Plan complexity metrics for head and neck VMAT competition plans.

Previous plan competitions have largely focused on dose metric assessments. However, whether the submitted plans were realistic and reasonable from a quality assurance (QA) perspective remains unclear. This study aimed to investigate the relationship between aperture-based plan complexity metrics (PCM) in volumetric modulated arc therapy (VMAT) competition plans and clinical treatment plans verified through patient-specific QA (PSQA). In addition, the association of PCMs with plan quality was examined. A head and neck (HN) plan competition was held for Japanese institutions from June 2019 to July 2019, in which 210 competition plans were submitted. Dose distribution quality was quantified based on dose-volume histogram (DVH) metrics by calculating the dose distribution plan score (DDPS). Differences in PCMs between the two VMAT treatment plan groups (HN plan competitions held in Japan and clinically accepted HN VMAT plans through PSQA) were investigated. The mean (± standard deviation) DDPS for the 98 HN competition plans was 158.5 ± 20.6 (maximum DDPS: 200). DDPS showed a weak correlation with PCMs with a maximum r of 0.45 for monitor unit (MU); its correlation with some PCMs was "very weak." Significant differences were found in some PCMs between plans with the highest 20% DDPSs and the remaining plans. The clinical VMAT and competition plans revealed similar distributions for some PCMs. Deviations in PCMs for the two groups were comparable, indicating considerable variability among planners regarding planning skills. The plan complexity for HN VMAT competition plans increased for high-quality plans, as shown by the dose distribution. Direct comparison of PCMs between competition plans and clinically accepted plans showed that the submitted HN VMAT competition plans were realistic and reasonable from the QA perspective. This evaluation may provide a set of criteria for evaluating plan quality in plan competitions.

Radiological imaging protection: a study on imaging dose used while planning computed tomography for external radiotherapy in Japan.

Previous studies have primarily focused on quality of imaging in radiotherapy planning computed tomography (RTCT), with few investigations on imaging doses. To our knowledge, this is the first study aimed to investigate the imaging dose in RTCT to determine baseline data for establishing national diagnostic reference levels (DRLs) in Japanese institutions. A survey questionnaire was sent to domestic RT institutions between 10 October and 16 December 2021. The questionnaire items were volume computed tomography dose index (CTDIvol), dose-length product (DLP), and acquisition parameters, including use of auto exposure image control (AEC) or image-improving reconstruction option (IIRO) for brain stereotactic irradiation (brain STI), head and neck (HN) intensity-modulated radiotherapy (IMRT), lung stereotactic body radiotherapy (lung SBRT), breast-conserving radiotherapy (breast RT), and prostate IMRT protocols. Details on the use of motion-management techniques for lung SBRT were collected. Consequently, we collected 328 responses. The 75th percentiles of CTDIvol were 92, 33, 86, 23, and 32 mGy and those of DLP were 2805, 1301, 2416, 930, and 1158 mGy·cm for brain STI, HN IMRT, lung SBRT, breast RT, and prostate IMRT, respectively. CTDIvol and DLP values in institutions that used AEC or IIRO were lower than those without use for almost all sites. The 75th percentiles of DLP in each treatment technique for lung SBRT were 2541, 2034, 2336, and 2730 mGy·cm for free breathing, breath holding, gating technique, and real-time tumor tracking technique, respectively. Our data will help in establishing DRLs for RTCT protocols, thus reducing imaging doses in Japan.

Combination of Clinical Factors and Radiomics Can Predict Local Recurrence and Metastasis After Stereotactic Body Radiotherapy for Non-small Cell Lung Cancer.

BACKGROUND/AIM: Radiomics, which links radiological image features with patient prognoses, is expected to be applied for the prediction of the clinical outcomes of radiotherapy. We investigated the clinical and radiomic factors associated with recurrence patterns after stereotactic body radiotherapy (SBRT) for non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: We retrospectively analyzed 125 patients with histologically confirmed NSCLC who underwent SBRT between April 2003 and June 2017 at our institution. A radiomic score was calculated from five radiomics features (histogram and texture features) selected using the LASSO Cox regression model. These features were extracted from the gross tumor volume (GTV) in three-dimensional wavelet decomposition CT images. We used univariate and multivariate analyses to determine the associations between local control (LC) time and metastasis-free survival (MFS), clinical factors (age, sex, performance status, operability, smoking, histology, and tumor diameter), and the radiomic score. RESULTS: With a median follow-up of 37 months, the following 3-year rates were observed: overall survival, 80.9%; progression-free survival, 61.7%; LC, 75.1%, and MFS; 74.5%. In multivariate analysis, histology (squamous cell carcinoma vs. non-squamous cell carcinoma, p=0.0045), tumor diameter (>3 cm vs. ≤3 cm, p=0.039); and radiomic score (>0.043 vs. ≤0.043, p=0.042) were significantly associated with LC, and the radiomic score (>0.304 vs. ≤0.304, p<0.001) was significantly associated with MFS. CONCLUSION: Histology, tumor diameter, and radiomic score could be significant factors for predicting NSCLC recurrence patterns after SBRT.

Direct adhesion between Cu foil and polytetrafluoroethylene without increasing surface roughness for high-frequency printed wiring boards.

Polytetrafluoroethylene (PTFE) serves as a suitable dielectric substrate for high-frequency printed wiring boards (PWBs) owing to its excellent properties at high frequency. However, to the best of our knowledge, no study has investigated the strong adhesion between PTFE and Cu foil with low surface roughness. Therefore, in this study, pure-PTFE comprising a weak boundary layer (WBL) on the surface and glass-cloth-containing PTFE (GC-PTFE), which did not contain a WBL, were subjected to heat-assisted plasma (HAP) treatment. Thereafter, we investigated the surface chemical bonding state, surface morphology, and adhesion properties of the as-prepared PTFE toward Cu foil with low surface roughness. As observed, oxygen-containing functional groups were generated on the HAP-treated PTFE, and the WBL in the as-received pure-PTFE was eliminated via HAP treatment. Moreover, the surface roughness of the HAP-treated PTFE did not increase compared to that of as-received PTFE. After performing thermal compression under atmospheric conditions, the adhesion strength of both HAP-treated pure-PTFE and GC-PTFE was ∼0.9 N mm-1. In addition, the adhesion strength of Cu/pure-PTFE and Cu/GC-PTFE increased after thermal compression under a reduced pressure, and the adhesion strength of 1 N mm-1 was obtained. Although the Cu foil was not roughened, Cu/PTFE realized strong adhesive strength. The developed method is advantageous because maintaining a low interface roughness is crucial for applying PTFE to manufacture high-frequency PWBs.

Magnetic resonance-based imaging biopsy with signatures including topological Betti number features for prediction of primary brain metastatic sites.

This study incorporated topology Betti number (BN) features into the prediction of primary sites of brain metastases and the construction of magnetic resonance-based imaging biopsy (MRB) models. The significant features of the MRB model were selected from those obtained from gray-scale and three-dimensional wavelet-filtered images, BN and inverted BN (iBN) maps, and clinical variables (age and gender). The primary sites were predicted as either lung cancer or other cancers using MRB models, which were built using seven machine learning methods with significant features chosen by three feature selection methods followed by a combination strategy. Our study dealt with a dataset with relatively smaller brain metastases, which included effective diameters greater than 2 mm, with metastases ranging from 2 to 9 mm accounting for 17% of the dataset. The MRB models were trained by T1-weighted contrast-enhanced images of 494 metastases chosen from 247 patients and applied to 115 metastases from 62 test patients. The most feasible model attained an area under the receiver operating characteristic curve (AUC) of 0.763 for the test patients when using a signature including features of BN and iBN maps, gray-scale and wavelet-filtered images, and clinical variables. The AUCs of the model were 0.744 for non-small cell lung cancer and 0.861 for small cell lung cancer. The results suggest that the BN signature boosted the performance of MRB for the identification of primary sites of brain metastases including small tumors.

CT Image-Based Biopsy to Aid Prediction of HOPX Expression Status and Prognosis for Non-Small Cell Lung Cancer Patients.

This study aimed to elucidate a computed tomography (CT) image-based biopsy with a radiogenomic signature to predict homeodomain-only protein homeobox (HOPX) gene expression status and prognosis in patients with non-small cell lung cancer (NSCLC). Patients were labeled as HOPX-negative or positive based on HOPX expression and were separated into training (n = 92) and testing (n = 24) datasets. In correlation analysis between genes and image features extracted by Pyradiomics for 116 patients, eight significant features associated with HOPX expression were selected as radiogenomic signature candidates from the 1218 image features. The final signature was constructed from eight candidates using the least absolute shrinkage and selection operator. An imaging biopsy model with radiogenomic signature was built by a stacking ensemble learning model to predict HOPX expression status and prognosis. The model exhibited predictive power for HOPX expression with an area under the receiver operating characteristic curve of 0.873 and prognostic power in Kaplan-Meier curves (p = 0.0066) in the test dataset. This study's findings implied that the CT image-based biopsy with a radiogenomic signature could aid physicians in predicting HOPX expression status and prognosis in NSCLC.

Can Persistent Homology Features Capture More Intrinsic Information about Tumors from 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Images of Head and Neck Cancer Patients?

This study hypothesized that persistent homology (PH) features could capture more intrinsic information about the metabolism and morphology of tumors from 18F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) images of patients with head and neck (HN) cancer than other conventional features. PET/CT images and clinical variables of 207 patients were selected from the publicly available dataset of the Cancer Imaging Archive. PH images were generated from persistent diagrams obtained from PET/CT images. The PH features were derived from the PH PET/CT images. The signatures were constructed in a training cohort from features from CT, PET, PH-CT, and PH-PET images; clinical variables; and the combination of features and clinical variables. Signatures were evaluated using statistically significant differences (p-value, log-rank test) between survival curves for low- and high-risk groups and the C-index. In an independent test cohort, the signature consisting of PH-PET features and clinical variables exhibited the lowest log-rank p-value of 3.30 × 10-5 and C-index of 0.80, compared with log-rank p-values from 3.52 × 10-2 to 1.15 × 10-4 and C-indices from 0.34 to 0.79 for other signatures. This result suggests that PH features can capture the intrinsic information of tumors and predict prognosis in patients with HN cancer.

Relapse predictability of topological signature on pretreatment planning CT images of stage I non-small cell lung cancer patients before treatment with stereotactic ablative radiotherapy.

BACKGROUND: This study aimed to explore the predictability of topological signatures linked to the locoregional relapse (LRR) and distant metastasis (DM) on pretreatment planning computed tomography images of stage I non-small cell lung cancer (NSCLC) patients before treatment with stereotactic ablative radiotherapy (SABR). METHODS: We divided 125 primary stage I NSCLC patients (LRR: 34, DM: 22) into training (n = 60) and test datasets (n = 65), and the training dataset was augmented to 260 cases using a synthetic minority oversampling technique. The relapse predictabilities of the conventional wavelet-based features (WF), topology-based features [BF, Betti number (BN) map features; iBF, inverted BN map features], and their combined features (BWF, iBWF) were compared. The patients were stratified into high-risk and low-risk groups using the medians of the radiomics scores in the training dataset. RESULTS: For the LRR in the test, the iBF, iBWF, and WF showed statistically significant differences (p < 0.05), and the highest nLPC was obtained for the iBF. For the DM in the test, the iBWF showed a significant difference and the highest nLPC. CONCLUSION: The iBF indicated the potential of improving the LRR and DM prediction of stage I NSCLC patients prior to undergoing SABR.

Algorithm for an automatic treatment planning system using a single-arc VMAT for prostate cancer.

Optimization process in treatment planning for intensity-modulated radiation therapy varies with the treatment planner. Therefore, a large variation in the quality of dose distribution is usually observed. To reduce variation, an automatic optimizing toolkit was developed for the Monaco treatment planning system (Elekta AB, Stockholm, Sweden) for prostate cancer using volumetric-modulated arc therapy (VMAT). This toolkit was able to create plans automatically. However, most plans needed two arcs per treatment to ensure the dose coverage for targets. For prostate cancer, providing a plan with a single arc was advisable in clinical practice because intrafraction motion management must be considered to irradiate accurately. The purpose of this work was to develop an automatic treatment planning system with a single arc per treatment for prostate cancer using VMAT. We designed the new algorithm for the automatic treatment planning system to use one arc per treatment for prostate cancer in Monaco. We constructed the system in two main steps: (1) Determine suitable cost function parameters for each case before optimization, and (2) repeat the calculation and optimization until the conditions for dose indices are fulfilled. To evaluate clinical suitability, the plan quality between manual planning and the automatic planning system was compared. Our system created the plans automatically in all patients within a few iterations. Statistical differences between the plans were not observed for the target and organ at risk. It created the plans with no human input other than the initial template setting and system initiation. This system offers improved efficiency in running the treatment planning system and human resources while ensuring high-quality outputs.

Survey on utilization of flattening filter-free photon beams in Japan.

To understand the current state of flattening filter-free (FFF) beam implementation in C-arm linear accelerators (LINAC) in Japan, the quality assurance (QA)/quality control (QC) 2018-2019 Committee of the Japan Society of Medical Physics (JSMP) conducted a 37-question survey, designed to investigate facility information and specifications regarding FFF beam adoption and usage. The survey comprised six sections: facility information, devices, clinical usage, standard calibration protocols, modeling for treatment planning (TPS) systems and commissioning and QA/QC. A web-based questionnaire was developed. Responses were collected between 18 June and 18 September 2019. Of the 846 institutions implementing external radiotherapy, 323 replied. Of these institutions, 92 had adopted FFF beams and 66 had treated patients using them. FFF beams were used in stereotactic radiation therapy (SRT) for almost all disease sites, especially for the lungs using 6 MV and liver using 10 MV in 51 and 32 institutions, respectively. The number of institutions using FFF beams for treatment increased yearly, from eight before 2015 to 60 in 2018. Farmer-type ionization chambers were used as the standard calibration protocol in 66 (72%) institutions. In 73 (80%) institutions, the beam-quality conversion factor for FFF beams was calculated from TPR20,10, via the same protocol used for beams with flattening filter (WFF). Commissioning, periodic QA and patient-specific QA for FFF beams also followed the procedures used for WFF beams. FFF beams were primarily used in high-volume centers for SRT. In most institutions, measurement and QA was conducted via the procedures used for WFF beams.

Commissioning of the Mobius3D independent dose verification system for TomoTherapy.

In radiation therapy, a secondary independent dose verification is an important component of a quality control system. Mobius3D calculates three-dimensional (3D) patient dose using reference beam data and a collapsed cone convolution algorithm and analyzes dose-volume histogram automatically. There are currently no published data on commissioning and determining tolerance levels of Mobius3D for TomoTherapy. To verify the calculation accuracy and adjust the parameters of this system, we compared the measured dose using an ion chamber and film in a phantom with the dose calculated using Mobius3D for nine helical intensity-modulated radiation therapy plans, each with three nominal field widths. We also compared 126 treatment plans used in our institution to treat prostate, head-and-neck, and esophagus tumors based on dose calculations by treatment planning system for given dose indices and 3D gamma passing rates with those produced by Mobius3D. On the basis of these results, we showed that the action and tolerance levels at the average dose for the planning target volume (PTV) at each treatment site are at µ ± 2σ and µ ± 3σ, respectively. After adjusting parameters, the dose difference ratio on average was -0.2 ± 0.6% using ion chamber and gamma passing rate with the criteria of 3% and 3 mm on average was 98.8 ± 1.4% using film. We also established action and tolerance levels for the PTV at the prostate, head-and-neck, esophagus, and for the organ at risk at all treatment sites. Mobius3D calculations thus provide an accurate secondary dose verification system that can be commissioned easily and immediately after installation. Before clinical use, the Mobius3D system needs to be commissioned using the treatment plans for patients treated in each institution to determine the calculational accuracy and establish tolerances for each treatment site and dose index.

Chemical synthesis of 4-azido-ß-galactosamine derivatives for inhibitors of N-acetylgalactosamine 4-sulfate 6-O-sulfotransferase.

Chondroitin sulfate E (CS-E) plays a crucial role in diverse processes ranging from viral infection to neuroregeneration. Its regiospecific sulfation pattern, generated by N-acetylgalactosamine 4-sulfate 6-O-sulfotransferase (GalNAc4S-6ST), is the main structural determinant of its biological activity. Inhibitors of GalNAc4S-6ST can serve as powerful tools for understanding physiological functions of CS-E and its potential therapeutic leads for human diseases. A family of new 4-acylamino-ß-GalNAc derivatives and 4-azido-ß-GalNAc derivatives were synthesized for their potential application as inhibitors of GalNAc4S-6ST. The target compounds were evaluated for their inhibitory activities against GalNAc4S-6ST. The results revealed that 4-pivaloylamino- and 4-azido-ß-GalNAc derivatives displayed evident activities against GalNAc4S-6ST with IC50 value ranging from 0.800 to 0.828 mM. They showed higher activities than benzyl D-GalNAc4S that was used as control.

Density scaling of phantom materials for a 3D dose verification system.

In this study, the optimum density scaling factors of phantom materials for a commercially available three-dimensional (3D) dose verification system (Delta4) were investigated in order to improve the accuracy of the calculated dose distributions in the phantom materials. At field sizes of 10 × 10 and 5 × 5 cm2 with the same geometry, tissue-phantom ratios (TPRs) in water, polymethyl methacrylate (PMMA), and Plastic Water Diagnostic Therapy (PWDT) were measured, and TPRs in various density scaling factors of water were calculated by Monte Carlo simulation, Adaptive Convolve (AdC, Pinnacle3 ), Collapsed Cone Convolution (CCC, RayStation), and AcurosXB (AXB, Eclipse). Effective linear attenuation coefficients (µeff ) were obtained from the TPRs. The ratios of µeff in phantom and water ((µeff )pl,water ) were compared between the measurements and calculations. For each phantom material, the density scaling factor proposed in this study (DSF) was set to be the value providing a match between the calculated and measured (µeff )pl,water . The optimum density scaling factor was verified through the comparison of the dose distributions measured by Delta4 and calculated with three different density scaling factors: the nominal physical density (PD), nominal relative electron density (ED), and DSF. Three plans were used for the verifications: a static field of 10 × 10 cm2 and two intensity modulated radiation therapy (IMRT) treatment plans. DSF were determined to be 1.13 for PMMA and 0.98 for PWDT. DSF for PMMA showed good agreement for AdC and CCC with 6 MV x ray, and AdC for 10 MV x ray. DSF for PWDT showed good agreement regardless of the dose calculation algorithms and x-ray energy. DSF can be considered one of the references for the density scaling factor of Delta4 phantom materials and may help improve the accuracy of the IMRT dose verification using Delta4.

Convolutional neural network architecture and input volume matrix design for ERP classifications in a tactile P300-based Brain-Computer Interface.

In the presented study we conduct the off-line ERP classification using the convolutional neural network (CNN) classifier for somatosensory ERP intervals acquired in the full- body tactile P300-based Brain-Computer Interface paradigm (fbBCI). The main objective of the study is to enhance fbBCI stimulus pattern classification accuracies by applying the CNN classifier. A 60 × 60 squared input volume transformed by one-dimensional somatosensory ERP intervals in each electrode channel is input to the convolutional architecture for a filter training. The flattened activation maps are evaluated by a multilayer perceptron with one-hidden-layer in order to calculate classification accuracy results. The proposed method reveals that the CNN classifier model can achieve a non-personal- training ERP classification with the fbBCI paradigm, scoring 100 % classification accuracy results for all the participated ten users.

A Comparative Study of Reference Dosimetries in Japan and Canada.

In Japan and North America, different dosimetry protocols have been implemented to determine the absorbed dose to water: JSMP Standard Dosimetry 12 and AAPM TG-51 addendum. In this study, Japanese and Canadian reference dosimetries for high energy photon beams were compared theoretically, and then they were verified experimentally. We estimated the theoretical differences of the ion recombination correction factors, the leakage correction factors, the radial dose distribution correction factors, the calibration factors, the beam quality correction factors and the absorbed dose to water. When an influence of the radial dose distribution is negligible, the ratios of Canadian to Japanese absorbed dose in reference dosimetries ranged from 0.995 to 1.007 for all the reference-class-Farmer-type ionization chambers. This discrepancy was mainly caused by the wall correction factor included in the beam quality correction factor. Subsequently, to verify the theoretical approaches, we calibrated the same ionization chamber in 60Co gamma ray of Japanese primary and secondary standard dosimetry laboratories (PSDL and SSDL) and measured the absorbed dose of a clinical linear accelerator. It followed that the ratios of Canadian to Japanese absorbed dose in reference dosimetries increased up to 1.015 for PTW 30013 reference-class-Farmer-type ionization chamber. This increase was mainly caused by a discrepancy in the calibration factors (ND,w) observed between Japanese PSDL and SSDL. In conclusion, in order to improve the international consistency of the absorbed dose to water determined by JSMP Standard Dosimetry 12, we should reevaluate the accuracy of the wall correction factors and implement a periodic comparative test of the ND,w between Japanese PSDL and SSDL.

A Proposal for the Absorbed Dose to Water Dosimetry for Flattening Filter-free Beams.

Flattening filter-free (FFF) beams generated by linear accelerators have been widely adopted in many hospitals recently for radiation therapy. FFF technology can provide higher dose rates so that shortening of the treatment time and less intra-fraction motion error are expected.In Japan, the current way of determining absorbed dose to water for FFF beams is to follow the Standard Dosimetry 12 protocol which was developed for flattened beams. Since it has been reported that the flattened beams and FFF beams have different beam properties, it is necessary to evaluate the usefulness of Standard Dosimetry 12 protocol for FFF beam dosimetry.This report reviews physical and dosimetric properties of FFF beams especially in terms of the effect on absorbed dose to water dosimetry using an ionization chamber. From the review, it became evident that the absorbed dose to water is underestimated by volume averaging effect of the ionization chamber. On the other hand, the absorbed dose to water is overestimated by using the beam-quality specifier TPR20,10 to predict the restricted mass collision stopping power ratio for FFF beams. Therefore, an alternative method was proposed for absorbed dose to water dosimetry of FFF beams based on Standard Dosimetry 12.