenchymal change, defined as the presence of consolidation, ground-glass opacities (GGOs), traction bronchiectasis and/or reticulation; (2) lung volume reduction, identified through reduction in lung height and/or distortions in fissures, diaphragm, anterior junction line and major airways anatomy, and (3) pleural changes, either thickening and/or effusion.

RESULTS

Six patients were excluded from the analysis due to anatomical changes caused by partial lung collapse and abscess. All remaining 27 patients had radiological evidence of lung damage. The three categories, parenchymal change, shrinkage and pleural change were present in 100%, 96% and 82% respectively. All patients had at least two categories of change present and 72% all three. GGOs, reticulation and traction bronchiectasis were present in 44%, 52% and 37% of patients.

CONCLUSIONS

Parenchymal change, lung shrinkage and pleural change are present in a high proportion of patients and are frequently identified in RILD. GGOs, reticulation and traction bronchiectasis are common at 12 months but not diagnostic.

The Value of CBCT-based Tumor Density and Volume Variations in Prediction of Early Response to Chemoradiation Therapy in Advanced NSCLC

The correlations between early responses and the variations in physical density and primary tumor volume (TV) according to cone-beam computed tomography (CBCT) during chemoradiotherapy for non-small cell lung cancer (NSCLC) patients were investigated. 54 patients with inoperable and locally advanced NSCLC were included in this study. The CT numbers (CTN) and TV were measured on each of the seven observation points. The changes in the mean CTN values and the variation ratios of TV during the treatment course were analysed and correlated with the clinical outcomes, as evaluated by the RECIST criteria. For patients who responded to treatment, the CTN and TV change ratio decreased by 28.44 ± 13.12 HU and 32.01% (range, 8.46-61.67%); these values were significantly higher than those in the non-responding patients, with 19.63 ± 8.67 HU and 23.20% (range, -15.57-38%) (p = 0.016, p = 0.048), respectively. The area under curve for the combination of CTN and TV was larger than either alone (AUC = 0.751, p = 0.002). The differences between response and non-response were most significant between Fraction 10 and Fraction 15 for CTN changes and between Fraction 5 and Fraction 10 for the TV regression ratio. The changes in CTN and TV obtained from CBCT images have the potential capability to predict an early response of NSCLC.

Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study

Purpose

In an effort for early assessment of treatment response, we investigate radiation induced changes in quantitative CT features of tumor during the delivery of chemoradiation therapy (CRT) for pancreatic cancer.

Methods

Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. On each daily CT, the pancreatic head, the spinal cord and the aorta were delineated and the histograms of CT number (CTN) in these contours were extracted. Eight histogram-based radiomic metrics including the mean CTN (MCTN), peak position, volume, standard deviation (SD), skewness, kurtosis, energy and entropy were calculated for each fraction. Paired t-test was used to check the significance of the change of specific metric at specific time. GEE model was used to test the association between changes of metrics over time for different pathology responses.

Results

In general, CTN histogram in the pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the 1^st to the 26^th fraction in MCTN ranged from -15.8 to 3.9 HU with an average of -4.7 HU (p<0.001). Meanwhile the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less peaked). The changes of MCTN, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response is associated with the changes of MCTN, SD, and skewness. In cases of good response, patients tend to have large reductions in MCTN and skewness, and large increases in SD and kurtosis.

Conclusions

Significant changes in CT radiomic features, such as the MCTN, skewness, and kurtosis in tumor were observed during the course of CRT for pancreas cancer based on quantitative analysis of daily CTs. These changes may be potentially used for early assessment of treatment response and stratification for therapeutic intensification.

Extent and computed tomography appearance of early radiation induced lung injury for non-small cell lung cancer

BACKGROUND AND PURPOSE

The present study investigates the extent and appearance of radiologic injury in the lung after radiotherapy for non-small cell lung cancer (NSCLC) patients and correlates radiologic response with clinical and dosimetric factors.

METHODS AND MATERIALS

Eligible follow-up CT scans acquired up to six months after radiotherapy were evaluated for radiologic injuries in 220 NSCLC patients. Radiologic injuries were divided into three categories: (1) interstitial changes, (2) ground-glass opacity, or (3) consolidation. The relationship between the fraction of injured lung of each category and clinical or dosimetric factors was investigated.

RESULTS

Radiological injuries of category 1-3 were found in 67%, 52%, and 51% of the patients, and the mean (and maximum) fraction of injured lung was 4.4% (85.9%), 2.4% (46.0%), and 2.1% (22.9%), respectively. Traditional lung dose metrics and time to follow-up predicted lung injury of all categories. Older age increased the risk of interstitial changes and current smoking reduced the risk of consolidation in the lung.

CONCLUSION

Radiologic injuries were frequently found in follow-up CT scans after radiotherapy for NSCLC patients. The risk of a radiologic response increased with increasing time and lung dose metrics, and depended on patient age and smoking status.

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography

PURPOSE

To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans.

METHODS AND MATERIALS

Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed.

RESULTS

During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R² > 0.99) and correlates weakly with the change in GTV (R² = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction.

CONCLUSION

Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.

Texture analysis of medical images for radiotherapy applications

The high-throughput extraction of quantitative information from medical images, known as radiomics, has grown in interest due to the current necessity to quantitatively characterize tumour heterogeneity. In this context, texture analysis, consisting of a variety of mathematical techniques that can describe the grey-level patterns of an image, plays an important role in assessing the spatial organization of different tissues and organs. For these reasons, the potentiality of texture analysis in the context of radiotherapy has been widely investigated in several studies, especially for the prediction of the treatment response of tumour and normal tissues. Nonetheless, many different factors can affect the robustness, reproducibility and reliability of textural features, thus limiting the impact of this technique. In this review, an overview of the most recent works that have applied texture analysis in the context of radiotherapy is presented, with particular focus on the assessment of tumour and tissue response to radiations. Preliminary, the main factors that have an influence on features estimation are discussed, highlighting the need of more standardized image acquisition and reconstruction protocols and more accurate methods for region of interest identification. Despite all these limitations, texture analysis is increasingly demonstrating its ability to improve the characterization of intratumour heterogeneity and the prediction of clinical outcome, although prospective studies and clinical trials are required to draw a more complete picture of the full potential of this technique.

Pulmonary imaging after stereotactic radiotherapy-does RECIST still apply?

The use of stereotactic ablative radiotherapy (SABR) for the treatment of primary lung cancer and metastatic disease is rapidly increasing. However, the presence of benign fibrotic changes on CT imaging makes response assessment following SABR a challenge, as these changes develop with an appearance similar to tumour recurrence. Misclassification of benign fibrosis as local recurrence has resulted in unnecessary interventions, including biopsy and surgical resection. Response evaluation criteria in solid tumours (RECIST) are widely used as a universal set of guidelines to assess tumour response following treatment. However, in the context of non-spherical and irregular post-SABR fibrotic changes, the RECIST criteria can have several limitations. Positron emission tomography can also play a role in response assessment following SABR; however, false-positive results in regions of inflammatory lung post-SABR can be a major clinical issue and optimal standardized uptake values to distinguish fibrosis and recurrence have not been determined. Although validated CT high-risk features show a high sensitivity and specificity for predicting recurrence, most recurrences are not detected until more than 1-year post-treatment. Advanced quantitative radiomic analysis on CT imaging has demonstrated promise in distinguishing benign fibrotic changes from local recurrence at earlier time points, and more accurately, than physician assessment. Overall, the use of RECIST alone may prove inferior to novel metrics of assessing response.

CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

BACKGROUND

Radiomics uses a large number of quantitative imaging features that describe the tumor phenotype to develop imaging biomarkers for clinical outcomes. Radiomic analysis of pre-treatment computed-tomography (CT) scans was investigated to identify imaging predictors of clinical outcomes in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT).

MATERIALS AND METHODS

CT images of 113 stage I-II NSCLC patients treated with SBRT were analyzed. Twelve radiomic features were selected based on stability and variance. The association of features with clinical outcomes and their prognostic value (using the concordance index (CI)) was evaluated. Radiomic features were compared with conventional imaging metrics (tumor volume and diameter) and clinical parameters.

RESULTS

Overall survival was associated with two conventional features (volume and diameter) and two radiomic features (LoG 3D run low gray level short run emphasis and stats median). One radiomic feature (Wavelet LLH stats range) was significantly prognostic for distant metastasis (CI=0.67, q-value<0.1), while none of the conventional and clinical parameters were. Three conventional and four radiomic features were prognostic for overall survival.

CONCLUSION

This exploratory analysis demonstrates that radiomic features have potential to be prognostic for some outcomes that conventional imaging metrics cannot predict in SBRT patients.

Radiation oncology in the era of precision medicine

Technological advances and clinical research over the past few decades have given radiation oncologists the capability to personalize treatments for accurate delivery of radiation dose based on clinical parameters and anatomical information. Eradication of gross and microscopic tumours with preservation of health-related quality of life can be achieved in many patients. Two major strategies, acting synergistically, will enable further widening of the therapeutic window of radiation oncology in the era of precision medicine: technology-driven improvement of treatment conformity, including advanced image guidance and particle therapy, and novel biological concepts for personalized treatment, including biomarker-guided prescription, combined treatment modalities and adaptation of treatment during its course.

Impact of single-nucleotide polymorphisms on radiation pneumonitis in cancer patients

Radiation pneumonitis (RP) is one of the most important dose-limiting toxicities in the radiotherapy of thoracic tumors, which reduces the rate of local tumor control and overall survival and severely affects the patients' quality of life. Single-nucleotide polymorphisms (SNPs) have recently attracted increasing attention as biomarkers for predicting the development of RP. SNPs in inflammation-related, DNA repair-related, stress response-related and angiogenesis-related genes were proved to be associated with RP, with different underlying mechanisms. Radiogenomics focuses on the differences in radiosensitivity caused by gene sequence variation, which may prove helpful in investigating the abovementioned associations. In this review, we aimed to investigate the associations between RP and SNPs reported in recent studies and highlight the main content and prospects of radiogenomics.

Should breathing adapted radiotherapy also be applied for right-sided breast irradiation?

BACKGROUND

Voluntary moderate deep inspiration breath-hold (vmDIBH) is widely used for left sided breast cancer patients. The purpose of this study was to investigate the usefulness of vmDIBH in local and locoregional radiation therapy (RT) of right-sided breast cancer.

MATERIALS AND METHODS

For fourteen right-sided breast cancer patients, 3D-conformal (3D-CRT) RT plans (i.e., forward IMRT) were calculated on free-breathing (FB) 3D-CRT(FB) and vmDIBHCT-scans, for local- as well as locoregional breast treatment, with and without internal mammary nodes (IMN). Dose volume parameters were compared.

RESULTS

For local breast treatment, no relevant reduction in mean lung dose (MLD) was found. For locoregional breast treatment without IMN, the average MLD reduced from 6.5 to 5.4 Gy (p < 0.005) for the total lung and from 11.2 to 9.7 Gy (p < 0.005) for the ipsilateral lung. For locoregional breast treatment with IMN, the average MLD reduced from 10.8 to 9.1 Gy (p < 0.005) for the total lung and from 18.7 to 16.2 Gy (p < 0.005) for the ipsilateral lung, whilea small reduction in mean heart dose of 0.4 Gy (p = 0.07) was also found.

CONCLUSIONS

Breathing adapted radiation therapy in left-sided breast cancer patients is becoming widely introduced. As a result of the slight reduction in lung dose found for locoregional right-sided breast cancer treatment in this study, a slightly lower risk of pneumonitis and secondary lung cancer (in ever smoking patients) can be expected.In addition, for some patients the heart dose will also be reduced by more than 0.5 up to 2.6 Gy. We therefore suggest to also apply breath-hold for locoregional irradiation of right-sided breast cancer patients.

Quantification of CT-assessed radiation-induced lung damage in lung cancer patients treated with or without chemotherapy and cetuximab

BACKGROUND AND PURPOSE

Prediction models for radiation-induced lung damage (RILD) are still unsatisfactory, with clinical toxicity endpoints that are difficult to quantify objectively. We therefore evaluated RILD more objectively, quantitatively and on a continuous scale measuring the lung tissue density changes per voxel.

MATERIAL AND METHODS

Patients treated with radiotherapy (RT) alone, sequential and concurrent chemo-RT with and without the addition of cetuximab were studied. Follow-up computed tomography (CT) scans were co-registered using deformable registration to baseline CT scans. CT density changes were correlated to the RT dose delivered in every part of the lungs.

RESULTS

One hundred and seventeen lung cancer patients were included. Mean dose to tumor was 60 Gy (range 45-79.2 Gy). Dose response curves showed a linear increase in the dose region between 0 and 65 Gy having a slope (based on coefficients of the multilevel model) expressed as a lung density increase per dose of 0.86 (95% CI 0.73-0.99), 1.31 (95% CI 1.19-1.43), 1.39 (95% CI 1.28-1.50) and 2.07 (95% CI 1.93-2.21) for patients treated only with RT (N=19), sequential chemo-RT (N=30), concurrent chemo-RT (N=49), and concurrent chemo-RT with cetuximab (N=19), respectively.

CONCLUSIONS

CT density changes allow quantitative assessment of lung damage after fractionated RT, giving complementary information to standard used clinical endpoints. Patients receiving cetuximab showed a significantly larger dose response compared with other treatments.

A new method to validate thoracic CT-CT deformable image registration using auto-segmented 3D anatomical landmarks

BACKGROUND

Deformable image registrations are prone to errors in aligning reliable anatomically features. Consequently, identification of registration inaccuracies is important. Particularly thoracic three-dimensional (3D) computed tomography (CT)-CT image registration is challenging due to lack of contrast in lung tissue. This study aims for validation of thoracic CT-CT image registration using auto-segmented anatomically landmarks.

MATERIAL AND METHODS

Five lymphoma patients were CT scanned three times within a period of 18 months, with the initial CT defined as the reference scan. For each patient the two successive CT scans were registered to the reference CT using three different image registration algorithms (Demons, B-spline and Affine). The image registrations were evaluated using auto-segmented anatomical landmarks (bronchial branch points) and Dice Similarity Coefficients (DSC). Deviation of corresponding bronchial landmarks were used to quantify inaccuracies in respect of both misalignment and geometric location within lungs.

RESULTS

The median bronchial branch point deviations were 1.6, 1.1 and 4.2 (mm) for the three tested algorithms (Demons, B-spline and Affine). The maximum deviations (> 15 mm) were found within both Demons and B-spline image registrations. In the upper part of the lungs the median deviation of 1.7 (mm) was significantly different (p < 0.02) relative to the median deviations of 2.0 (mm), found in the middle and lower parts of the lungs. The DSC revealed similar registration discrepancies among the three tested algorithms, with DSC values of 0.96, 0.97 and 0.91, for respectively Demons, B-spline and the Affine algorithms.

CONCLUSION

Bronchial branch points were found useful to validate thoracic CT-CT image registration. Bronchial branch points identified local registration errors > 15 mm in both Demons and B-spline deformable algorithms.

Ventilation/Perfusion Positron Emission Tomography--Based Assessment of Radiation Injury to Lung

PURPOSE

To investigate (68)Ga-ventilation/perfusion (V/Q) positron emission tomography (PET)/computed tomography (CT) as a novel imaging modality for assessment of perfusion, ventilation, and lung density changes in the context of radiation therapy (RT).

METHODS AND MATERIALS

In a prospective clinical trial, 20 patients underwent 4-dimensional (4D)-V/Q PET/CT before, midway through, and 3 months after definitive lung RT. Eligible patients were prescribed 60 Gy in 30 fractions with or without concurrent chemotherapy. Functional images were registered to the RT planning 4D-CT, and isodose volumes were averaged into 10-Gy bins. Within each dose bin, relative loss in standardized uptake value (SUV) was recorded for ventilation and perfusion, and loss in air-filled fraction was recorded to assess RT-induced lung fibrosis. A dose-effect relationship was described using both linear and 2-parameter logistic fit models, and goodness of fit was assessed with Akaike Information Criterion (AIC).

RESULTS

A total of 179 imaging datasets were available for analysis (1 scan was unrecoverable). An almost perfectly linear negative dose-response relationship was observed for perfusion and air-filled fraction (r(2)=0.99, P<.01), with ventilation strongly negatively linear (r(2)=0.95, P<.01). Logistic models did not provide a better fit as evaluated by AIC. Perfusion, ventilation, and the air-filled fraction decreased 0.75 ± 0.03%, 0.71 ± 0.06%, and 0.49 ± 0.02%/Gy, respectively. Within high-dose regions, higher baseline perfusion SUV was associated with greater rate of loss. At 50 Gy and 60 Gy, the rate of loss was 1.35% (P=.07) and 1.73% (P=.05) per SUV, respectively. Of 8/20 patients with peritumoral reperfusion/reventilation during treatment, 7/8 did not sustain this effect after treatment.

CONCLUSIONS

Radiation-induced regional lung functional deficits occur in a dose-dependent manner and can be estimated by simple linear models with 4D-V/Q PET/CT imaging. These findings may inform future studies of functional lung avoidance using V/Q PET/CT.

Computed tomography number changes observed during computed tomography-guided radiation therapy for head and neck cancer

PURPOSE

To investigate CT number (CTN) changes in gross tumor volume (GTV) and organ at risk (OAR) according to daily diagnostic-quality CT acquired during CT-guided intensity modulated radiation therapy for head and neck cancer (HNC) patients.

METHODS AND MATERIALS

Computed tomography scans acquired using a CT-on-rails during daily CT-guided intensity modulated radiation therapy for 15 patients with stage II to IVa squamous cell carcinoma of the head and neck were analyzed. The GTV, parotid glands, spinal cord, and nonspecified tissue were generated on each selected daily CT. The changes in CTN distributions and the mean and mode values were collected. Pearson analysis was used to assess the correlation between the CTN change, organ volume reduction, and delivered radiation dose.

RESULTS

Volume and CTN changes for GTV and parotid glands can be observed during radiation therapy delivery for HNC. The mean (±SD) CTNs in GTV and ipsi- and contralateral parotid glands were reduced by 6 ± 10, 8 ± 7, and 11 ± 10 Hounsfield units, respectively, for all patients studied. The mean CTN changes in both spinal cord and nonspecified tissue were almost invisible (<2 Hounsfield units). For 2 patients studied, the absolute mean CTN changes in GTV and parotid glands were strongly correlated with the dose delivered (P<.001 and P<.05, respectively). For the correlation between CTN reductions and delivered isodose bins for parotid glands, the Pearson coefficient varied from -0.98 (P<.001) in regions with low-dose bins to 0.96 (P<.001) in high-dose bins and were patient specific.

CONCLUSIONS

The CTN can be reduced in tumor and parotid glands during the course of radiation therapy for HNC. There was a fair correlation between CTN reduction and radiation doses for a subset of patients, whereas the correlation between CTN reductions and volume reductions in GTV and parotid glands were weak. More studies are needed to understand the mechanism for the radiation-induced CTN changes.

Association between morphologic CT imaging traits and prognostically relevant gene signatures in women with high-grade serous ovarian cancer: a hypothesis-generating study

PURPOSE

To investigate associations among imaging traits observed on computed tomographic (CT) images, Classification of Ovarian Cancer (CLOVAR) gene signatures, and survival in women with high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

The institutional review board approved this HIPAA-compliant retrospective study of CT images obtained before cytoreductive surgery in 46 women with HGSOC, whose tumors were subjected to molecular analysis performed by the Cancer Genome Atlas Research Network. Two readers independently evaluated the CT features of the primary ovarian mass and sites of metastatic spread if present, including size, outline, and texture. Fisher exact test was used to examine the relationship between imaging traits and CLOVAR subtypes (CLOVAR differentiated, immunoreactive, mesenchymal, and proliferative). Kaplan-Meier and Cox proportional hazards regression survival analyses were performed.

RESULTS

The presence of mesenteric infiltration and diffuse peritoneal involvement by tumor at CT were significantly associated with CLOVAR subtype (P = .002-.004 for reader 1 and P = .005-.012 for reader 2). Mesenteric infiltration at CT was associated with CLOVAR mesenchymal subtype. Patients with mesenteric infiltration had shorter median progression-free survival than patients without mesenteric involvement (14.7 months vs 25.6 months according to both readers; P = .019 for reader 1 and .015 for reader 2) and overall survival (49.0 vs 58.2 months; P = .014 [reader 1] and 50.0 vs 59.1 months; P = .015 [reader 2]). No other imaging features were significantly associated with CLOVAR subtype or survival.

CONCLUSION

Specific CT imaging traits were associated with the CLOVAR subtypes and survival in patients with HGSOC.

A longitudinal evaluation of partial lung irradiation in mice by using a dedicated image-guided small animal irradiator

PURPOSE

In lung cancer radiation therapy, the dose constraints are determined mostly by healthy lung toxicity. Preclinical microirradiators are a new tool to evaluate treatment strategies closer to clinical irradiation devices. In this study, we quantified local changes in lung density symptomatic of radiation-induced lung fibrosis (RILF) after partial lung irradiation in mice by using a precision image-guided small animal irradiator integrated with micro-computed tomography (CT) imaging.

METHODS AND MATERIALS

C57BL/6 adult male mice (n=76) were divided into 6 groups: a control group (0 Gy) and groups irradiated with a single fraction of 4, 8, 12, 16, or 20 Gy using 5-mm circular parallel-opposed fields targeting the upper right lung. A Monte Carlo model of the small animal irradiator was used for dose calculations. Following irradiation, all mice were imaged at regular intervals over 39 weeks (10 time points total). Nonrigid deformation was used to register the initial micro-CT scan to all subsequent scans.

RESULTS

Significant differences could be observed between the 3 highest (>10 Gy) and 3 lowest irradiation (<10 Gy) dose levels. A mean difference of 120 ± 10 HU between the 0- and 20-Gy groups was observed at week 39. RILF was found to be spatially limited to the irradiated portion of the lung.

CONCLUSIONS

The data suggest that the severity of RILF in partial lung irradiation compared to large field irradiation in mice for the same dose is reduced, and therefore higher doses can be tolerated.

Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities

Imaging techniques for the characterization and delineation of primary lung tumours and lymph nodes are a prerequisite for adequate radiotherapy. Numerous imaging modalities have been proposed for this purpose, but only computed tomography (CT) and FDG-PET have been implemented in clinical routine. Hypoxia PET, dynamic contrast-enhanced CT (DCE-CT), dual energy CT (DECT) and (functional) magnetic resonance imaging (MRI) hold promise for the future. Besides information on the primary tumour, these techniques can be used for quantification of tissue heterogeneity and response. In the future, treatment strategies may be designed which are based on imaging techniques to optimize individual treatment.