Local Correlation Between Monte-Carlo Dose and Radiation-Induced Fibrosis in Lung Cancer Patients

Nonmalignant respiratory disease mortality in male Colorado Plateau uranium miners, 1960-2016

BACKGROUND

To evaluate trends of nonmalignant respiratory disease (NMRD) mortality among US underground uranium miners on the Colorado Plateau, and to estimate the exposure-response association between cumulative radon progeny exposure and NMRD subtype mortality.

METHODS

Standardized mortality ratios (SMRs) and excess relative rates per 100 working level months (excess relative rate [ERR]/100 WLM) were estimated in a cohort of 4021 male underground uranium miners who were followed from 1960 through 2016.

RESULTS

We observed elevated SMRs for all NMRD subtypes. Silicosis had the largest SMR (n = 52, SMR = 41.4; 95% confidence interval [CI]: 30.9, 54.3), followed by other pneumoconiosis (n = 49, SMR = 39.6; 95% CI: 29.6, 52.3) and idiopathic pulmonary fibrosis (IPF) (n = 64, SMR = 4.77; 95% CI 3.67, 6.09). SMRs for silicosis increased with duration of employment; SMRs for IPF increased with duration of employment and calendar period. There was a positive association between cumulative radon exposure and silicosis with evidence of modification by smoking (ERR/100 WLM≥10 pack-years  = 0.78; 95% CI: 0.05, 24.6 and ERR/100 WLM<10 pack-years  = 0.01; 95% CI: -0.03, 0.52), as well as a small positive association between radon and IPF (ERR/100 WLM = 0.06, 95% CI: 0.00, 0.24); these associations were driven by workers with prior employment in hard rock mining.

CONCLUSIONS

Uranium mining workers had excess NMRD mortality compared with the general population; this excess persisted throughout follow-up. Exposure-response analyses indicated a positive association between radon exposure and IPF and silicosis, but these analyses have limitations due to outcome misclassification and missing information on occupational co-exposures such as silica dust.

Investigation of the evolution of radiation-induced lung damage using serial CT imaging and pulmonary function tests

BACKGROUND AND PURPOSE

Radiation-induced lung damage (RILD) is a common consequence of lung cancer radiotherapy (RT) with unclear evolution over time. We quantify radiological RILD longitudinally and correlate it with dosimetry and respiratory morbidity.

MATERIALS AND METHODS

CTs were available pre-RT and at 3, 6, 12 and 24-months post-RT for forty-five subjects enrolled in a phase 1/2 clinical trial of isotoxic, dose-escalated chemoradiotherapy for locally advanced non-small cell lung cancer. Fifteen CT-based measures of parenchymal, pleural and lung volume change, and anatomical distortions, were calculated. Respiratory morbidity was assessed with the Medical Research Council (MRC) dyspnoea score and spirometric pulmonary function tests (PFTs): FVC, FEV1, FEV1/FVC and DLCO.

RESULTS

FEV1, FEV1/FVC and MRC scores progressively declined post-RT; FVC decreased by 6-months before partially recovering. Radiologically, an early phase (3-6 months) of acute inflammation was characterised by reversible parenchymal change and non-progressive anatomical distortion. A phase of chronic scarring followed (6-24 months) with irreversible parenchymal change, progressive volume loss and anatomical distortion. Post-RT increase in contralateral lung volume was common. Normal lung volume shrinkage correlated longitudinally with mean lung dose (r = 0.30-0.40, p = 0.01-0.04). Radiological findings allowed separation of patients with predominant acute versus chronic RILD; subjects with predominantly chronic RILD had poorer pre-RT lung function.

CONCLUSIONS

CT-based measures enable detailed quantification of the longitudinal evolution of RILD. The majority of patients developed progressive lung damage, even when the early phase was absent or mild. Pre-RT lung function and RT dosimetry may allow to identify subjects at increased risk of RILD.

Correlation of normal lung density changes with dose after stereotactic body radiotherapy (SBRT) for early stage lung cancer

BACKGROUND AND PURPOSE

To investigate the correlation between normal lung CT density changes with dose accuracy and outcome after stereotactic body radiation therapy (SBRT) for patients with early stage non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

Thirty-one patients (with a total of 33 lesions) with non-small cell lung cancer were selected out of 270 patients treated with SBRT at a single institution between 2003 and 2009. Out of these 31 patients, 10 patients had developed radiation pneumonitis (RP). Dose distributions originally planned using a 1-D pencil beam-based dose algorithm were retrospectively recomputed using different algorithms. Prescription dose was 48 Gy in 4 fractions in most patients. Planning CT images were rigidly registered to follow-up CT datasets at 3-9 months after treatment. Corresponding dose distributions were mapped from planning to follow-up CT images. Hounsfield Unit (HU) changes in lung density in individual, 5 Gy, dose bins from 5 to 45 Gy were assessed in the peri-tumoral region. Correlations between HU changes in various normal lung regions, dose indices (V20, MLD, generalized equivalent uniform dose (gEUD)), and RP grade were investigated.

RESULTS

Strong positive correlation was found between HU changes in the peri-tumoral region and RP grade (Spearman's r = 0.760; p < 0.001). Positive correlation was also observed between RP and HU changes in the region covered by V20 for all algorithms (Spearman's r ≥ 0.738; p < 0.001). Additionally, V20, MLD, and gEUD were significantly correlated with RP grade (p < 0.01). MLD in the peri-tumoral region computed with model-based algorithms was 5-7% lower than the PB-based methods.

CONCLUSION

Changes of lung density in the peri-tumoral lung and in the region covered by V20 were strongly associated with RP grade. Relative to model-based methods, PB algorithms over-estimated mean peri-tumoral dose and showed displacement of the high-dose region, which correlated with HU changes on follow-up CT scans.

Spatial signature of dose patterns associated with acute radiation-induced lung damage in lung cancer patients treated with stereotactic body radiation therapy

Thoracic radiation therapy (RT) is often associated with lung side effects, whose etiology is still controversial. Our aim was to explore correlations between local dose in the thoracic anatomy and the radiation-induced lung damage (RILD). To this end, we designed a robust scheme for voxel-based analysis (VBA) to explore dose patterns associated with RILD in non-small-cell lung cancer (NSCLC) patients receiving stereotactic body RT (SBRT). We analyzed 106 NSCLC SBRT patients (median prescription dose: 50 Gy; range: [40-54] Gy) in 4 fractions (range: [3-5]) with clinical and dosimetric records suitable for the analysis. The incidence of acute G1 RILD (RTOG grade  ⩾  1) was 68%. Each planning CT and dose map was spatially normalized to a common anatomical reference using a B-spline inter-patient registration algorithm after masking the gross tumor volume. The tumor-subtracted dose maps were converted into biologically effective dose maps (α/β  =  3 Gy). VBA was performed according to a non-parametric permutation test accounting for multiple comparison, based on a cluster analysis method. The underlying general linear model of RILD was designed to include dose maps and each non-dosimetric variable significantly correlated with RILD. The clusters of voxels with dose differences significantly correlated with RILD at a given p -level (S _p) were generated. The only non-dosimetric variable significantly correlated with RILD was the chronic obstructive pulmonary disease (p   =  0.034). Patients with G1 RILD received significantly (p   ⩽  0.05) higher doses in two voxel clusters S _0.05 in the lower-left lung (14 cm³) and in an area (64 cm³) largely included within the ventricles. The applied VBA represents a powerful tool to probe the dose susceptibility of inhomogeneous organs in clinical radiobiology studies. The identified subregions with dose differences associated with G1 RILD in both the heart and lower lungs endorse a trend of previously reported hypotheses on lung toxicity radiobiology.

Image-Guided Fluorescence Endomicroscopy: From Macro- to Micro-Imaging of Radiation-Induced Pulmonary Fibrosis

Radiation-induced pulmonary fibrosis (RIPF) is a debilitating side effect of radiation therapy (RT) of several cancers including lung and breast cancers. Current clinical methods to assess and monitor RIPF involve diagnostic computed tomography (CT) imaging, which is restricted to anatomical macroscopic changes. Confocal laser endomicroscopy (CLE) or fluorescence endomicroscopy (FE) in combination with a fibrosis-targeted fluorescent probe allows to visualize RIPF in real-time at the microscopic level. However, a major limitation of FE imaging is the lack of anatomical localization of the endomicroscope within the lung. In this work, we proposed and validated the use of x-ray fluoroscopy-guidance in a rat model of RIPF to pinpoint the location of the endomicroscope during FE imaging and map it back to its anatomical location in the corresponding CT image. For varying endomicroscope positions, we observed a positive correlation between CT and FE imaging as indicated by the significant association between increased lung density on CT and the presence of fluorescent fiber structures with FE in RT cases compared to Control. Combining multimodality imaging allows visualization and quantification of molecular processes at specific locations within the injured lung. The proposed image-guided FE method can be extended to other disease models and is amenable to clinical translation for assessing and monitoring fibrotic damage.

A comparative analysis of longitudinal computed tomography and histopathology for evaluating the potential of mesenchymal stem cells in mitigating radiation-induced pulmonary fibrosis

Radiation-induced pulmonary fibrosis (RIPF) is a debilitating side effect that occurs in up to 30% of thoracic irradiations in breast and lung cancer patients. RIPF remains a major limiting factor to dose escalation and an obstacle to applying more promising new treatments for cancer cure. Limited treatment options are available to mitigate RIPF once it occurs, but recently, mesenchymal stem cells (MSCs) and a drug treatment stimulating endogenous stem cells (GM-CSF) have been investigated for their potential in preventing this disease onset. In a pre-clinical rat model, we contrasted the application of longitudinal computed tomography (CT) imaging and classical histopathology to quantify RIPF and to evaluate the potential of MSCs in mitigating RIPF. Our results on histology demonstrate promises when MSCs are injected endotracheally (but not intravenously). While our CT analysis highlights the potential of GM-CSF treatment. Advantages and limitations of both analytical methods are contrasted in the context of RIPF.

Lung deformations and radiation-induced regional lung collapse in patients treated with stereotactic body radiation therapy

PURPOSE

To differentiate radiation-induced fibrosis from regional lung collapse outside of the high dose region in patients treated with stereotactic body radiation therapy (SBRT) for lung tumors.

METHODS

Lung deformation maps were computed from pre-treatment and post-treatment computed tomography (CT) scans using a point-to-point translation method. Fifty anatomical landmarks inside the lung (vessel or airway branches) were matched on planning and follow-up scans for the computation process. Two methods using the deformation maps were developed to differentiate regional lung collapse from fibrosis: vector field and Jacobian methods. A total of 40 planning and follow-ups CT scans were analyzed for 20 lung SBRT patients.

RESULTS

Regional lung collapse was detected in 15 patients (75%) using the vector field method, in ten patients (50%) using the Jacobian method, and in 12 patients (60%) by radiologists. In terms of sensitivity and specificity the Jacobian method performed better. Only weak correlations were observed between the dose to the proximal airways and the occurrence of regional lung collapse.

CONCLUSIONS

The authors presented and evaluated two novel methods using anatomical lung deformations to investigate lung collapse and fibrosis caused by SBRT treatment. Differentiation of these distinct physiological mechanisms beyond what is usually labeled "fibrosis" is necessary for accurate modeling of lung SBRT-induced injuries. With the help of better models, it becomes possible to expand the therapeutic benefits of SBRT to a larger population of lung patients with large or centrally located tumors that were previously considered ineligible.

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.

Monte Carlo simulations will change the way we treat patients with proton beams today

Within the past two decades, the evolution of Monte Carlo simulation tools, coupled with our better understanding of physics processes and computer technology has enabled accurate and efficient prediction of particle interactions with tissue. Monte Carlo simulations have now been applied for routine clinical applications. This commentary outlines how simulations have the potential to change clinical practice particularly in proton therapy. Specifically, Monte Carlo simulations will impact treatment outcome analysis, reduce treatment volumes and help understand proton-induced radiation biology.

Time evolution of regional CT density changes in normal lung after IMRT for NSCLC

PURPOSE

This study investigates the clinical radiobiology of radiation induced lung disease in terms of regional computed tomography (CT) density changes following intensity modulated radiotherapy (IMRT) for non-small-cell lung cancer (NSCLC).

METHODS

A total of 387 follow-up CT scans in 131 NSCLC patients receiving IMRT to a prescribed dose of 60 or 66 Gy in 2 Gy fractions were analyzed. The dose-dependent temporal evolution of the density change was analyzed using a two-component model, a superposition of an early, transient component and a late, persistent component.

RESULTS

The CT density of healthy lung tissue was observed to increase significantly (p<0.0001) for all dose levels after IMRT. The time evolution and the size of the density signal depend on the local delivered dose. The transient component of the density signal was found to peak in the range of 3-4 months, while the density tends to stabilize at times >12 months.

CONCLUSIONS

The radiobiology of lung injury may be analyzed in terms of CT density change. The initial transient change in density is consistent with radiation pneumonitis, while the subsequent stabilization of the density is consistent with pulmonary fibrosis.

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.

The features of radiation induced lung fibrosis related with dosimetric parameters

BACKGROUND AND PURPOSE

Radiation induced lung fibrosis (RILF) is a major complication after lung irradiation and is very important for long term quality of life and could result in fatal respiratory insufficiency. However, there has been little information on dosimetric parameters for radiotherapy planning in the aspect of RILF. The features of RILF related with dosimetric parameters were evaluated.

METHODS AND MATERIALS

Forty-eight patients with non-small cell lung carcinoma who underwent post-operative radiation therapy (PORT) without adjuvant chemotherapy were analyzed. The degree of lung fibrosis was estimated by fibrosis volume and the dosimetric parameters were calculated from the plan of 3-dimensional conformal radiotherapy.

RESULTS

The fibrosis volume and V-dose as dosimetric parameters showed significant correlation and the correlation coefficient ranged from 0.602 to 0.683 (P<0.01). The degree of the correlation line was steeper as the dose increase and threshold dose was not found. Mean lung dose (MLD) showed strong correlation with fibrosis volume (correlation coefficient = 0.726, P<0.01).

CONCLUSIONS

The fibrosis volume is continuously increased with V-dose as the reference dose increases. MLD is useful as a single parameter for comparing rival plans in the aspect of RILF.

Imaging of normal lung, liver and parotid gland function for radiotherapy

There is growing clinical evidence that functional imaging is useful for target volume definition and early assessment of tumour response to external beam radiotherapy. A subject that has perhaps received less attention, but is no less promising, is the application of functional imaging to the prediction or measurement of radiation adverse effects in normal tissues. In this manuscript, we review the current published literature describing the use of positron emission tomography (PET), four-dimensional computed tomography (4D-CT), single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) to study normal tissue function in the context of radiotherapy to the lung, liver and head & neck. Published results to date demonstrate that functional imaging can be used to preferentially avoid normal tissues not easily identifiable on solely anatomical images. It is also a potentially very powerful tool for the early detection of radiotherapy-induced normal tissue adverse effects and could provide valuable data for building predictive models of outcome. However, one of the major challenges to building useful predictive models is that, to date, there are very little data available with combined images of normal function, 3D delivered radiation dose and clinical outcomes. Prospective data collection through well-constructed studies which use established morbidity scores is clearly a priority if significant progress is to be made in this area.

Accurate accumulation of dose for improved understanding of radiation effects in normal tissue

The actual distribution of radiation dose accumulated in normal tissues over the complete course of radiation therapy is, in general, poorly quantified. Differences in the patient anatomy between planning and treatment can occur gradually (e.g., tumor regression, resolution of edema) or relatively rapidly (e.g., bladder filling, breathing motion) and these undermine the accuracy of the planned dose distribution. Current efforts to maximize the therapeutic ratio require models that relate the true accumulated dose to clinical outcome. The needed accuracy can only be achieved through the development of robust methods that track the accumulation of dose within the various tissues in the body. Specific needs include the development of segmentation methods, tissue-mapping algorithms, uncertainty estimation, optimal schedules for image-based monitoring, and the development of informatics tools to support subsequent analysis. These developments will not only improve radiation outcomes modeling but will address the technical demands of the adaptive radiotherapy paradigm. The next 5 years need to see academia and industry bring these tools into the hands of the clinician and the clinical scientist.

Radon exposure and mortality among white and American Indian uranium miners: an update of the Colorado Plateau cohort

Studies of uranium miners on the US Colorado Plateau have identified associations between exposure to radon progeny and risk of lung cancer. This study added 15 years of mortality follow-up for the 4,137 miners (primarily white or American Indian) in the Colorado Plateau cohort. The cohort experienced 209 new lung cancer deaths. For white miners, the standardized mortality ratio for lung cancer compared with the regional population was 3.99 (95% confidence interval: 3.43, 4.62) for the period 1991-2005. For American Indian miners, the lung cancer standardized mortality ratio was 3.27 (95% confidence interval: 2.19, 4.73). These standardized mortality ratios have not declined substantially since the 1980s. Internally standardized rate ratios by radon exposure category over the entire follow-up period are similar to those based on earlier follow-up, although estimates within smoking categories demonstrated improved precision. The apparent interaction between radon and smoking in causing lung cancer remains submultiplicative but greater than additive. Mortality rates from silicosis remain highly elevated in the cohort. Elevated mortality rates were observed from interstitial pulmonary fibrosis, multiple myeloma, and non-Hodgkin lymphoma. Significant trends were observed with increased radon exposure in silicosis and pulmonary fibrosis mortality and in the incidence of diabetes-related end-stage renal disease among white miners.