Monocyte-to-lymphocyte ratio is a prognostic predictor for patients with non-small cell lung cancer treated with stereotactic body radiation therapy.

Background: The monocyte-to-lymphocyte ratio (MLR), a systemic inflammation biomarker, has been shown to predict patient outcomes in several types of cancer. This study aimed to determine the association between MLR and local control (LC) and cause-specific survival (CSS) rates in patients with non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT). Materials and methods: The median age of the 194 included participants (144 men, 50 women) was 80 (range, 50-96) years. The median follow-up period was 19 (range, 1-108) months. The LC and CSS rates were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazard regression models were used to estimate the LC and CSS rates. Results: Local recurrence was observed in 25 patients during the follow-up. Univariate Cox proportional hazards regression analysis revealed that MLR, performance status, and tumor diameter were significant factors for LC. Multivariate analysis showed MLR and tumor diameter as significant factors (p = 0.041 and 0.031, respectively). The 1- and 2-year LC rates for the lower and higher MLR groups were 97.5% and 97.5%, and 89.7% and 81.2%, respectively. During the follow-up period, 14 patients died due to NSCLC. Although MLR tended to predict CSS in univariate analysis (p = 0.086), none of the parameters was significant in predicting CSS. However, MLR as a continuous variable was a significant factor for CSS in the univariate analysis (p = 0.004). Conclusions: Our data suggest that MLR is correlated with LC and CSS rates in NSCLC patients treated with SBRT.

Assessing tumor volumetric reduction with consideration for setup errors based on mathematical tumor model and microdosimetric kinetic model in single-isocenter VMAT for brain metastases.

The volumetric reduction rate (VRR) was evaluated with consideration for six degrees-of-freedom (6DoF) patient setup errors based on a mathematical tumor model in single-isocenter volumetric modulated arc therapy (SI-VMAT) for brain metastases. Simulated gross tumor volumes (GTV) of 1.0 cm and dose distribution were created (27 Gy/3 fractions). The distance between the GTV center and isocenter (d) was set at 0-10 cm. The GTV was translated within 0-1.0 mm (Trans) and rotated within 0-1.0° (Rot) in the three axis directions using affine transformation. The tumor growth volume was calculated using a multicomponent mathematical model (MCTM), and lethal effects of irradiation and repair from damage during irradiation were calculated by a microdosimetric kinetic model (MKM) for non-small cell lung cancer (NSCLC) A549 and NCI-H460 (H460) cells. The VRRs were calculated 5 days after the end of irradiation using the physical dose to the GTV for varying d and 6DoF setup errors. The tolerance value of VRR, the GTV volume reduction rate, was set at 5%, based on the pre-irradiation GTV volume. With the exception of the only one A549 condition where (Trans, Rot) = (1.0 mm, 1.0°) was repeated for 3 fractions, all conditions met all the tolerance VRR values for A549 and H460 cells with varying d from 0 to 10 cm. Evaluation based on the mathematical tumor model suggested that if the 6DoF setup errors at each irradiation could be kept within 1.0 mm and 1.0°, there would be little effect on tumor volume regardless of the distance from the isocenter in SI-VMAT.

Biomechanical imaging biomarker during chemoradiotherapy predicts treatment response in head and neck squamous cell carcinoma.

Objective. For response-adapted adaptive radiotherapy (R-ART), promising biomarkers are needed to predict post-radiotherapy (post-RT) responses using routine clinical information obtained during RT. In this study, a patient-specific biomechanical model (BM) of the head and neck squamous cell carcinoma (HNSCC) was proposed using the pre-RT maximum standardized uptake value (SUVmax) of18F-fluorodeoxyglucose (FDG) and tumor structural changes during RT as evaluated using computed tomography (CT). In addition, we evaluated the predictive performance of BM-driven imaging biomarkers for the treatment response of patients with HNSCC who underwent concurrent chemoradiotherapy (CCRT).Approach. Patients with histologically confirmed HNSCC treated with definitive CCRT were enrolled in this study. All patients underwent CT two times as follows: before the start of RT (pre-RT) and 3 weeks after the start of RT (mid-RT). Among these patients, 67 patients who underwent positron emission tomography/CT during the pre-RT period were included in the final analysis. The locoregional control (LC), progression-free survival (PFS), and overall survival (OS) prediction performances of whole tumor stress change (TS) between pre- and mid-RT computed using BM were assessed using univariate, multivariate, and Kaplan-Meier survival curve analyses, respectively. Furthermore, performance was compared with the pre and post-RT SUVmax, tumor volume reduction rate (TVRR) during RT, and other clinical prognostic factors.Main results. For both univariate, multivariate, and survival curve analyses, the significant prognostic factors were as follows (p< 0.05): TS and TVRR for LC; TS and pre-RT FDG-SUVmaxfor PFS; and TS only for OS. In addition, for 2 year LC, PFS, and OS prediction, TS showed a comparable predictive performance to post-RT FDG-SUVmax.Significance. BM-driven TS is an effective prognostic factor for tumor treatment response after CCRT. The proposed method can be a feasible functional imaging biomarker that can be acquired during RT using only routine clinical data and may provide useful information for decision-making during R-ART.

Deep inspiration breath hold real-time tumor-tracking radiation therapy (DBRT) as a novel stereotactic body radiation therapy approach for lung tumors.

Radiotherapy with deep inspiration breath hold (DIBH) reduces doses to the lungs and organs at risk. The stability of breath holding and reproducibility of tumor location are higher during expiration than during inspiration; therefore, we developed an irradiation method combining DIBH and real-time tumor-tracking radiotherapy (RTRT) (DBRT). Nine patients were enrolled in this study. Fiducial markers were placed near tumors using bronchoscopy. Treatment planning computed tomography (CT) was performed thrice during DIBH, assisted by spirometer-based device. Each CT scan was fused using fiducial markers. Gross tumor volume (GTV) was contoured for each dataset and summed to create GTVsum; adding a 5-mm margin around GTVsum generated the planning target volume. The prescribed dose was mainly 42 Gy in four fractions. The treatment plan was created using DIBH CT (DBRT-plan), with a similar treatment plan created for expiratory CT for cases for which DBRT could not be performed (conv-plan). Vx defined as the volume of the lung received x Gy, and the mean lung dose, V20, V10, and V5 were evaluated. DBRT was completed in all patients. Mean dose, V20, and V10 were significantly lower in the DBRT-plan than in the conv-plan (all p = 0.003). Mean rates of decrease for mean dose, V20, and V10 were 14.0%, 27.6%, and 19.1%, respectively. No significant difference was observed in V5. We developed DBRT, a stereotactic body radiation therapy performed with the DIBH technique; it combines a spirometer-based breath-hold support system with an RTRT system. All patients who underwent DBRT completed the procedure without any technical or mechanical complications. This is a promising methodology that may significantly reduce lung doses.

Intra- and inter-fractional variations of tumors with fiducial markers measured using respiratory-correlated computed tomography images for respiratory gated lung stereotactic body radiation therapy.

PURPOSE: This study evaluated the intra- and inter-fractional variation of tumors with fiducial markers (FMs), relative to the tumor-FM distance, to establish how close an FM should be inserted for respiratory-gated stereotactic body radiation therapy (RG-SBRT). METHODS: Forty-five lung tumors treated with RG-SBRT were enrolled. End-expiratory computed tomography (CT) (CTplan) and four-dimensional-CT (4D-CT) scans were obtained for planning. End-expiratory CT (CTfr) scanning was performed before each fraction. The FMs were divided into two groups based on the median tumor-FM distance in the CTplan (Dp). For the intra-fractional variation, the correlations between the corresponding tumor and FM intra-fractional motions, defined as the centroid coordinates of those in each 0-90% phase, with the 50% phase of 4D-CT as the origin, were calculated in the left-right, anterior-posterior, and superior-inferior directions. Furthermore, the maximum difference in the tumor-FM distance in each phase of 4D-CT scan, based on those in the 50% phase of 4D-CT scan (Dmax), was obtained. Inter-fractional variation was defined as the maximum distance between the tumors in CTplan and CTfr, when the CT scans were fused based on each FM or vertebra. RESULTS: The median Dp was 26.1 mm. While FM intra-fractional motions were significantly and strongly correlated with the tumor intra-fractional motions in only anterior-posterior and superior-inferior directions for the Dp > 26 mm group, they were significantly and strongly correlated in all directions for the Dp ≤ 26 mm group. In all directions, Dmax values of the Dp ≤ 26 mm group were lower than those of the Dp > 26 mm group. The inter-fractional variations based on the Dp ≤ 26 mm were smaller than those on the Dp > 26 mm and on the vertebra in all directions. CONCLUSIONS: Regarding intra- and inter-fractional variation, FMs for Dp ≤ 26 mm can increase the accuracy for RG-SBRT.

Pseudo dual-energy CT-derived iodine mapping using single-energy CT data based on a convolution neural network.

Objective: The objectives of this study are: (1) to develop a convolutional neural network model that yields pseudo high-energy CT (CTpseudo_high) from simple image processed low-energy CT (CTlow) images, and (2) to create a pseudo iodine map (IMpseudo) and pseudo virtual non-contrast (VNCpseudo) images for thoracic and abdominal regions. Methods: Eighty patients who underwent dual-energy CT (DECT) examinations were enrolled. The data obtained from 55, 5, and 20 patients were used for training, validation, and testing, respectively. The ResUnet model was used for image generation model and was trained using CTlow and high-energy CT (CThigh) images. The proposed model performance was evaluated by calculating the CT values, image noise, mean absolute errors (MAEs), and histogram intersections (HIs). Results: The mean difference in the CT values between CTpseudo_high and CThigh images were less than 6 Hounsfield unit (HU) for all evaluating patients. The image noise of CTpseudo_high was significantly lower than that of CThigh. The mean MAEs was less than 15 HU, and HIs were almost 1.000 for all the patients. The evaluation metrics of IM and VNC exhibited the same tendency as that of the comparison between CTpseudo_high and CThigh images. Conclusions: Our results indicated that the proposed model enables to obtain the DECT images and material-specific images from only single-energy CT images. Advances in knowledges: We constructed the CNN-based model which can generate pseudo DECT image and DECT-derived material-specific image using only simple image-processed CTlow images for the thoracic and abdominal regions.

Immune Checkpoint Inhibitors after Radiation Therapy Improve Overall Survival Rates in Patients with Stage IV Lung Cancer.

This exploratory and retrospective study aimed to evaluate whether there is a difference in the overall survival (OS) rates of patients with stage IV lung cancer who underwent radiation therapy (RT) depending on the presence or absence of immune checkpoint inhibitors (ICIs) and the timing of their use. Eighty patients with histologically confirmed stage IV lung cancer were enrolled, and ICIs were administered to thirty (37.5%). ICIs were administered before RT and after RT in 11 and 20 patients, respectively. The median follow-up period was 6 (range: 1-37) months. Patients treated with ICIs had significantly better OS rates than those not treated with ICIs (p < 0.001). The 6-month OS rates in patients treated with and without ICIs were 76.3% and 34.5%, respectively. The group that received ICI therapy after RT had a significantly better OS rate than the group that received ICI therapy prior to RT (6-month OS: 94.7% vs. 40.0%, p < 0.001). In the multivariate analysis, performance status (0-1 vs. 2-4) and ICI use after RT were significant factors for OS (p = 0.032 and p < 0.001, respectively). Our results suggest that ICI administration after RT may prolong the OS of patients with stage IV lung cancer.

Mathematical model combined with microdosimetric kinetic model for tumor volume calculation in stereotactic body radiation therapy.

We proposed a new mathematical model that combines an ordinary differential equation (ODE) and microdosimetric kinetic model (MKM) to predict the tumor-cell lethal effect of Stereotactic body radiation therapy (SBRT) applied to non-small cell lung cancer (NSCLC). The tumor growth volume was calculated by the ODE in the multi-component mathematical model (MCM) for the cell lines NSCLC A549 and NCI-H460 (H460). The prescription doses 48 Gy/4 fr and 54 Gy/3 fr were used in the SBRT, and the effect of the SBRT on tumor cells was evaluated by the MKM. We also evaluated the effects of (1) linear quadratic model (LQM) and the MKM, (2) varying the ratio of active and quiescent tumors for the total tumor volume, and (3) the length of the dose-delivery time per fractionated dose (tinter) on the initial tumor volume. We used the ratio of the tumor volume at 1 day after the end of irradiation to the tumor volume before irradiation to define the radiation effectiveness value (REV). The combination of MKM and MCM significantly reduced REV at 48 Gy/4 fr compared to the combination of LQM and MCM. The ratio of active tumors and the prolonging of tinter affected the decrease in the REV for A549 and H460 cells. We evaluated the tumor volume considering a large fractionated dose and the dose-delivery time by combining the MKM with a mathematical model of tumor growth using an ODE in lung SBRT for NSCLC A549 and H460 cells.

Assessing four-dimensional CT stress maps derived from patient-specific biomechanical models of the lung with pulmonary function test data in lung cancer patients.

OBJECTIVE: This study aims to retrospectively compare the stress map of the lung with pulmonary function test (PFT) results in lung cancer patients and to evaluate the potential of the stress map as an imaging biomarker for chronic obstructive pulmonary disease (COPD). METHODS: 25 lung cancer patients with pre-treatment four-dimensional CT (4DCT) and PFT data were retrospectively analysed. PFT metrics were used to diagnose obstructive lung disease. For each patient, forced expiratory volume in 1 s (FEV1 % predicted) and the ratio of FEV1 and forced vital capacity (FEV1/FVC) were recorded. 4DCT and biomechanical model-deformable image registration (BM-DIR) were used to obtain the lung stress map. The relationship between the mean of the total lung stress and PFT data was evaluated, and the COPD classification grade was also evaluated. RESULTS: The mean values of the total lung stress and FEV1 % predicted showed a significant strong correlation [R = 0.833, (p < 0.001)]. The mean values and FEV1/FVC showed a significant strong correlation [R = 0.805, (p < 0.001)]. For the total lung stress, the area under the curve and the optimal cut-off value were 0.94 and 510.8 Pa for the classification of normal or abnormal lung function, respectively. CONCLUSION: This study has demonstrated the potential of lung stress maps based on BM-DIR to accurately assess lung function by comparing them with PFT data. ADVANCES IN KNOWLEDGE: The derivation of stress map directly from 4DCT is novel method. The BM-DIR-based lung stress map can provide an accurate assessment of lung function.

Investigation of the combination of intratumoral and peritumoral radiomic signatures for predicting epidermal growth factor receptor mutation in lung adenocarcinoma.

PURPOSE: We investigated optimal peritumoral size and constructed predictive models for epidermal growth factor receptor (EGFR) mutation. METHODS: A total of 164 patients with lung adenocarcinoma were retrospectively analyzed. Radiomic signatures for the intratumoral region and combinations of intratumoral and peritumoral regions (3, 5, and 7 mm) from computed tomography images were extracted using analysis of variance and least absolute shrinkage. The optimal peritumoral region was determined by radiomics score (rad-score). Intratumoral radiomic signatures with clinical features (IRS) were used to construct predictive models for EGFR mutation. Combinations of intratumoral and 3, 5, or 7 mm-peritumoral signatures with clinical features (IPRS3, IPRS5, and IPRS7, respectively) were also used to construct predictive models. Support vector machine (SVM), logistic regression (LR), and LightGBM models with five-fold cross-validation were constructed, and the receiver operating characteristics were evaluated. Area under the curve (AUC) of the training and test cohorts values were calculated. Brier scores (BS) and decision curve analysis (DCA) were used to evaluate the predictive models. RESULTS: The AUC values of the SVM, LR, and LightGBM models derived from IRS were 0.783 (95% confidence interval: 0.602-0.956), 0.789 (0.654-0.927), and 0.735 (0.613-0.958) for training, and 0.791 (0.641-0.920), 0.781 (0.538-0.930), and 0.734 (0.538-0.930) for test cohort, respectively. Rad-score confirmed that the 3 mm-peritumoral size was optimal (IPRS3), and AUCs values of SVM, LR, and lightGBM models derived from IPRS3 were 0.831 (0.666-0.984), 0.804 (0.622-0.908), and 0.769 (0.628-0.921) for training and 0.765 (0.644-0.921), 0.783 (0.583-0.921), and 0.796 (0.583-0.949) for test cohort, respectively. The BS and DCA of the LR and LightGBM models derived from IPRS3 were better than those from IRS. CONCLUSION: Accordingly, the combination of intratumoral and 3 mm-peritumoral radiomic signatures may be helpful for predicting EGFR mutations.

Multicomponent mathematical model for tumor volume calculation with setup error using single-isocenter stereotactic radiotherapy for multiple brain metastases.

We evaluated the tumor residual volumes considering six degrees-of-freedom (6DoF) patient setup errors in stereotactic radiotherapy (SRT) with multicomponent mathematical model using single-isocenter irradiation for brain metastases. Simulated spherical gross tumor volumes (GTVs) with 1.0 (GTV 1), 2.0 (GTV 2), and 3.0 (GTV 3)-cm diameters were used. The distance between the GTV center and isocenter (d) was set at 0-10 cm. The GTV was simultaneously translated within 0-1.0 mm (T) and rotated within 0°-1.0° (R) in the three axis directions using affine transformation. We optimized the tumor growth model parameters using measurements of non-small cell lung cancer cell lines' (A549 and NCI-H460) growth. We calculated the GTV residual volume at the irradiation's end using the physical dose to the GTV when the GTV size, d, and 6DoF setup error varied. The d-values that satisfy tolerance values (10%, 35%, and 50%) of the GTV residual volume rate based on the pre-irradiation GTV volume were determined. The larger the tolerance value set for both cell lines, the longer the distance to satisfy the tolerance value. In GTV residual volume evaluations based on the multicomponent mathematical model on SRT with single-isocenter irradiation, the smaller the GTV size and the larger the distance and 6DoF setup error, the shorter the distance that satisfies the tolerance value might need to be.

Comparison of the radiomics-based predictive models using machine learning and nomogram for epidermal growth factor receptor mutation status and subtypes in lung adenocarcinoma.

The purpose of this study is to develop the predictive models for epidermal growth factor receptor (EGFR) mutation status and subtypes [exon 21-point mutation (L858R) and exon 19 deletion mutation (19Del)] and evaluate their clinical usefulness. Total 172 patients with lung adenocarcinoma were retrospectively analyzed. The analysis of variance and the least absolute shrinkage were used for feature selection from plain computed tomography images. Then, radiomic score (rad-score) was calculated for the training and test cohorts. Two machine learning (ML) models with 5-fold were applied to construct the predictive models with rad-score, clinical features, and the combination of rad-score and clinical features. The nomogram was developed using rad-score and clinical features. The prediction performance was evaluated by the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis (DCA) was performed using the best ML and nomogram models. In the test cohorts, the AUC of the best ML and the nomogram model were 0.73 (95% confidence interval, 0.59-0.87) and 0.79 (0.65-0.92) in the EGFR mutation groups, 0.83 (0.67-0.99) and 0.85 (0.72-0.97) in the L858R mutation groups, as well as 0.77 (0.58-0.97) and 0.77 (0.60-0.95) in the 19Del groups. The DCA showed that the nomogram models have comparable results with ML models. We constructed two predictive models for EGFR mutation status and subtypes. The nomogram models had comparable results to the ML models. Because the superiority of the performance of ML and nomogram models varied depending on the prediction groups, appropriate model selection is necessary.

Differences in Radiosensitivity According to EGFR Mutation Status in Non-Small Cell Lung Cancer: A Clinical and In Vitro Study.

Unlike drug selection, radiation parameters (field, dose) are not based on driver gene mutations in patients with metastatic non-small cell lung cancer (NSCLC). This study aimed to compare radiosensitivity in NSCLC with and without EGFR driver gene mutations using clinical and in vitro data. The clinical study included 42 patients who underwent whole-brain radiotherapy for brain metastases from NSCLC; of these, 13 patients had EGFR mutation-positive tumors. The Kaplan-Meier method was used to calculate the cranial control rate without intracranial recurrence. In the in vitro study, colony formation and double-strand DNA breaks were examined in two EGFR mutation-negative and three EGFR mutation-positive NSCLC-derived cell lines. Colony formation was assessed 14 days after irradiation with 0 (control), 2, 4, or 8 Gy. DNA double-strand breaks were evaluated 0.5 and 24 h after irradiation. EGFR mutation-positive patients had a significantly better cranial control rates than EGFR mutation-negative patients (p = 0.021). EGFR mutation-positive cells formed significantly fewer colonies after irradiation with 2 or 4 Gy than EGFR mutation-negative cells (p = 0.002, respectively) and had significantly more DNA double-strand breaks at 24 h after irradiation (p < 0.001). Both clinical and in vitro data suggest that EGFR mutation-positive NSCLC is radiosensitive.

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.

Assessing liver fibrosis distribution through liver elasticity estimates obtained using a biomechanical model of respiratory motion with magnetic resonance elastography.

Objective. This study aimed to produce a three-dimensional liver elasticity map using the finite element method (FEM) and respiration-induced motion captured by T1-weighted magnetic resonance images (FEM-E-map) and to evaluate whether FEM-E-maps can be an imaging biomarker comparable to magnetic resonance elastography (MRE) for assessing the distribution and severity of liver fibrosis.Approach. We enrolled 14 patients who underwent MRI and MRE. T1-weighted MR images were acquired during shallow inspiration and expiration breath-holding, and the displacement vector field (DVF) between two images was calculated using deformable image registration. FEM-E-maps were constructed using FEM and DVF. First, three Poisson's ratio settings (0.45, 0.49, and 0.499995) were validated and optimized to minimize the difference in liver elasticity between the FEM-E-map and MRE. Then, the whole and regional liver elasticity values estimated using FEM-E-maps were compared with those obtained from MRE using Pearson's correlation coefficients. Spearman rank correlations and chi-square histograms were used to compare the voxel-level elasticity distribution.Main results. The optimal Poisson's ratio was 0.49. Whole liver elasticity estimated using FEM-E-maps was strongly correlated with that measured using MRE (r = 0.96). For regional liver elasticity, the correlation was 0.84 for the right lobe and 0.82 for the left lobe. Spearman analysis revealed a moderate correlation for the voxel-level elasticity distribution between FEM-E-maps and MRE (0.61 ± 0.10). The small chi-square distances between the two histograms (0.11 ± 0.07) indicated good agreement.Significance. FEM-E-maps represent a potential imaging biomarker for visualizing the distribution of liver fibrosis using only T1-weighted images obtained with a common MR scanner, without any additional examination or special elastography equipment. However, additional studies including comparisons with biopsy findings are required to verify the reliability of this method for clinical application.

Predicting programmed death-ligand 1 expression level in non-small cell lung cancer using a combination of peritumoral and intratumoral radiomic features on computed tomography.

In this study, we investigated the possibility of predicting expression levels of programmed death-ligand 1 (PD-L1) using radiomic features of intratumoral and peritumoral tumors on computed tomography (CT) images. We retrospectively analyzed 161 patients with non-small cell lung cancer. We extracted radiomic features for intratumoral and peritumoral regions on CT images. The null importance, least absolute shrinkage, and selection operator model were used to select the optimized feature subset to build the prediction models for the PD-L1 expression level. LightGBM with five-fold cross-validation was used to construct the prediction model and evaluate the receiver operating characteristics. The corresponding area under the curve (AUC) was calculated for the training and testing cohorts. The proportion of ambiguously clustered pairs was calculated based on consensus clustering to evaluate the validity of the selected features. In addition, Radscore was calculated for the training and test cohorts. For expression level of PD-L1 above 1%, prediction models that included radiomic features from the intratumoral region and a combination of radiomic features from intratumoral and peritumoral regions yielded an AUC of 0.83 and 0.87 and 0.64 and 0.74 in the training and test cohorts, respectively. In contrast, the models above 50% prediction yielded an AUC of 0.80, 0.97, and 0.74, 0.83, respectively. The selected features were divided into two subgroups based on PD-L1 expression levels≥50% or≥1%. Radscore was statistically higher for subgroup one than subgroup two when radiomic features for intratumoral and peritumoral regions were combined. We constructed a predictive model for PD-L1 expression level using CT images. The model using a combination of intratumoral and peritumoral radiomic features had a higher accuracy than the model with only intratumoral radiomic features.

Anemia is a Prognostic Factor for Overall Survival Rate in Patients with Non-Small Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy.

PURPOSE: Anemia has been associated with poor prognosis in patients with cancer across several cancer types. It has been identified as a prognostic factor in patients with non-small cell lung cancer (NSCLC) who have undergone surgery or chemoradiotherapy. However, there are only a few reports that have evaluated the prognostic significance of anemia in patients with NSCLC undergoing stereotactic body radiation therapy (SBRT). PATIENTS AND METHODS: A total of 77 patients were enrolled in this study. The pretreatment hemoglobin (Hb) levels, within 2 weeks before SBRT, were available for all patients. The median age of the participants (56 men, 21 women) was 80 (range, 50-90) years. The median Hb level was 12.8 (range, 7.8-18.3) g/dL. The median follow-up period was 24 (range, 1-87) months. RESULTS: Local recurrence was observed in 8 (10.4%) cases during the follow-up period. The 1- and 2-year local control (LC) rates were 94.8% and 86.4%, respectively. Seventeen (22.1%) patients died during the follow-up period. The 1- and 2-year overall survival (OS) rates were 93.1% and 85.2%, respectively. Univariate analysis identified anemia and body mass index as significant prognostic factors for predicting OS. On multivariate analysis, anemia was confirmed to be the only significant factor (p = 0.02469). CONCLUSION: Our data suggest that anemia is a prognostic factor for predicting the OS rate in patients with early-stage NSCLC treated with SBRT.

Implementation of six degree-of-freedom high-precision robotic phantom on commercial industrial robotic manipulator.

This technical note discloses our implementation of a six degree-of-freedom (DOF) high-precision robotic phantom on a commercially available industrial robot manipulator. These manipulators are designed to optimize their set point tracking accuracy as it is the most important performance metric for industrial manipulators. Their in-house controllers are tuned to suppress its error less than a few tens of micrometers. However, the use of industrial robot manipulators in six DOF robotic phantom can be a difficult problem since their in-house controller are not optimized for continuous path tracking in general. Although instantaneous tracking error in a continuous path tracking task will not exceed five millimeters during motion with the in-house controller, it seriously matters for a robotic phantom, as the tracking error should remain within one millimeter in three dimensional space for all time during motion. The difficulty of the task is further increased since the reference trajectory of a robotic phantom, which is a six DOF tumor motion of a patient, cannot be as smooth as the ones used in factories. The present study presents a feedforward controller for a feedback-controlled industrial six DOF robotic manipulator to be used as a six DOF robotic phantom to drive the water equivalent phantom (WEP). We first trained a set of six recurrent neural networks (RNNs) to capture the six DOF input/output behavior of the robotic manipulator controlled by its in-house controller, and we proceed to formulate an iterative learning control (ILC) using the trained model to generate an augmented reference trajectory for a specific patient that enables very high tracking accuracy to that trajectory. Experimental evaluation results demonstrate clear improvements in the accuracy of the proposed robotic phantom compared to our previous robotic phantom, which uses the same manipulator but is driven by a different corrected reference trajectory.

Estimation of liver elasticity using the finite element method and four-dimensional computed tomography images as a biomarker of liver fibrosis.

PURPOSE: Current radiotherapy planning procedures are generally designed based on anatomical information only and use computed tomography (CT) images that do not incorporate organ-functional information. In this study, we developed a method for estimating liver elasticity using the finite element method (FEM) and four-dimensional CT (4DCT) images acquired during radiotherapy planning, and we subsequently evaluated its feasibility as a biomarker for liver fibrosis. MATERIALS AND METHODS: Twenty patients who underwent 4DCT and ultrasound-based transient elastography (UTE) were enrolled. All patients had chronic liver disease or cirrhosis. Liver elasticity measurements of the UTE were performed on the right lobe of the patient's liver in 20 patients. The serum biomarkers of the aspartate aminotransferase (AST)-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) were available in 18 of the 20 total patients, which were measured within 1 week after undergoing 4DCT. The displacement between the 4DCT images obtained at the endpoints of exhalation and inspiration was determined using the actual (via deformable image registration) and simulated (via FEM) respiration-induced displacement. The elasticity of each element of the liver model was optimized by minimizing the error between the actual and simulated respiration-induced displacement. Then, each patient's estimated liver elasticity was defined as the mean Young's modulus of the liver's right lobe and that of the whole liver using the estimated elasticity map. The estimated liver elasticity was evaluated for correlations with the elasticity obtained via UTE and with two serum biomarkers (APRI and FIB-4). RESULTS: The mean ± standard deviation (SD) of the errors between the actual and simulated respiration-induced displacement in the liver model was 0.54 ± 0.33 mm. The estimated liver's right lobe elasticity was statistically significantly correlated with the UTE (r = 0.87, P < 0.001). Furthermore, the estimated whole liver elasticity was statistically significantly correlated with the UTE (r = 0.84, P < 0.001), APRI score (r = 0.62, P = 0.005), and FIB-4 score (r = 0.54, P = 0.021). CONCLUSION: In this study, liver elasticity was estimated through FEM-based simulation and actual respiratory-induced liver displacement obtained from 4DCT images. Furthermore, we assessed that the estimated elasticity of the liver's right lobe was strongly correlated with the UTE. Therefore, the estimated elasticity has the potential to be a feasible imaging biomarker for assessing liver fibrosis using only 4DCT images without additional inspection or equipment costs. Because our results were derived from a limited sample of 20 patients, it is necessary to evaluate the accuracy of elasticity estimation for each liver segment on larger groups of biopsied patients to utilize liver elasticity information for radiotherapy planning.

Analysis of dosimetric impact of intrafraction translation and rotation during respiratory-gated stereotactic body radiotherapy with real-time tumor monitoring of the lung using a novel six degrees-of-freedom robotic moving phantom.

PURPOSE: This study aimed to develop a six degrees-of-freedom (6DoF) robotic moving phantom for evaluating the dosimetric impact of intrafraction rotation during respiratory-gated radiotherapy with real-time tumor monitoring in the lung. MATERIALS AND METHODS: Fifteen patients who had undergone respiratory-gated stereotactic body radiotherapy (SBRT) with the SyncTraX system for lung tumors were enrolled in this study. A water-equivalent phantom (WEP) was set at the tip of the robotic arm. A log file that recorded the three-dimensional positions of three fiducial markers implanted near the lung tumor was used as the input to the 6DoF robotic moving phantom. Respiratory-gated radiotherapy was performed for the WEP, which was driven using translational and rotational motions of the lung tumor. The accuracy of the 6DoF robotic moving phantom was calculated as the difference between the actual and the measured positions. To evaluate the dosimetric impact of intrafraction rotation, the absolute dose distributions under conditions involving gating and movement were compared with those under static conditions. RESULTS: For the sinusoidal patterns, the mean ± standard deviation (SD) of the root mean square errors (RMSEs) of the translation and rotation positional errors was <0.40 mm and 0.30°, respectively, for all directions. For the respiratory motion patterns of 15 patients, the mean ± SD of the RMSEs of the translation and rotation positional errors was <0.55 mm and 0.85°, respectively, for all directions. The γ3%/2mm values under translation with/without gating were 97.6 ± 2.2%/80.9 ± 18.1% and 96.8 ± 2.3%/80.0 ± 17.0% in the coronal and sagittal planes, respectively. Further, the γ3%/2mm values under rotation with/without gating were 91.5 ± 6.5%/72.8 ± 18.6% and 90.3 ± 6.1%/72.9 ± 15.7% in the coronal and sagittal planes, respectively. CONCLUSIONS: The developed 6DoF robotic phantom system could determine the translational and rotational motions of lung tumors with high accuracy. Further, respiratory-gating radiotherapy with real-time tumor monitoring using an internal surrogate marker was effective in compensating for the translational motion of lung tumors but not for correcting their rotational motion.