Dose-function Histogram Research Articles

Predicting radiation pneumonitis with fuzzy clustering neural network using 4DCT ventilation image based dosimetric parameters.

To develop a fuzzy clustering neural network to predict radiation-induced pneumonitis (RP) using four-dimensional computed tomography (4DCT) ventilation image (VI) based dosimetric parameters for thoracic cancer patients. The VI were retrospectively calculated from pre-treatment 4DCT data using a deformable image registration (DIR) and an improved VI algorithm. Similar to dose-volume histogram (DVH) of intensity modulated radiotherapy (IMRT), dose-function histogram (DFH) was derived from dose distribution and VI. Then, the dose-function metrics were calculated from DFH. For comparison, the dose-volume metrics were calculated from DVH. Correspondingly, two sets of feature vectors were formed from the dose-volume metrics and the dose-function metrics, respectively. For the feature vectors of each set, they were first pre-processed by principal component analysis (PCA) to reduce feature dimensions. Then, they were grouped to few clusters determined by fuzzy c-means (FCM) algorithm. Next, the neural network was trained to correlate the dosimetric parameters with RP based on the feature vectors of each cluster. Finally, the occurrence of RP was predicted by the neural network on the test data. Through PCA analysis, the top 5 principal components were selected. Their contribution is more than 98%, which is adequate to represent the original feature space of input data. Based on the clustering validity indexes, the optimal number of clusters is 4 and used for subsequent fuzzy clustering of the input data. After network training, the areas under the curve (AUC) of the prediction model is 0.77 using VI-based dosimetric parameters and 0.67 using structure-based dosimetric parameters. Compared to the structure-based dosimetric features, the VI-based dosimetric features are more relevant to lung function and presented higher prediction accuracy of RP. The fuzzy clustering neural network improved the prediction accuracy of RP compared to the conventional neural network. The combination of VI-based dose-function metrics and fuzzy clustering neural network provides an effective predictive model for assessing lung toxicity risk after radiotherapy.

Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features.

In this article, we highlight the fundamental importance of the simultaneous use of dose-volume histogram (DVH) and dose-function histogram (DFH) features based on functional images calculated from 4-dimensional computed tomography (4D-CT) and deformable image registration (DIR) in developing a multivariate radiation pneumonitis (RP) prediction model. The patient characteristics, DVH features and DFH features were calculated from functional images by Hounsfield unit (HU) and Jacobian metrics, for an RP grade ≥ 2 multivariate prediction models were computed from 85 non-small cell lung cancer patients. The prediction model is developed using machine learning via a kernel-based support vector machine (SVM) machine. In the patient cohort, 21 of the 85 patients (24.7%) presented with RP grade ≥ 2. The median area under curve (AUC) was 0.58 for the generated 50 prediction models with patient clinical features and DVH features. When HU metric and Jacobian metric DFH features were added, the AUC improved to 0.73 and 0.68, respectively. We conclude that predictive RP models that incorporate DFH features were successfully developed via kernel-based SVM. These results demonstrate that effectiveness of the simultaneous use of DVH features and DFH features calculated from 4D-CT and DIR on functional image-guided radiotherapy.

Impact of 99mTc-GSA SPECT Image-Guided Inverse Planning on Dose-Function Histogram Parameters for Stereotactic Body Radiation Therapy Planning for Patients With Hepatocellular Carcinoma: A Dosimetric Comparison Study.

Purpose:To evaluate the impact of 99mTc-labeled diethylene triamine pentaacetate-galactosyl human serum albumin (99mTc-GSA) single-photon emission computed tomography (SPECT) image-guided inverse planning on the dose–function histogram (DFH) parameters for stereotactic body radiation therapy planning in patients with hepatocellular carcinoma (HCC).Methods:Eleven patients were enrolled in this study. The functional liver structure (FLS) was derived from SPECT thresholds of 60% to 80% of the maximum pixel value. Two treatment plans optimized without FLS (plan C) and with FLS (plan F) were designed for 50 Gy to the planning target volume (PTV). The DFH parameters were calculated as follows: Fx = (sum of the counts within the liver volume receiving a dose >x Gy/sum of the counts within the whole liver volume) × 100. Other parameters for the PTV included D95, mean dose, conformity index (CI), and homogeneity index (HI).Results:Compared with plan C, plan F significantly reduced DFH parameters of F5 to F40 (P < .05). There were no significant differences in the parameters of the PTV of D95, mean dose, CI, and HI and organs at risks (stomach, duodenum, spinal cord, and kidneys) between plans C and F.Conclusion:DFH analyses revealed that 99mTc-GSA SPECT image-guided inverse planning provided dosimetric benefits related to sparing of liver function and may reduce hepatic toxicities.

Comparison of predictive powers of functional and anatomic dosimetric parameters for radiation-induced lung toxicity in locally advanced non-small cell lung cancer

PurposeTo investigate the predictive value of the perfusion (Q) single-photon emission computed tomography (SPECT)-weighted dose–function histogram (DFH) obtained mid-treatment (mid-Tx) with radiotherapy (RT) for radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC). Materials and methodsThe study population consisted of NSCLC patients who were undergoing RT treatment and enrolled in prospective imaging studies. Q-SPECT was performed prior to and during RT (at ∼40–45 Gy). A baseline dose–volume histogram (DVH) and mid-Tx DVH based on simulation CT as well as a baseline DFH and mid-Tx DFH based on Q-SPECT were calculated. Only patients with stage III NSCLC and visible functional lung (FL) changes on the mid-Tx scan were eligible for this enriched analysis. RILT was graded according to a reported scale. ResultsForty-two stage III NSCLC patients met the criteria for inclusion. The accumulative incidence of grade ≥2 RILT was 31% in this high-risk population. Significant differences in functional metrics such as functional lung volume FV5–FV20 at increments of 5 Gy and functional MLD (FMLD) were observed between patients with and without grade ≥2 RILT (p < 0.05). Similar results were also obtained for anatomical metrics from V5–V20 and MLD (p < 0.05). The areas under the receiver operating characteristic curves (AUCs) ranged from 0.724to 0.812 for baseline DVH parameters, from 0.745 to 0.830 for mid-Tx DVH parameters, from 0.764 to 0.878 for baseline DFH parameters, and from 0.767 to 0.891 for mid-Tx DFH parameters. Further principal components analysis showed that the AUCs were 0.814/0.817 and 0.790/0.857 for baseline/mid-Tx DVH and baseline/mid-Tx DFH, respectively. ConclusionsMid-Tx DFH parameters based on Q-SPECT were significantly elevated in patients with grade ≥2 RILT in this study population. Among the metrics compared, mid-Tx DFH seemed to have better predictive accuracy, but this difference did not reach statistical difference.

Functional Liver Imaging and Dosimetry to Predict Hepatotoxicity Risk in Cirrhotic Patients With Primary Liver Cancer

Mitigating radiation-induced liver disease (RILD) is an ongoing need in patients with hepatocellular carcinoma. We hypothesize that [99mTc]-sulfur colloid (SC) single photon emission computed tomography (SPECT)/computed tomography (CT) scans can provide global functional liver metrics and functional liver dosimetric parameters that are predictive of hepatotoxicity risk in patients with primary liver cancer with cirrhosis. We retrospectively reviewed 47 patients (n=26 proton, n=21 stereotactic body radiation therapy) with Child-Pugh (CP)-A (62%) or CP-B (38%) cirrhosis who underwent SC SPECT/CT scans for radiation therapy planning. SC SPECT scans were mined for image intensity threshold-based functional liver volumes (FLV), mean liver-spleen uptake ratio (L/Smean), and total liver function (TLF=FLV*L/Smean). Radiation therapy doses were voxel-wise converted to the biologically equivalent dose (EQD2a/b=3) and relative biological effectiveness (GyRBE). Normal liver (liver minus gross tumor volume [GTV]) and FLV mean doses, absolute and relative dose-volumes (VGy[cc], VGy[%]), and relative dose-function histogram quantiles in 10 GyEQD2 increments were calculated. Logistic regression was performed for correlation to CP score increase of 2 or higher (CP+2). Cox regression was performed for correlation to RILD-specific survival (RILD-SS) and overall survival. The strongest predictors of RILD-SS were FLV V20 and liver-GTV F20. FLV mean dose, but not CT-derived anatomic mean dose, was predictive of RILD-SS. TLF and L/Smean were the only parameters that were associated with CP+2 after adjusting for baseline CP score. Optimal cutoffs to mitigate risk RILD-SS were identified: FLV mean dose <23 GyEQD2, liver-GTV V20<36%, FLV V20<36%, liver-GTV F20<36%, FLV <32% (350cc), L/Smean >0.75, TLF >0.60, tumor volume <40cm3, and CP score A5-6 versus B7-C10. A narrower therapeutic window was observed in CP-B/C patients. The discriminatory power for RILD-SS within CP-B/C classes was improved with the addition of a functional dosimetric constraint, resulting in low- and high-risk subgroups (P=3×10-6). Functional liver metrics and dosimetric parameters derived from pretreatment SC SPECT/CT scans were complementary predictors of hepatotoxicity and may provide useful clinical decision support in the management of cirrhotic patients with primary liver cancer.

Correlation of Regional Lung Ventilation and Gas Transfer to Red Blood Cells: Implications for Functional-Avoidance Radiation Therapy Planning

To investigate the degree to which lung ventilation and gas exchange are regionally correlated, using the emerging technology of hyperpolarized (HP)-129Xe magnetic resonance imaging (MRI). Hyperpolarized-129Xe MRI studies were performed on 17 institutional review board-approved human subjects, including 13 healthy volunteers, 1 emphysema patient, and 3 non-small cell lung cancer patients imaged before and approximately 11weeks after radiation therapy (RT). Subjects inhaled 1L of HP-129Xe mixture, followed by the acquisition of interleaved ventilation and gas exchange images, from which maps were obtained of the relative HP-129Xe distribution in three states: (1) gaseous, in lung airspaces; (2) dissolved interstitially, in alveolar barrier tissue; and (3) transferred to red blood cells (RBCs), in the capillary vasculature. The relative spatial distributions of HP-129Xe in airspaces (regional ventilation) and RBCs (regional gas transfer) were compared. Further, we investigated the degree to which ventilation and RBC transfer images identified similar functional regions of interest (ROIs) suitable for functionally guided RT. For the RT patients, both ventilation and RBC functional images were used to calculate differences in the lung dose-function histogram and functional effective uniform dose. The correlation of ventilation and RBC transfer was ρ=0.39±0.15 in healthy volunteers. For the RT patients, this correlation was ρ=0.53±0.02 before treatment and ρ=0.39±0.07 after treatment; for the emphysema patient it was ρ=0.24. Comparing functional ROIs, ventilation and RBC transfer demonstrated poor spatial agreement: Dice similarity coefficient=0.50±0.07 and 0.26±0.12 for the highest-33%- and highest-10%-function ROIs in healthy volunteers, and in RT patients (before treatment) these were 0.58±0.04 and 0.40±0.04. The average magnitude of the differences between RBC- and ventilation-derived functional effective uniform dose, fV20Gy, fV10Gy, and fV5Gy were 1.5±1.4Gy, 4.1%±3.8%, 5.0%±3.8%, and 5.3%±3.9%, respectively. Ventilation may not be an effective surrogate for true regional lung function for all patients.

Evaluating Which Dose-Function Metrics Are Most Critical for Functional Guided Radiation Therapy with CT Ventilation Imaging

4DCT-ventilation imaging is increasingly being used to calculate lung ventilation and implement functional guided radiotherapy in clinical trials. There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation for functional guided radiotherapy. Our study evaluated which dose-function metrics are most critical in assessing the risk of radiation pneumonitis (RP). Seventy lung cancer patients with 4DCT imaging and RP grading were used. Pre-treatment 4DCTs of each patient were used to calculate ventilation images. We evaluated 3 different types of dose function metrics that combined that patient’s 4DCT-ventilation image and treatment planning dose distribution: 1) structure-based approaches 2) image-based approaches using the dose-function histogram (DFH) and 3) non-linear weighting schemes. Structure-based approaches used a binary approximation in which the lung was binned to either functional or non-functional status. A full range of cutoff values to delineate between functional and non-functional and the volume of functional lung receiving ≥ 5Gy, 10Gy, 20Gy, and 30Gy was investigated. Imaging-based and non-linear approaches investigated the fraction of lung function receiving ≥ 5Gy, 10Gy, 20Gy, and 30Gy. Maximum likelihood methods were used to generate normal tissue complication probability (NTCP) models predicting grade 3+ RP for the dose-function schemes and all tested dose-function metrics. The area under the curve (AUC) for each model was used to quantify the ability to predict for toxicity. All techniques were compared to NTCP models based on traditional, total lung dose metrics. The most predictive models for grade 3+ RP were structure-based approaches that focused on the volume of functional lung receiving ≥20Gy (AUC=0.70) where functional lung was treated as regions with ventilation values ≥84th percentile. Imaging-based analysis with the DFH and non-linear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when evaluating the fraction of functionality receiving ≥20Gy. All dose-function metrics outperformed the traditional lung dose metrics (mean lung dose, AUC = 0.55). A full range of dose-function metrics and functional thresholds were examined. The AUC values for the most predictive functional models occupied a narrow range (0.66-0.70) and all demonstrated improvements over AUC from traditional lung dose metrics (0.55). Identifying the dose-function parameters most predictive of grade 3+ RP provides valuable data for treatment planning and plan evaluation parameters. With prospective clinical trials of functional guided radiotherapy using 4DCT-ventilation imaging underway, this work provides seminal data to help establish guidelines for the implementation of functional guided radiotherapy.

Correlation of Perfused Lung Heterogeneity and Dosimetry With Incidence of Radiation Pneumonitis

In patients undergoing radiation treatment to the thorax, baseline lung function and functional lung dosimetry may play an important role in modulating pneumonitis risk. We evaluated features of perfused lung heterogeneity and dosimetry for correlation to incidence of radiation-induced pneumonitis. Pre-treatment 99mTc-MAA perfusion SPECT/CT scans were co-registered to planning CT scans in 28 patients who received definitive-dose thoracic radiotherapy: 20 patients with non-small cell lung cancer, 5 with small cell lung cancer, and 3 with lung metastasis. Eleven patients underwent IMRT or 3DCRT, 7 SBRT, and 10 proton RT. Two patients had clinical grade 2, one patient had grade 3, and two patients had grade 4 radiation pneumonitis defined by CTCAE version 4. Anatomic GTV-subtracted total lung (TL-GTV) mean dose (MLD) and dose-volumes were extracted. Threshold percentages of maximum perfusion (10-90%) within TL-GTV defined functional lung volumes, from which mean perfused lung doses (pMLD10-90%) were calculated. Dose-function histogram quantiles, defined as the fraction of integral lung perfusion receiving a given dose or higher (FGy), were recorded. Heterogeneity in baseline lung perfusion was assessed by intensity histogram distribution moments (coefficient of variation, skewness, kurtosis). Doses were voxelwise converted to EQD2a/b=3and GyRBE to account for fractionation variability and proton therapy dosing, respectively. Logistic regression characterized the predictive accuracy of features for incidence of grade 2 or higher pneumonitis (G2+ PNM). Anatomic mean lung dose was significantly higher in G2+ PNM patients following Mann-Whitney testing (14.6 vs. 9.3 GyEQD2, p=0.003). Patients with G2+ PNM demonstrated significantly higher pMLD70% (19.3 vs. 5.6 GyEQD2, p=0.02). MLD (p=0.002), pMLD70% (p=0.02) and F25Gy (p=0.009) were predictive of G2+ PNM under univariate logistic regression (AUC>0.79). Patients at high risk for pneumonitis presented with MLD>13.6 GyEQD2, pMLD70%>13.2 GyEQD2 and F25Gy>16% (100% sensitivity, >74% specificity). Baseline perfused lung distribution coefficient of variation, skewness and kurtosis did not correlate with G2+ PNM incidence. Perfused lung dose and dose-function histogram parameters were statistically associated with incidence of grade 2 or higher radiation pneumonitis. Validation of these functional lung planning constraints is underway within a prospective functional lung avoidance trial.

Evaluating Which Dose-Function Metrics Are Most Critical for Functional-Guided Radiation Therapy

Four-dimensional (4D) computed tomography (CT) ventilation imaging is increasingly being used to calculate lung ventilation and implement functional-guided radiation therapy in clinical trials.There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation. The purpose of our study was to evaluate which dose-function metrics best predict for radiation pneumonitis (RP). Seventy lung cancer patients who underwent 4D CT imaging and pneumonitis grading were assessed. Pretreatment 4D CT scans of each patient were used to calculate ventilation images. We evaluated 3 types of dose-function metrics that combined the patient's 4D CT ventilation image and treatment planning dose distribution: (1) structure-based approaches; (2) image-based approaches using the dose-function histogram; and (3) nonlinear weighting schemes. Log-likelihood methods were used to generate normal tissue complication probability models predicting grade 3 or higher (ie, grade 3+) pneumonitis for all dose-function schemes. The area under the curve (AUC) was used to assess the predictive power of the models. All techniques were compared with normal tissue complication probability models based on traditional, total lung dose metrics. The most predictive models were structure-based approaches that focused on the volume of functional lung receiving ≥20Gy (AUC, 0.70). Probabilities of grade 3+RP of 20% and 10% correspond to V20 (percentage of volume receiving ≥20Gy) to the functional subvolumes of 26.8% and 9.3%, respectively.Imaging-based analysis with the dose-function histogram and nonlinear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when we evaluated the percentage of functionality receiving ≥20Gy.All dose-function metrics outperformed the traditional dose metrics (mean lung dose, AUC of 0.55). A full range of dose-function metrics and functional thresholds was examined. The calculated AUC values for the most predictive functional models occupied a narrow range (0.66-0.70), and all showed notable improvements over AUC from traditional lung dose metrics (0.55). Identifying the combinations most predictive of grade 3+RP provides valuable data to inform the functional-guided radiation therapy process.

SPECT‐based functional lung imaging for the prediction of radiation pneumonitis: A clinical and dosimetric correlation

When we irradiate lung cancer, the radiation dose that can be delivered safely is limited by the risk of radiation pneumonitis (RP) in the surrounding normal lung. This risk is dose-dependent and is commonly predicted using metrics such as the V20, which are usually formulated assuming homogeneous pulmonary function. Because in vivo pulmonary function is not homogeneous, if highly functioning lung can be identified beforehand and preferentially avoided during treatment, it might be possible to reduce the risk of RP, suggesting the utility of function-based prediction metrics. We retrospectively identified 26 patients who received ventilation and perfusion single photon emission computed tomography (SPECT-CT) immediately prior to curative-intent radiation therapy. Patients were separated into non-RP and RP groups. As-treated dose-volume histogram (DVH), perfusion-SPECT-based and ventilation-SPECT-based dose-function histogram (DFH) parameters were defined for each group and were tested for differences. The relative utilities of ventilation-based and perfusion-based DFH metrics were assessed using receiver operating characteristic (ROC) analysis. The standard mean lung dose (MLD) was significantly higher in the RP group; the standard V20 and V30 were higher in the RP group but not significantly. Perfusion-weighted and ventilation-weighted values of the MLD, V20 and V30 were all significantly higher in the RP group. ROC analysis suggested that SPECT-based DFH parameters outperformed standard DVH parameters as predictors of RP. SPECT-based DFH parameters appear to be useful as predictors of RP.

A methodology for selecting the beam arrangement to reduce the intensity-modulated radiation therapy (IMRT) dose to the SPECT-defined functioning lung

Macroaggregated albumin single-photon emission computed tomography (MAA-SPECT) provides a map of the spatial distribution of lung perfusion. Our previous work developed a methodology to use SPECT guidance to reduce the dose to the functional lung in IMRT planning. This study aims to investigate the role of beam arrangement on both low and high doses in the functional lung. In our previous work, nine-beam IMRT plans were generated with and without SPECT guidance and compared for five patients. For the current study, the dose–function histogram (DFH) contribution for each of the nine beams for each patient was calculated. Four beams were chosen based on orientation and DFH contributions to create a SPECT-guided plan that spared the functional lung and maintained target coverage. Four-beam SPECT-guided IMRT plans reduced the F20 and F30 values by (16.5 ± 6.8)% and (6.1 ± 9.2)%, respectively, when compared to nine-beam conventional IMRT plans. Moreover, the SPECT-4F Plan reduces F5 and F13 for all patients by (11.0 ± 8.2)% and (6.1 ± 3.6)%, respectively, compared to the SPECT Plan. Using fewer beams in IMRT planning may reduce the amount of functional lung that receives 5 and 13 Gy, a factor that has recently been associated with radiation pneumonitis.

SU-FF-J-136: The Impact of Attenuation and Scatter Correction On the SPECT Guided Radiation Therapy for Lung Cancer Patients: Comparison of SPECT Weighted Mean Dose and Functional Lung Segmentation

Purpose: To investigate the impact of different types of image reconstruction and attenuation/scatter (A/S) correction on the calculation of dosimetric indices proposed to be used for Single Photon Emission Computed Tomography (SPECT) guided dose escalation in lung cancer patients. Methods and Materials: SPECT lung perfusion scans were obtained for nine lung cancer patients using 99mTc-macroaggregated albumin. Four image sets were reconstructed from each scan: one using a vendor provided ordered subsets expectation maximization (OSEM) algorithm, two quantitative SPECT reconstructions using OSEM methods with different types of A/S corrections and the fourth an OSEM reconstruction without any A/S correction. SPECT weighted mean dose (SWMD), dose function histogram, and functional lung volume have been calculated from dose distributions and regional perfusion maps. To investigate the dependence of SWMDs on gantry angle, twelve equally spaced co-planar open field radiation beams delivering the same MU were centered on the PTV. Three field sizes, 5×5, 7.5×7.5 and 10×10cm2 were considered. SWMDs were calculated for each field and reconstruction. Functional lung volumes were segmented in each reconstruction using 10, 20, …, 90% of maximum SPECT uptake as a threshold. Results: SWMDs calculated from reconstructions without A/S correction showed more than 5% average difference compared to those with corrections. With A/S corrections, more consistent SWMDs were found in all the three OSEM reconstructions (average difference ∼2%). However, a large variation was observed between segmented functional lung volumes and the V20 of these volumes in all four reconstructions. The difference between the volumes reached over 50% regardless of whether A/S correction was applied in the reconstruction. Conclusion: Functional volume segmentation is sensitive to the type of A/S correction. In contrast, SPECT weighted mean dose calculation produces more consistent results and appears to be a more robust choice for clinical outcome analysis and SPECT guided treatment planning.

SU‐GG‐J‐98: Functional Lung Preservation Using Four‐Dimensional Computed Tomography and Intensity‐Modulated Radiation Therapy for Lung Cancer

Purpose: The goal of this work is to reduce irradiation to functional lung using the four‐dimensional computed tomography (4D CT) derived images. The proposed technique is incorporated into intensity‐modulated radiation therapy (IMRT) to minimize radiation damage to healthy lung and pulmonary toxicity. Method and Materials: Fifteen patients with non‐small‐ cell lung cancer (NSCLC) were selected for this study. A BSpline deformable registration was employed to map each tissue element across the 4D CT data set to establish the correspondence of each voxel. Based on the changes in voxel intensities of each patient, functional image set was generated using pairs between expiration phase and other phases using the equalized histogram technique which equalizes the lung volume under each pixel intensity bin. All functional images were imported into the treatment planning system. The highly functional lung volumes formed by the percentile functional volumes were chosen to be the regions of interest (ROIs) for avoidance in IMRT treatment planning. Two IMRT plans with (fIMRT) and without (aIMRT) the functional image constraint were created and dose distributions including dose volume histograms (DVHs) and dose function histograms (DFHs) and other dosimetric parameters for the planning target volume (PTV) and critical structures in both plans were computed and compared. Results: Compared to aIMRT, the mean dose in fIMRT at 90 and 50 percentile levels were reduced by 2.5 Gy and 4.3 Gy, respectively. The mean reductions in the percentage of irradiated volume of 5 Gy (V5) and 20 Gy (V20) were significantly reduced from that of fIMRT. Conclusion: The dynamic functional images derived from 4D CT was used to guide IMRT planning and it was shown to be effective in preserving normal lung function for NSCLC cancer patients.

Reduction of Normal Lung Irradiation in Locally Advanced Non–Small-Cell Lung Cancer Patients, Using Ventilation Images for Functional Avoidance

To investigate the ability of four-dimensional computed tomography (4D-CT)-derived ventilation images to identify regions of highly functional lung for avoidance in intensity-modulated radiotherapy (IMRT) planning in locally advanced non-small-cell lung cancer (NSCLC). The treatment-planning records from 21 patients with Stage III NSCLC were selected. Ventilation images were generated from the 4D-CT sets, and each was imported into the treatment-planning system. Ninetieth percentile functional volumes (PFV90), constituting the 10% of the lung volume where the highest ventilation occurs, were generated. Baseline IMRT plans were generated using the lung volume constraint on V20 (<35%), and two additional plans were generated using constraints on the PFV90 without a volume constraint. Dose-volume and dose-function histograms (DVH, DFH) were generated and used to evaluate the planning target volume coverage, lung volume, and functional parameters for comparison of the plans. The mean dose to the PFV90 was reduced by 2.9 Gy, and the DFH at 5 Gy (F5) was reduced by 9.6% (SE = 2.03%). The F5, F10, V5, and V10 were all significantly reduced from the baseline values. We identified a favorable subset of patients for whom there was a further significant improvement in the mean lung dose. Four-dimensional computed tomography-derived ventilation regions were successfully used as avoidance structures to reduce the DVH and DFH at 5 Gy in all cases. In a subset, there was also a reduction in the F10 and V10 without a change in the V20, suggesting that this technique could be safely used.

A methodology for using SPECT to reduce intensity-modulated radiation therapy (IMRT) dose to functioning lung

Single photon emission computed tomography (SPECT) provides a map of the spatial distribution of lung perfusion. Thus, SPECT guidance can be used to divert dose away from higher-functioning lung, potentially reducing lung toxicity. We present a methodology for achieving this aim and test it in intensity-modulated radiotherapy (IMRT) treatment-planning. IMRT treatment plans were generated with and without SPECT guidance and compared for 5 patients. Healthy lung was segmented into four regions on the basis of SPECT intensity in the SPECT plan. Dose was sequentially allowed to the target via regions of increasing SPECT intensity. This process results in reduction of dose to functional lung, reflected in the dose-function histogram (DFH). The plans were compared using DFHs and F(20)/F(30) values (F(x) is the functional lung receiving dose above x Gy). In all cases, the SPECT-guided plan produced a more favorable DFH compared with the non-SPECT-guided plan. Additionally, the F(20) and F(30) values were reduced for all patients by an average of 13.6% +/- 5.2% and 10.5% +/- 5.8%, respectively. In all patients, DFHs of the two highest-functioning SPECT regions were reduced, whereas DFHs of the two lower-functioning regions were increased, illustrating the dose "give-take" between SPECT regions during redistribution. SPECT-guided IMRT shows potential for reducing the dose delivered to highly functional lung regions. This dose reduction could reduce the number of high-grade pneumonitis cases that develop after radiation treatment and improve patient quality of life.

TH‐C‐224C‐09: Using SPECT‐Guidance to Reduce Intensity Modulated Radiation Therapy (IMRT) Dose to Functioning Lung

Purpose: Single photon emission computed tomography (SPECT) provides a map of the spatial distribution of lung perfusion. Thus, SPECT guidance can be used to deliberately divert dose away from higher functioning lung, thereby potentially reducing lung toxicity. This work presents an algorithmic methodology for achieving this aim, and tests it in intensity modulated radiotherapy (IMRT) treatment planning of five randomly selected lung cancer patients. Method and Materials: IMRT treatment plans were generated with and without SPECT guidance and compared. Both sets of plans were made to adhere to the same dose‐volume constraints. The SPECT‐guided process works by segmenting healthy lung into four regions on the basis of SPECT intensity, and sequentially allowing dose to the target via regions of increasing SPECT intensity. This process results in reduction of dose to functional lung, reflected in the dose‐function histogram (DFH). DFHs quantify the percentage of total function above dose levels. The plans were compared using DFHs and F20 / F30 values (Fx is the functional lung receiving dose above x Gy; 20/30 Gy are significant thresholds for radiation pneumonitis). Results: In all cases, the SPECT‐guided plan produced a more favorable DFH compared to the non‐SPECT guided plan. Additionally, the F20 and F30 values were reduced for all patients by an average of 13.6% ± 5.2% and 10.5% ± 5.8%, respectively. In all patients, for the SPECT‐guided plans, DFHs of the two highest functioning SPECT regions were reduced while DFHs of the two lower functioning regions were increased, illustrating the dose “give‐take” between SPECT regions that is inherent to the redistribution process. Conclusion: SPECT‐guided IMRT shows potential for reducing the dose delivered to highly functional lung regions. This dose reduction could reduce the number of high grade pneumonitis cases that develop after radiation treatment and improve patient quality of life.

Predicting radiotherapy‐induced cardiac perfusion defects

The purpose of this work is to compare the efficacy of mathematical models in predicting the occurrence of radiotherapy-induced left ventricular perfusion defects assessed using single-photon emission computed tomography (SPECT). The basis of this study is data from 73 left-sided breast/ chestwall patients treated with tangential photon fields. The mathematical models compared were three commonly used parametric models [Lyman normal tissue complication probability (LNTCP), relative serialty (RS), generalized equivalent uniform dose (gEUD)] and a nonparametric model (Linear discriminant analysis--LDA). Data used by the models were the left ventricular dose--volume histograms, or SPECT-based dose-function histograms, and the presence/absence of SPECT perfusion defects 6 months postradiation therapy (21 patients developed defects). For the parametric models, maximum likelihood estimation and F-tests were used to fit the model parameters. The nonparametric LDA model step-wise selected features (volumes/function above dose levels) using a method based on receiver operating characteristics (ROC) analysis to best separate the groups with and without defects. Optimistic (upper bound) and pessimistic (lower bound) estimates of each model's predictive capability were generated using ROC curves. A higher area under the ROC curve indicates a more accurate model (a model that is always accurate has area = 1). The areas under these curves for different models were used to statistically test for differences between them. Pessimistic estimates of areas under the ROC curve using dose-volume histogram/ dose-function histogram inputs, in order of increasing prediction accuracy, were LNTCP (0.79/0.75), RS (0.80/0.77), gEUD (0.81/0.78), and LDA (0.84/0.86). Only the LDA model benefited from SPECT-based regional functional information. In general, the LDA model was statistically superior to the parametric models. The LDA model selected as features the left ventricular volumes above approximately 23 Gy (V23), essentially volume in field, and 33 Gy (V33), as best separating the groups with and without defects. In conclusion, the nonparametric LDA model appears to be a more accurate predictor of radiotherapy-induced left ventricular perfusion defects than commonly used parametric models.

Predicting the risk of radiation-induced lung injury using a biophysical parameter

Predicting the risk of radiation-induced lung injury using a biophysical parameter

Predicting the risk of radiation-induced lung injury using a biophysical parameter

This research work is based on the premise that many normal organs have heterogeneous volumes with spatially variable function. Consequently, the utilization of biological models that incorporate functional imaging information is imperative in predicting and quantifying the risk of radiation-induced normal organs toxicity. The objective of this work is to correlate lung toxicity data from non-small cell lung cancer (NSCLC) patients with values from the functional equivalent uniform dose biological model, so that such information may be used to predict the risk of radiation-induced lung injury. The data from 38 NSCLC patients with single photon emission computed tomography (SPECT) perfusion data, who received 3DCRT treatments at our institution, were analyzed. The patients’ dose-volume histograms were used to calculate the lung generalized equivalent uniform dose (EUD) values. The EUD reports the generalized mean value of the non-uniform dose distribution, which represents the homogenous dose distribution that produces the same lung complication as that produced by the inhomogeneous dose distribution. The patients’ dose-function histograms (DFH), which relates dose to the percentage of total function value at that dose, were used to calculate lung functional EUD (FEUD) values. The DFH incorporates lung SPECT perfusion imaging data. A treatment plan with a low lung FEUD value implies more sparing of functional sub-units and this may result in lower complications. The CT anatomical-volume of lungs was first correlated with changes in SPECT regional perfusion data. The lungs dose distributions were then evaluated using the generalized EUD and FEUD models with a lung a value of 0.96 (a or 1/n is a critical structure specific parameter which describes the dose-volume effect). The a parameter value was calculated using the tolerance dose values of Emami et al to the whole lung and partial volumes that would result in a 5% complication probability in 5 years (TD5/5). The biophysical parameter (RFE), which is the ratio of FEUD to EUD, was evaluated for each patient in order to predict the risk of radiation-induced lung pneumonitis (RP) by correlating the patients’ outcome data with the RFE values. Figure 1(left) shows the lungs FEUD and EUD data for the lung patients with and without RP. The results suggest that there is a correlation between RFE and lung RP. Twenty-three out of 32 patients without RP have FEUD values less than EUD (RFE <1). Six out of 8 patients with RP have FEUD values higher or equal to EUD (RFE ≥ 1). The RFE data quantify the radiation-induced lung toxicity (i.e. the risk of RP is higher with the irradiation of more functioning lungs) and suggest that RFE may be used as predictor for RP. Figure 2(right) shows FEUD and EUD for the lung patients with their tumor T staging. The majority of patients with tumor staging T3 and T4 have FEUD values equal or less than EUD (RFE <1). Patients with stage T1 have FEUD values approximately equal to EUD. The RFE data show that as tumor aggressiveness increases, the lung function decreases, which may be due to tumor obstruction of blood flow to the lung vessels. The biophysical parameter (RFE), which combines EUD and FEUD, quantifies radiation-induced lung injury, a fact that is not revealed by the physical EUD data alone. Furthermore, this work shows that predictions from biological models that incorporate both dose-function and dose-volume information correlate better with patient outcome data.

Incorporation of functional imaging data in the evaluation of dose distributions using the generalized concept of equivalent uniform dose

Advances in the fields of IMRT and functional imaging have greatly increased the prospect of escalating the dose to highly active or hypoxic tumour sub-volumes and steering the dose away from highly functional critical structure regions. However, current clinical treatment planning and evaluation tools assume homogeneous activity/function status in the tumour/critical structures. A method was developed to incorporate tumour/critical structure heterogeneous functionality in the generalized concept of equivalent uniform dose (EUD). The tumour and critical structures functional EUD (FEUD) values were calculated from the dose–function histogram (DFH), which relates dose to the fraction of total function value at that dose. The DFH incorporates flouro-deoxyglucose positron emission tomography (FDG-PET) functional data for tumour, which describes the distribution of metabolically active tumour clonogens, and single photon emission computed tomography (SPECT) perfusion data for critical structures. To demonstrate the utility of the method, the lung dose distributions of two non-small cell lung caner patients, who received 3D conformal external beam radiotherapy treatment with curative intent, were evaluated. Differences between the calculated lungs EUD and FEUD values of up to 50% were observed in the 3D conformal plans. In addition, a non-small cell lung cancer patient was inversely planned with a target dose prescription of 76 Gy. Two IMRT plans (plan-A and plan-B) were generated for the patient based on the CT, FDG-PET and SPECT treatment planning images using dose–volume objective functions. The IMRT plans were generated with the goal of achieving more critical structures sparing in plan-B than plan-A. Results show the target volume EUD in plan-B is lower than plan-A by 5% with a value of 73.31 Gy, and the FEUD in plan-B is lower than plan-A by 2.6% with a value of 75.77 Gy. The FEUD plan-B values for heart and lungs were lower than plan-A by 22% and 18%, respectively. While EUD values show plan-A is marginally better than plan-B in terms of target volumetric coverage, the FEUD plan-B values show adequate target function coverage with significant critical structure function sparing. In conclusion, incorporating functional data in the calculation of EUD is important in evaluating the biological merit of treatment plans.