Evaluation of PTV margin in CBCT-based online adaptive radiation therapy for gastric mucosa-associated lymphoid tissue lymphoma.

The aim of this study was to investigate planning target volume (PTV) margin in online adaptive radiation therapy (oART) for gastric mucosa-associated lymphoid tissue (MALT) lymphomas. Four consecutive patients with gastric MALT lymphoma who received oART (30 Gy in 15 fractions) on the oART system were included in this study. One hundred and twenty cone-beam computed tomography (CBCT) scans acquired pre- and post-treatment of 60 fractions for all patients were used to evaluate intra- and interfractional motions. Patients were instructed on breath-holding at exhalation during image acquisition. To assess the intrafraction gastric motion, different PTVs were created by isotropically extending the CTV contoured on a pre-CBCT image (CTVpre) at1 mm intervals. Intrafraction motion was defined as the amount of expansion covering the contoured CTV on post-CBCT images (CTVpost). Interfractional motion was defined as the amount of reference CTV expansion that could cover each CTVpre, as well as the evaluation of the intrafractional motion. PTV margins were estimated from the cumulative proportion of fraction covering the intra- and interfractional motions. The extent of expansion covering the CTVs in 90% of fractions was adopted as the PTV margin. The PTV margin for intrafractional gastric motion using the oART system with breath-holding was 14 mm. In contrast, the PTV margin for interfractional gastric organ motion without the oART system was 25 mm. These results indicated that the oART system can reduce the PTV margin by >10 mm. Our results could be valuable data for oART cases.

Difference in target dose distributions between Acuros XB and collapsed cone convolution/superposition and the impact of the tumor locations in clinical cases of stereotactic ablative body radiotherapy for lung cancer.

Objectives: The objective of the study is to analyze the difference in target dose distributions between Acuros XB (AXB) and collapsed cone convolution (CCC)/superposition and the impact of the tumor locations in clinical cases of stereotactic ablative body radiotherapy (SABR) for lung cancer. Materials and Methods: Ninety-six patients underwent SABR for lung cancers Kyushu University Hospital from 2014 to 2017. We recalculated clinical plans originally calculated by AXB using CCC with the identical monitor units (MUs) and beam arrangements. We calculated the following dosimetric parameters: maximum dose (Dmax), minimum dose (Dmin), homogeneity index (HI), conformity index (CI), and D95 of the planning target volume (PTV). We investigated the difference between the results of two calculations and examined the impact of tumor location. Moreover, we determined the target central dose using a thorax phantom and assessed the calculation accuracy of the two algorithms for each fraction. Results: CCC significantly overestimated the dose to PTV, compared to AXB (P < 0.05). The mean differences of Dmax, Dmin, and D95 were 1.17, 1.95, and 1.85 Gy, respectively. The mean differences of HI and CI were 0.02 and - 0.06. Dmin, HI, and D95 had significant correlations with the tumor location, and the difference was greater when the PTV was included the chest wall (P < 0.05). The discrepancy between the calculated and irradiated dose was 2.48% for CCC, whereas it was 0.14% for AXB. Conclusions: We demonstrated that CCC significantly overestimated the dose to PTV relative to AXB in clinical cases of lung SABR.

Investigation of uncertainty in internal target volume definition for lung stereotactic body radiotherapy.

This study evaluated the validity of internal target volumes (ITVs) defined by three- (3DCT) and four-dimensional computed tomography (4DCT), and subsequently compared them with actual movements during treatment. Five patients with upper lobe lung tumors were treated with stereotactic body radiotherapy (SBRT) at 48 Gy in four fractions. Planning 3DCT images were acquired with peak-exhale and peak-inhale breath-holds, and 4DCT images were acquired in the cine mode under free breathing. Cine images were acquired using an electronic portal imaging device during irradiation. Tumor coverage was evaluated based on the manner in which the peak-to-peak breathing amplitude on the planning CT covered the range of tumor motion (± 3 SD) during irradiation in the left-right, anteroposterior, and cranio-caudal (CC) directions. The mean tumor coverage of the 4DCT-based ITV was better than that of the 3DCT-based ITV in the CC direction. The internal margin should be considered when setting the irradiation field for 4DCT. The proposed 4DCT-based ITV can be used as an efficient approach in free-breathing SBRT for upper-lobe tumors of the lung because its coverage is superior to that of 3DCT.

[Dosimetric Properties of Brass Mesh Bolus for High-energy Photon Beam].

PURPOSE: To investigate fundamental dosimetric properties of surface dose, exit dose, and beam profile of the brass mesh bolus for 4, 6, and 10 MV high-energy photon beams in radiation therapy. METHODS: Surface dose and exit dose in the water-equivalent phantom were measured, and percent depth doses (PDDs) were calculated with no bolus, one layer of brass mesh, two layers of brass mesh bolus, three layers of brass mesh bolus, and 0.5 cm tissue-equivalent (TE) bolus. Exit dose was measured at a phantom thickness of 10 cm. Beam profiles were measured at phantom depths of 0 cm and 10 cm. All dosimetry was performed for 4, 6, and 10 MV photon beams using a linear accelerator. RESULTS: The surface dose at a phantom depth of 0 cm increased to 37.3%, 36.3%, and 31.0% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The surface dose decreased with one layer of brass mesh bolus compared to that with the 0.5 cm TE bolus. On the other hand, the exit dose increased to 22.0%, 23.1%, and 22.8% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The beam profile at the depth of 0 cm showed oscillations, and the difference between the maximum and minimum doses was up to 13.1% with one layer of brass mesh bolus. CONCLUSION: It was suggested that the brass mesh bolus not only increases the surface dose but also has different properties from the conventional TE bolus.

Multi-Institutional Study of End-to-End Dose Delivery Quality Assurance Testing for Image-Guided Brachytherapy Using a Gel Dosimeter.

PURPOSE: To quantify dose delivery errors for high-dose-rate image-guided brachytherapy (HDR-IGBT) using an independent end-to-end dose delivery quality assurance test at multiple institutions. The novelty of our study is that this is the first multi-institutional end-to-end dose delivery study in the world. MATERIALS AND METHODS: The postal audit used a polymer gel dosimeter in a cylindrical acrylic container for the afterloading system. Image acquisition using computed tomography, treatment planning, and irradiation were performed at each institution. Dose distribution comparison between the plan and gel measurement was performed. The percentage of pixels satisfying the absolute-dose gamma criterion was reviewed. RESULTS: Thirty-five institutions participated in this study. The dose uncertainty was 3.6% ± 2.3% (mean ± 1.96σ). The geometric uncertainty with a coverage factor of k = 2 was 3.5 mm. The tolerance level was set to the gamma passing rate of 95% with the agreement criterion of 5% (global)/3 mm, which was determined from the uncertainty estimation. The percentage of pixels satisfying the gamma criterion was 90.4% ± 32.2% (mean ± 1.96σ). Sixty-six percent (23/35) of the institutions passed the verification. Of the institutions that failed the verification, 75% (9/12) had incorrect inputs of the offset between the catheter tip and indexer length in treatment planning and 17% (2/12) had incorrect catheter reconstruction in treatment planning. CONCLUSIONS: The methodology should be useful for comprehensively checking the accuracy of HDR-IGBT dose delivery and credentialing clinical studies. The results of our study highlight the high risk of large source positional errors while delivering dose for HDR-IGBT in clinical practices.

Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis.

OBJECTIVES: We aimed to explore the synergistic combination of a topologically invariant Betti number (BN)-based signature and a biomarker for the accurate prediction of symptomatic (grade ≥2) radiation-induced pneumonitis (RP+) before stereotactic ablative radiotherapy (SABR) for lung cancer. METHODS: A total of 272 SABR cases with early-stage non-small cell lung cancer were chosen for this study. The occurrence of RP+ was predicted using a support vector machine (SVM) model trained with the combined features of the BN-based signature extracted from planning computed tomography (pCT) images and a pretreatment biomarker, serum Krebs von den Lungen-6 (BN+KL-6 model). In all, 242 (20 RP+ and 222 RP-(grade 1)) and 30 cases (8 RP+ and 22 RP-) were used for training and testing the model, respectively. The BN-based features were extracted from BN maps that characterize topologically invariant heterogeneous traits of potential RP+ lung regions on pCT images by applying histogram- and texture-based feature calculations to the maps. The SVM models were built to predict RP+ patients with a BN signature that was constructed based on the least absolute shrinkage and selection operator logistic regression model. The evaluation of the prediction models was performed based on the area under the receiver operating characteristic curves (AUCs) and accuracy in the test. The performance of the BN+KL-6 model was compared to the performance based on the BN, conventional original pCT, and wavelet decomposition (WD) models. RESULTS: The test AUCs obtained for the BN+KL-6, BN, pCT, and WD models were 0.825, 0.807, 0.642, and 0.545, respectively. The accuracies of the BN+KL-6, BN, pCT, and WD models were found to be 0.724, 0.708, 0.591, and 0.534, respectively. CONCLUSION: This study demonstrated the comprehensive performance of the BN+KL-6 model for the prediction of potential RP+ patients before SABR for lung cancer.

Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy.

This study developed a radiomics-based predictive model for radiation-induced pneumonitis (RP) after lung cancer stereotactic body radiation therapy (SBRT) on pretreatment planning computed tomography (CT) images. For the RP prediction models, 275 non-small-cell lung cancer patients consisted of 245 training (22 with grade ≥ 2 RP) and 30 test cases (8 with grade ≥ 2 RP) were selected. A total of 486 radiomic features were calculated to quantify the RP texture patterns reflecting radiation-induced tissue reaction within lung volumes irradiated with more than x Gy, which were defined as LVx. Ten subsets consisting of all 22 RP cases and 22 or 23 randomly selected non-RP cases were created from the imbalanced dataset of 245 training patients. For each subset, signatures were constructed, and predictive models were built using the least absolute shrinkage and selection operator logistic regression. An ensemble averaging model was built by averaging the RP probabilities of the 10 models. The best model areas under the receiver operating characteristic curves (AUCs) calculated on the training and test cohort for LV5 were 0.871 and 0.756, respectively. The radiomic features calculated on pretreatment planning CT images could be predictive imaging biomarkers for RP after lung cancer SBRT.

Observer uncertainties of soft tissue-based patient positioning in IGRT.

PURPOSE: There remain uncertainties due to inter- and intraobserver variability in soft-tissue-based patient positioning even with the use of image-guided radiation therapy (IGRT). This study aimed to reveal observer uncertainties of soft-tissue-based patient positioning on cone-beam computed tomography (CBCT) images for prostate cancer IGRT. METHODS: Twenty-six patients (7-8 fractions/patient, total number of 204 fractions) who underwent IGRT for prostate cancer were selected. Six radiation therapists retrospectively measured prostate cancer location errors (PCLEs) of soft-tissue-based patient positioning between planning CT (pCT) and pretreatment CBCT (pre-CBCT) images after automatic bone-based registration. Observer uncertainties were evaluated based on residual errors, which denoted the differences between soft-tissue and reference positioning errors. Reference positioning errors were obtained as PCLEs of contour-based patient positioning between pCT and pre-CBCT images. Intraobserver variations were obtained from the difference between the first and second soft-tissue-based patient positioning repeated by the same observer for each fraction. Systematic and random errors of inter- and intraobserver variations were calculated in anterior-posterior (AP), superior-inferior (SI), and left-right (LR) directions. Finally, clinical target volume (CTV)-to-planning target volume (PTV) margins were obtained from systematic and random errors of inter- and intraobserver variations in AP, SI, and LR directions. RESULTS: Interobserver variations in AP, SI, and LR directions were 0.9, 0.9, and 0.5 mm, respectively, for the systematic error, and 1.8, 2.2, and 1.1 mm, respectively, for random error. Intraobserver variations were <0.2 mm in all directions. CTV-to-PTV margins in AP, SI, and LR directions were 3.5, 3.8, and 2.1 mm, respectively. CONCLUSION: Intraobserver variability was sufficiently small and would be negligible. However, uncertainties due to interobserver variability for soft-tissue-based patient positioning using CBCT images should be considered in CTV-to-PTV margins.

Assessment of the anatomical position of point B and the relationship between point B dose and the dose delivered to pelvic lymph nodes in CT-based high-dose-rate brachytherapy for uterine cervical cancer.

PURPOSE: To examine the anatomical position of point B and the relationship between the dose at point B and the dose delivered to the pelvic lymph nodes in computed tomography (CT)-based brachytherapy for cervical cancer. MATERIAL AND METHODS: Forty-nine cervical cancer patients were treated at Kyushu University Hospital. For all cases, planning CT images obtained after the applicator insertion were imported to an Oncentra Brachy (Elekta AB, Stockholm, Sweden), and points A (dose prescription, 6 Gy) and points B were set according to the Manchester method. The pelvic lymph node regions (external iliac, internal iliac, and obturator) were contoured, and the anatomic positions of 98 points B in 49 patients were examined. Dose volume histogram (DVH) parameters (D100, D90, D50, D2cc, D1cc, and D0.1cc) were calculated for each lymph node region and compared with the point B dose. RESULTS: The mean bilateral dose to point B was 1.70 ±0.18 Gy, and 26 (27%) of 98 points B were not located in any pelvic lymph node regions. The DVH analysis indicated a low degree of correlation overall, and all values were significantly different from point B doses (p < 0.05), except for D0.1cc of the external iliac node (p = 0.0594) and D1cc of the internal iliac node (p = 0.0711). CONCLUSIONS: We investigated the anatomical location of point B in patients with cervical cancer who underwent brachytherapy, and the DVH analysis revealed that the point B dose was a poor surrogate for the dose delivered to the pelvic lymph nodes.

Dosimetric assessment of a single-energy metal artifact reduction algorithm for computed tomography images in radiation therapy.

This study aimed to evaluate the performance of a single-energy metal artifact reduction (SEMAR) algorithm for radiation therapy treatment using phantom cases with metal inserts, assess improvements in computed tomography (CT) number accuracy, and investigate its effects on treatment planning dosimetry. A standard electron density phantom was scanned with and without metal inserts. The numbers of tissue-equivalent materials on both uncorrected and SEMAR-corrected CT images were compared. Treatment planning accuracy was evaluated by comparing dose distributions computed using true density images (without metal inserts), uncorrected images (with metal inserts), and SEMAR-corrected images (with metal inserts) using three-dimensional gamma analysis. The numbers of the true density and uncorrected and SEMAR-corrected CT images in a muscle plug with unilateral inserts were 25.9 HU, - 281.8 HU, and 26.1 HU, respectively. A similar tendency was obtained for other tissue-equivalent materials, and the numbers on CT images were improved with the SEMAR algorithm. In cases involving 1 portal irradiation, 10-MV X-ray, and the Acuros XB algorithm, the pass ratio between the true density and uncorrected images was 89.89%, while that between the true density and SEMAR-corrected images was 95.03%. Improvements in dose distribution were evident using the SEMAR algorithm. Similar trends were found for different irradiation methods and dose calculation algorithms. The SEMAR algorithm can significantly reduce metal artifacts on CT images used for radiation treatment planning. This aspect influenced dosimetry in the region of the artifact and dose distribution was significantly improved with use of the SEMAR-corrected images.

Comparison of volumetric-modulated arc therapy and intensity-modulated radiation therapy prostate cancer plans accounting for cold spots.

This study compared dosimetric indices of volumetric-modulated arc therapy (VMAT) with intensity-modulated radiation therapy (IMRT) accounting for cold spots in prostate cancer plans. IMRT plans were retrospectively generated from 30 prostate cancer patients with ten cases for each risk group, who received VMAT plans. The mean, maximum, and minimum doses, and conformity and homogeneity indexes were evaluated for planning target volume (PTV) and the mean dose and V20-V70 for organs at risk (OAR) including the rectum, bladder, right and left femoral heads, and rectum overlapped with PTV (ROP) regions. The numbers and volume percentages of cold spots within PTVs and ROP regions were measured using in-house software. Three-dimensional probabilistic distributions of the probability and distributions of cold spots were generated using a centroid matching technique for visualization and analysis. There was a statistically better dose conformity in the PTV, rectum, and bladder dose-sparing in VMAT compared to that in the IMRT plans, whereas VMAT had statistically worse target dose homogeneity, and right and left femoral head dose-sparing than those of the IMRT plans. The average volume percentage of cold spots per PTV for the VMAT was 4.37 ± 2.68%, which was smaller than the 5.72 ± 1.84% observed for IMRT plans (P = 0.007). The volume percentage of cold spots per ROP for the VMAT did not significantly differ from those for the IMRT plans. Compared with IMRT, the VMAT plans achieved better PTV dose conformity, OAR dose-sparing, and smaller cold spots in the treatment of prostate cancer.

Effect of accounting for interfractional CTV shape variations in PTV margins on prostate cancer radiation treatment plans.

PURPOSE: The aim of this study was to account for interfractional clinical target volume (CTV) shape variation and apply this to the planning target volume (PTV) margin for prostate cancer radiation treatment plans. METHODS: Interfractional CTV shape variations were estimated from weekly cone-beam computed tomography (CBCT) images using statistical point distribution models. The interfractional CTV shape variation was taken into account in the van Herk's margin formula. The PTV margins without and with the CTV shape variation, i.e., standard (PTVori) and new (PTVshape) margins, were applied to 10 clinical cases that had weekly CBCT images acquired during their treatment sessions. Each patient was replanned for low-, intermediate-, and high-risk CTVs, using both margins. The dose indices (D98 and V70) of treatment plans with the two margins were compared on weekly pseudo-planning computed tomography (PCT) images, which were defined as PCT images registered using a deformable image registration technique with weekly CBCT images, including contours of the CTV, rectum, and bladder. RESULTS: The percentage of treatment fractions of patients who received CTV D98 greater than 95% of a prescribed dose increased from 80.3 (PTVori) to 81.8% (PTVshape) for low-risk CTVs, 78.8 (PTVori) to 87.9% (PTVshape) for intermediate-risk CTVs, and 80.3 (PTVori) to 87.9% (PTVshape) for high-risk CTVs. In most cases, the dose indices of the rectum and bladder were acceptable in clinical practice. CONCLUSION: The results of this study suggest that interfractional CTV shape variations should be taken into account when determining PTV margins to increase CTV coverages.

Feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy.

This study aimed to investigate the feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy. The relationships between the reference centroids of prostate regions (CPRs) (prostate locations) and anatomical feature points were explored, and the most feasible anatomical feature points were selected based on the smallest location estimation errors of CPRs and the largest Dice's similarity coefficient (DSC) between the reference and extracted prostates. The reference CPRs were calculated according to reference prostate contours determined by radiation oncologists. Five anatomical feature points were manually determined on a prostate, bladder, and rectum in a sagittal plane of a planning computed tomography image for each case. The CPRs were estimated using three machine learning architectures [artificial neural network, random forest, and support vector machine (SVM)], which learned the relationships between the reference CPRs and anatomical feature points. The CPRs were applied for placing a prostate probabilistic atlas at the coordinates and extracting prostate regions using a Bayesian delineation framework. The average estimation errors without and with SVM using three feature points, which indicated the best performance, were 5.6 ± 3.7 mm and 1.8 ± 1.0 mm, respectively (the smallest error) (p < 0.001). The average DSCs without and with SVM using the three feature points were 0.69 ± 0.13 and 0.82 ± 0.055, respectively (the highest DSC) (p < 0.001). The anatomical feature points may be feasible for the estimation of prostate locations, which can be applied to the general Bayesian delineation frameworks for prostate cancer radiotherapy.

[Evaluation of a 2D Diode Array Corresponding to Flattening Filter Free X-ray Beams].

Recently, a medical linear accelerator with a flattening filter free (FFF) mode has led to the use of FFF X-ray beams at clinical sites. The usefulness of FFF X-ray beams in high-precision radiation therapy has been reported. Therefore, the quality assurance and quality control for FFF X-ray beams have become necessary. In this study, the characteristics of the detectors of a newly developed 2-D diode array (MapCHECK2, Sun Nuclear Corporation) for FFF X-ray beams, i.e., dose reproducibility, dose rate dependence, dose linearity, and output factor, were evaluated. For the measurements, 6 and 10 MV FFF beams were used. The results showed that the coefficient of variation for dose reproducibility was within 0.08%, the dose rate dependence was less than 1.0%, the coefficient of determination of dose linearity was found to be R2=1.0, which was high, and the output factor agreed within 2.5% as compared with the farmer ion chamber, diode E, and pinpoint ion chamber for field sizes greater than 2×2 cm2. The results suggested that MapCHECK2 could be a useful tool for quality assurance and quality control for FFF X-ray beams.

Possibility of chest wall dose reduction using volumetric-modulated arc therapy (VMAT) in radiation-induced rib fracture cases: comparison with stereotactic body radiation therapy (SBRT).

The present study compares dosimetric parameters between volumetric-modulated arc therapy (VMAT) and 3D conformal radiation therapy (3D-CRT) in lung tumors adjacent to the chest wall treated with stereotactic body radiation therapy (SBRT). The study focused on the radiation dose to the chest wall of 16 patients who had developed radiation-induced rib fractures (RIRF) after SBRT using 3D-CRT. The targets in all patients were partially overlapping with the fractured ribs, and the median overlapping rib-PTV distance was 0.4 cm. Stereotactic body radiation therapy was re-planned for all patients. The prescribed dose was 48 Gy in four fractions to cover at least 95% of the planning target volume (PTV). Evaluated dosimetric factors included D98% and the conformation number (CN) of the PTV, the D2cm3, V40 and V30 of the fractured ribs, the V30 of the chest wall, and the Dmean, V20 and V5 of the lung. A comparison of 3D-CRT with the VMAT plan for PTV revealed that CN was significantly improved in the VMAT plan, whereas D98% did not significantly differ between the two plans. Regarding organs at risk (OARs), the D2cm3, V40 and V30 of fractured ribs, the V30 of the chest wall, and the Dmean, V20 and V5 of the lung, were significantly decreased in the VMAT plan. We concluded that the dose to OARs such as ribs and chest wall could be reduced with improved target conformity using VMAT instead of 3D-CRT for SBRT to treat peripheral lung tumors.

Computational analysis of interfractional anisotropic shape variations of the rectum in prostate cancer radiation therapy.

PURPOSE: To analyze the uncertainties of the rectum due to anisotropic shape variations by using a statistical point distribution model (PDM). MATERIALS AND METHODS: The PDM was applied to the rectum contours that were delineated on planning computed tomography (CT) and cone-beam CT (CBCT) at 80 fractions of 11 patients. The standard deviations (SDs) of systematic and random errors of the shape variations of the whole rectum and the region in which the rectum overlapped with the PTV (ROP regions) were derived from the PDMs at all fractions of each patient. The systematic error was derived by using the PDMs of planning and average rectum surface determined from rectum surfaces at all fractions, while the random error was derived by using a PDM-based covariance matrix at all fractions of each patient. RESULTS: Regarding whole rectum, the population SDs were larger than 1.0 mm along all directions for random error, and along the anterior, superior, and inferior directions for systematic error. The deviation is largest along the superior and inferior directions for systematic and random errors, respectively. For ROP regions, the population SDs of systematic error were larger than 1.0 mm along the superior and inferior directions. The population SDs of random error for the ROP regions were larger than 1.0 mm except along the right and posterior directions. CONCLUSIONS: The anisotropic shape variations of the rectum, especially in the ROP regions, should be considered when determining a planning risk volume (PRV) margins for the rectum associated with the acute toxicities.

Exploration of temporal stability and prognostic power of radiomic features based on electronic portal imaging device images.

PURPOSE: We aimed to explore the temporal stability of radiomic features in the presence of tumor motion and the prognostic powers of temporally stable features. METHODS: We selected single fraction dynamic electronic portal imaging device (EPID) (n = 275 frames) and static digitally reconstructed radiographs (DRRs) of 11 lung cancer patients, who received stereotactic body radiation therapy (SBRT) under free breathing. Forty-seven statistical radiomic features, which consisted of 14 histogram-based features and 33 texture features derived from the graylevel co-occurrence and graylevel run-length matrices, were computed. The temporal stability was assessed by using a multiplication of the intra-class correlation coefficients (ICCs) between features derived from the EPID and DRR images at three quantization levels. The prognostic powers of the features were investigated using a different database of lung cancer patients (n = 221) based on a Kaplan-Meier survival analysis. RESULTS: Fifteen radiomic features were found to be temporally stable for various quantization levels. Among these features, seven features have shown potentials for prognostic prediction in lung cancer patients. CONCLUSIONS: This study suggests a novel approach to select temporally stable radiomic features, which could hold prognostic powers in lung cancer patients.

Investigation of interfractional shape variations based on statistical point distribution model for prostate cancer radiation therapy.

PURPOSE: The setup errors and organ motion errors pertaining to clinical target volume (CTV) have been considered as two major causes of uncertainties in the determination of the CTV-to-planning target volume (PTV) margins for prostate cancer radiation treatment planning. We based our study on the assumption that interfractional target shape variations are not negligible as another source of uncertainty for the determination of precise CTV-to-PTV margins. Thus, we investigated the interfractional shape variations of CTVs based on a point distribution model (PDM) for prostate cancer radiation therapy. MATERIALS AND METHODS: To quantitate the shape variations of CTVs, the PDM was applied for the contours of 4 types of CTV regions (low-risk, intermediate- risk, high-risk CTVs, and prostate plus entire seminal vesicles), which were delineated by considering prostate cancer risk groups on planning computed tomography (CT) and cone beam CT (CBCT) images of 73 fractions of 10 patients. The standard deviations (SDs) of the interfractional random errors for shape variations were obtained from covariance matrices based on the PDMs, which were generated from vertices of triangulated CTV surfaces. The correspondences between CTV surface vertices were determined based on a thin-plate spline robust point matching algorithm. The systematic error for shape variations was defined as the average deviation between surfaces of an average CTV and planning CTVs, and the random error as the average deviation of CTV surface vertices for fractions from an average CTV surface. RESULTS: The means of the SDs of the systematic errors for the four types of CTVs ranged from 1.0 to 2.0 mm along the anterior direction, 1.2 to 2.6 mm along the posterior direction, 1.0 to 2.5 mm along the superior direction, 0.9 to 1.9 mm along the inferior direction, 0.9 to 2.6 mm along the right direction, and 1.0 to 3.0 mm along the left direction. Concerning the random errors, the means of the SDs ranged from 0.9 to 1.2 mm along the anterior direction, 1.0 to 1.4 mm along the posterior direction, 0.9 to 1.3 mm along the superior direction, 0.8 to 1.0 mm along the inferior direction, 0.8 to 0.9 mm along the right direction, and 0.8 to 1.0 mm along the left direction. CONCLUSIONS: Since the shape variations were not negligible for intermediate and high-risk CTVs, they should be taken into account for the determination of the CTV-to-PTV margins in radiation treatment planning of prostate cancer.

Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy.

PURPOSE: To investigate the feasibility of differential geometry features in the detection of anatomical feature points on a patient surface in infrared-ray-based range images in image-guided radiation therapy. METHODS: The key technology was to reconstruct the patient surface in the range image, i.e., point distribution with three-dimensional coordinates, and characterize the geometrical shape at every point based on curvature features. The region of interest on the range image was extracted by using a template matching technique, and the range image was processed for reducing temporal and spatial noise. Next, a mathematical smooth surface of the patient was reconstructed from the range image by using a non-uniform rational B-splines model. The feature points were detected based on curvature features computed on the reconstructed surface. The framework was tested on range images acquired by a time-of-flight (TOF) camera and a Kinect sensor for two surface (texture) types of head phantoms A and B that had different anatomical geometries. The detection accuracy was evaluated by measuring the residual error, i.e., the mean of minimum Euclidean distances (MMED) between reference (ground truth) and detected feature points on convex and concave regions. RESULTS: The MMEDs obtained using convex feature points for range images of the translated and rotated phantom A were [Formula: see text] and [Formula: see text], respectively, using the TOF camera. For the phantom B, the MMEDs of the convex and concave feature points were [Formula: see text] and [Formula: see text] mm, respectively, using the Kinect sensor. There was a statistically significant difference in the decreased MMED for convex feature points compared with concave feature points [Formula: see text]. CONCLUSIONS: The proposed framework has demonstrated the feasibility of differential geometry features for the detection of anatomical feature points on a patient surface in range image-guided radiation therapy.