Organ-contour-driven auto-matching algorithm in image-guided radiotherapy.

PURPOSE: This study aimed to demonstrate the potential clinical applicability of an organ-contour-driven auto-matching algorithm in image-guided radiotherapy. METHODS: This study included eleven consecutive patients with cervical cancer who underwent radiotherapy in 23 or 25 fractions. Daily and reference magnetic resonance images were converted into mesh models. A weight-based algorithm was implemented to optimize the distance between the mesh model vertices and surface of the reference model during the positioning process. Within the cost function, weight parameters were employed to prioritize specific organs for positioning. In this study, three scenarios with different weight parameters were prepared. The optimal translation and rotation values for the cervix and uterus were determined based on the calculated translations alone or in combination with rotations, with a rotation limit of ±3°. Subsequently, the coverage probabilities of the following two planning target volumes (PTV), an isotropic 5 mm and anisotropic margins derived from a previous study, were evaluated. RESULTS: The percentage of translations exceeding 10 mm varied from 9% to 18% depending on the scenario. For small PTV sizes, more than 80% of all fractions had a coverage of 80% or higher. In contrast, for large PTV sizes, more than 90% of all fractions had a coverage of 95% or higher. The difference between the median coverage with translational positioning alone and that with both translational and rotational positioning was 1% or less. CONCLUSION: This algorithm facilitates quantitative positioning by utilizing a cost function that prioritizes organs for positioning. Consequently, consistent displacement values were algorithmically generated. This study also revealed that the impact of rotational corrections, limited to ±3°, on PTV coverage was minimal.

Influence of dose calculation algorithms on the helical diode array using volumetric-modulated arc therapy for small targets.

BACKGROUND: For patient-specific quality assurance (PSQA) for small targets, the dose resolution can change depending on the characteristics of the dose calculation algorithms. PURPOSE: This study aimed to evaluate the influence of the dose calculation algorithms Acuros XB (AXB), anisotropic analytical algorithm (AAA), photon Monte Carlo (pMC), and collapsed cone (CC) on a helical diode array using volumetric-modulated arc therapy (VMAT) for small targets. MATERIALS AND METHODS: ArcCHECK detectors were inserted with a physical depth of 2.9 cm from the surface. To evaluate the influence of the dose calculation algorithms for small targets, rectangular fields of 2×100, 5×100, 10×100, 20×100, 50×100, and 100×100 mm2 were irradiated and measured using ArcCHECK with TrueBeam STx. A total of 20 VMAT plans for small targets, including the clinical sites of 19 brain metastases and one spine, were also evaluated. The gamma passing rates (GPRs) were evaluated for the rectangular fields and the 20 VMAT plans using AXB, AAA, pMC, and CC. RESULTS: For rectangular fields of 2×100 and 5×100 mm2, the GPR at 3%/2 mm of AXB was < 50% because AXB resulted in a coarser dose resolution with narrow beams. For field sizes > 10×100 mm2, the GPR at 3%/2 mm was > 88.1% and comparable for all dose calculation algorithms. For the 20 VMAT plans, the GPRs at 3%/2 mm were 79.1 ± 15.7%, 93.2 ± 5.8%, 94.9 ± 4.1%, and 94.5 ± 4.1% for AXB, AAA, pMC, and CC, respectively. CONCLUSION: The behavior of the dose distribution on the helical diode array differed depending on the dose calculation algorithm for small targets. Measurements using ArcCHECK for VMAT with small targets can have lower GPRs owing to the coarse dose resolution of AXB around the detector area.

Enzymatic sulfation of coelenterazine by human cytosolic aryl sulfotransferase SULT1A1: identification of coelenterazine C2-benzyl monosulfate by LC/ESI-TOF-MS.

Coelenterazine (CTZ) is known as a light-emitting source for the bioluminescence reaction in marine organisms. CTZ has two phenolic hydroxy groups at the C2-benzyl and C6-phenyl positions, and a keto-enol type hydroxy group at the C3-position in the core structure of imidazopyrazinone (= 3,7-dihydroimidazopyrazin-3-one). These hydroxy groups in CTZ could be sulfated by sulfotransferase(s), and the sulfates of Watasenia luciferin (CTZ disulfate at the C2- and C6-positions) and Renilla pre-luciferin (CTZ 3-enol sulfate) have been identified in marine organisms. To characterize the sulfation process of CTZ, human cytosolic aryl sulfotransferase SULT1A1 (SUTase) was used as a model enzyme. The sulfated products catalyzed by SUTase with 3'-phosphoadenosine 5'-phosphosulfate (PAPS) were analyzed by LC/ESI-TOF-MS. The product was the monosulfate of CTZ and identified as the C2-benzyl sulfate of CTZ (CTZ C2-benzyl monosulfate), but CTZ disulfate, CTZ 3-enol sulfate, and CTZ C6-phenyl monosulfate were not detected. The non-enzymatic oxidation products of dehydrocoelenterazine (dCTZ, dehydrogenated derivative of CTZ), coelenteramide (CTMD), and coelenteramine (CTM) from CTZ were also identified as their monosulfates.

Development of General-purpose Dielectric Constant Imaging Unit for SEM and Direct Observation of Samples in Aqueous Solution.

Electron microscopes can observe samples with a spatial resolution of 10 nm or higher; however, they cannot observe samples in solutions due to the vacuum conditions inside the sample chamber. Recently, we developed a scanning electron-assisted dielectric microscope (SE-ADM), based on scanning electron microscope, which enables the observation of various specimens in solution. Until now, the SE-ADM system used a custom-made SE-ADM stage with a built-in amplifier and could not be linked to the scanning electron microscopy (SEM) operation system. Therefore, it was necessary to manually acquire images from the SE-ADM system after setting the EB focus, astigmatism, and observation field-of-view from the SEM operating console. In this study, we developed a general-purpose dielectric constant imaging unit attached to commercially available SEMs. The new SE-ADM unit can be directly attached to the standard stage of an SEM, and the dielectric signal detected from this unit can be input to the external input terminal of the SEM, enabling simultaneous observation yielding SEM and SE-ADM images. Furthermore, 4.5 nm spatial resolution was achieved using a 10 nm thick silicon nitride film in the sample holder in the observation of aggregated PM2.5. We carried out the observation of cultured cells, PM2.5, and clay samples in solution.

Dosimetric impact of deformable image registration using radiophotoluminescent glass dosimeters with a physical geometric phantom.

PURPOSE: To study the dosimetry impact of deformable image registration (DIR) using radiophotoluminescent glass dosimeter (RPLD) and custom developed phantom with various inserts. METHODS: The phantom was developed to facilitate simultaneous evaluation of geometric and dosimetric accuracy of DIR. Four computed tomography (CT) images of the phantom were acquired with four different configurations. Four volumetric modulated arc therapy (VMAT) plans were computed for different phantom. Two different patterns were applied to combination of four phantom configurations. RPLD dose measurement was combined between corresponding two phantom configurations. DIR-based dose accumulation was calculated between corresponding two CT images with two commercial DIR software and various DIR parameter settings, and an open source software. Accumulated dose calculated using DIR was then compared with measured dose using RPLD. RESULTS: The mean ± standard deviation (SD) of dose difference was 2.71 ± 0.23% (range, 2.22%-3.01%) for tumor-proxy and 3.74 ± 0.79% (range, 1.56%-4.83%) for rectum-proxy. The mean ± SD of target registration error (TRE) was 1.66 ± 1.36 mm (range, 0.03-4.43 mm) for tumor-proxy and 6.87 ± 5.49 mm (range, 0.54-17.47 mm) for rectum-proxy. These results suggested that DIR accuracy had wide range among DIR parameter setting. CONCLUSIONS: The dose difference observed in our study was 3% for tumor-proxy and within 5% for rectum-proxy. The custom developed physical phantom with inserts showed potential for accurate evaluation of DIR-based dose accumulation. The prospect of simultaneous evaluation of geometric and dosimetric DIR accuracy in a single phantom may be useful for validation of DIR for clinical use.

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment. METHODS: Ten patients with lung cancer treated with marker-implanted RTTT were included. The prescription dose was 50 Gy in four fractions, using seven- to nine-port non-coplanar static beams. This corresponds to 14-18 X-ray tube angles for an orthogonal X-ray imaging system rotating with the gantry. All patients underwent 10 respiratory phases four-dimensional computed tomography. After a data augmentation approach, for each X-ray tube angle of a patient, 2250 digitally reconstructed radiograph (DRR) images with gross tumor volume (GTV) contour labeled were obtained. These images were adopted to train the patient and X-ray tube angle-specific GTV contour prediction model. During the testing, the model trained with DRR images predicted GTV contour on X-ray projection images acquired during treatment. The predicted three-dimensional (3D) positions of the GTV were calculated based on the centroids of the contours in the orthogonal images. The 3D positions of GTV determined by the marker-implanted RTTT during the treatment were considered as the ground truth. The 3D deviations between the prediction and the ground truth were calculated to evaluate the performance of the model. RESULTS: The median GTV volume and motion range were 7.42 (range, 1.18-25.74) cm3 and 22 (range, 11-28) mm, respectively. In total, 8993 3D position comparisons were included. The mean calculation time was 85 ms per image. The overall median value of the 3D deviation was 2.27 (interquartile range: 1.66-2.95) mm. The probability of the 3D deviation smaller than 5 mm was 93.6%. CONCLUSIONS: The evaluation results and calculation efficiency show the proposed deep learning-based markerless RTTT method may be feasible for patients with lung cancer.

Automatic measurement of beam-positioning accuracy at off-isocenter positions.

PURPOSE: This study performed an automatic measurement of the off-axis beam-positioning accuracy at a single isocenter via the TrueBeam Developer mode and evaluated the beam-positioning accuracy considering the effect of couch rotational errors. METHODS: TrueBeam STx and the Winston-Lutz test-dedicated phantom, with a 3 mm diameter steel ball, were used in this study. The phantom was placed on the treatment couch, and the Winston-Lutz test was performed at the isocenter for four gantry angles (0°, 90°, 180°, and 270°) using an electronic portal imaging device. The phantom offset positions were at distances of 0, 25, 50, 75, and 100 mm from the isocenter along the superior-inferior, anterior-posterior, and left-right directions. Seventeen patterns of multileaf collimator-shaped square fields of 10 × 10 mm2 were created at the isocenter and off-axis positions for each gantry angle. The beam-positioning accuracy was evaluated with couch rotation along the yaw-axis (0°, ± 0.5°, and ± 1.0°). RESULTS: The mean beam-positioning errors at the isocenter and off-isocenter distances (from the isocenter to ±100 mm) were 0.46-0.60, 0.44-0.91, and 0.42-1.11 mm for the couch angles of 0°, ±0.5°, and ±1°, respectively. The beam-positioning errors increased as the distance from the isocenter and couch rotation increased. CONCLUSION: These findings suggest that the beam-positioning accuracy at the isocenter and off-isocenter positions can be evaluated quickly and automatically using the TrueBeam Developer mode. The proposed procedure is expected to contribute to an efficient evaluation of the beam-positioning accuracy at off-isocenter positions.

Potential utility of cone-beam CT-guided adaptive radiotherapy under end-exhalation breath-hold conditions for pancreatic cancer.

PURPOSE: The purpose of this study was to demonstrate the potential utility of cone-beam computed tomography (CBCT)-guided online adaptive radiotherapy (ART) under end-exhalation breath-hold (EE-BH) conditions for pancreatic cancer (PC). METHODS: Eleven PC patients who underwent 15-fraction volumetric-modulated arc therapy under EE-BH conditions were included. Planning CT images and daily 165 CBCT images were imported into a dedicated treatment planning system. The prescription dose was set to 48 Gy in 15 fractions. The reference plan was automatically generated along with predefined clinical goals. After segmentation was completed on CBCT images, two different plans were generated: One was an adapted (ADP) plan in which re-optimization was performed on the anatomy of the day, and the other was a scheduled (SCH) plan, which was the same as the reference plan. The dose distributions calculated using the synthetic CT created from both planning CT and CBCT were compared between the two plans. Independent calculation-based quality assurance was also performed for the ADP plans, with a gamma passing rate of 3%/3 mm. RESULTS: All clinical goals were successfully achieved during the reference plan generation. Of the 165 sessions, gross tumor volume D98% and clinical target volume D98% were higher in 100 (60.1%) and 122 (74.0%) ADP fractions. In each fraction, the V3 Gy  < 1 cm3 of the stomach and duodenum was violated in 47 (28.5%) and 48 (29.1%), respectively, of the SCH fractions, whereas no violations were observed in the ADP fractions. There were statistically significant differences in the dose-volume indices between the SCH and ADP fractions (p < 0.05). The gamma passing rates were above 95% in all ADP fractions. CONCLUSIONS: The CBCT-guided online ART under EE-BH conditions successfully reduced the dose to the stomach and duodenum while maintaining target coverage.

Three-dimensional assessment of interfractional cervical and uterine motions using daily magnetic resonance images to determine margins and timing of replanning.

PURPOSE: This study was conducted to determine the margins and timing of replanning by assessing the daily interfractional cervical and uterine motions using magnetic resonance (MR) images. METHODS: Eleven patients with cervical cancer, who underwent intensity-modulated radiotherapy (IMRT) in 23-25 fractions, were considered in this study. The daily and reference MR images were converted into three-dimensional (3D) shape models. Patient-specific anisotropic margins were calculated from the proximal 95% of vertices located outside the surface of the reference model. Population-based margins were defined as the 90th percentile values of the patient-specific margins. The expanded volume of interest (expVOI) for the cervix and uterus was generated by expanding the reference model based on the population-based margin to calculate the coverage for daily deformable mesh models. For comparison, expVOIconv was generated using conventional margins: right (R), left (L), anterior (A), posterior (P), superior (S), and inferior (I) were (5, 5, 15, 15, 10, 10) and (10, 10, 20, 20, 15, 15) mm for the cervix and uterus, respectively. Subsequently, a replanning scenario was developed based on the cervical volume change. ExpVOIini and expVOIreplan were generated before and after replanning, respectively. RESULTS: Population-based margins were (R, L, A, P, S, I) of (7, 7, 11, 6, 11, 8) and (14, 13, 27, 19, 15, 21) mm for the cervix and uterus, respectively. The timing of replanning was found to be the 16th fraction, and the volume of expVOIreplan decreased by >30% compared to that of expVOIini . However, margins cannot be reduced to ensure equivalent coverage after replanning. CONCLUSION: We determined the margins and timing of replanning through detailed daily analysis. The margins of the cervix were smaller than conventional margins in some directions, while the margins of the uterus were larger in almost all directions. A margin equivalent to that at the initial planning was required for replanning.

Evaluation of generalization ability for deep learning-based auto-segmentation accuracy in limited field of view CBCT of male pelvic region.

PURPOSE: The aim of this study was to evaluate generalization ability of segmentation accuracy for limited FOV CBCT in the male pelvic region using a full-image CNN. Auto-segmentation accuracy was evaluated using various datasets with different intensity distributions and FOV sizes. METHODS: A total of 171 CBCT datasets from patients with prostate cancer were enrolled. There were 151, 10, and 10 CBCT datasets acquired from Vero4DRT, TrueBeam STx, and Clinac-iX, respectively. The FOV for Vero4DRT, TrueBeam STx, and Clinac-iX was 20, 26, and 25 cm, respectively. The ROIs, including the bladder, prostate, rectum, and seminal vesicles, were manually delineated. The U2 -Net CNN network architecture was used to train the segmentation model. A total of 131 limited FOV CBCT datasets from Vero4DRT were used for training (104 datasets) and validation (27 datasets); thereafter the rest were for testing. The training routine was set to save the best weight values when the DSC in the validation set was maximized. Segmentation accuracy was qualitatively and quantitatively evaluated between the ground truth and predicted ROIs in the different testing datasets. RESULTS: The mean scores ± standard deviation of visual evaluation for bladder, prostate, rectum, and seminal vesicle in all treatment machines were 1.0 ± 0.7, 1.5 ± 0.6, 1.4 ± 0.6, and 2.1 ± 0.8 points, respectively. The median DSC values for all imaging devices were ≥0.94 for the bladder, 0.84-0.87 for the prostate and rectum, and 0.48-0.69 for the seminal vesicles. Although the DSC values for the bladder and seminal vesicles were significantly different among the three imaging devices, the DSC value of the bladder changed by less than 1% point. The median MSD values for all imaging devices were ≤1.2 mm for the bladder and 1.4-2.2 mm for the prostate, rectum, and seminal vesicles. The MSD values for the seminal vesicles were significantly different between the three imaging devices. CONCLUSION: The proposed method is effective for testing datasets with different intensity distributions and FOV from training datasets.

Development of a prediction model for target positioning by using diaphragm waveforms extracted from CBCT projection images.

PURPOSE: To develop a prediction model (PM) for target positioning using diaphragm waveforms extracted from CBCT projection images. METHODS: Nineteen patients with lung cancer underwent orthogonal rotational kV x-ray imaging lasting 70 s. IR markers placed on their abdominal surfaces and an implanted gold marker located nearest to the tumor were considered as external surrogates and the target, respectively. Four different types of regression-based PM were trained using surrogate motions and target positions for the first 60 s, as follows: Scenario A: Based on the clinical scenario, 3D target positions extracted from projection images were used as they were (PMCL ). Scenario B: The short-arc 4D-CBCT waveform exhibiting eight target positions was obtained by averaging the target positions in Scenario A. The waveform was repeated for 60 s (W4D-CBCT ) by adapting to the respiratory phase of the external surrogate. W4D-CBCT was used as the target positions (PM4D-CBCT ). Scenario C: The Amsterdam Shroud (AS) signal, which depicted the diaphragm motion in the superior-inferior direction was extracted from the orthogonal projection images. The amplitude and phase of W4D-CBCT were corrected based on the AS signal. The AS-corrected W4D-CBCT was used as the target positions (PMAS-4D-CBCT ). Scenario D: The AS signal was extracted from single projection images. Other processes were the same as in Scenario C. The prediction errors were calculated for the remaining 10 s. RESULTS: The 3D prediction error within 3 mm was 77.3% for PM4D-CBCT , which was 12.8% lower than that for PMCL . Using the diaphragm waveforms, the percentage of errors within 3 mm improved by approximately 7% to 84.0%-85.3% for PMAS-4D-CBCT in Scenarios C and D, respectively. Statistically significant differences were observed between the prediction errors of PM4D-CBCT and PMAS-4D-CBCT . CONCLUSION: PMAS-4D-CBCT outperformed PM4D-CBCT , proving the efficacy of the AS signal-based correction. PMAS-4D-CBCT would make it possible to predict target positions from 4D-CBCT images without gold markers.

A virtual audit system for intensity-modulated radiation therapy credentialing in Japan Clinical Oncology Group clinical trials: A pilot study.

PURPOSE: The Medical Physics Working Group of the Radiation Therapy Study Group at the Japan Clinical Oncology Group is currently developing a virtual audit system for intensity-modulated radiation therapy dosimetry credentialing. The target dosimeters include films and array detectors, such as ArcCHECK (Sun Nuclear Corporation, Melbourne, Florida, USA) and Delta4 (ScandiDos, Uppsala, Sweden). This pilot study investigated the feasibility of our virtual audit system using previously acquired data. METHODS: We analyzed 46 films (32 and 14 in the axial and coronal planes, respectively) from 29 institutions. Global gamma analysis between measured and planned dose distributions used the following settings: 3%/3 mm criteria (the dose denominator was 2 Gy), 30% threshold dose, no scaling of the datasets, and 90% tolerance level. In addition, 21 datasets from nine institutions were obtained for array evaluation. Five institutions used ArcCHECK, while the others used Delta4. Global gamma analysis was performed with 3%/2 mm criteria (the dose denominator was the maximum calculated dose), 10% threshold dose, and 95% tolerance level. The film calibration and gamma analysis were conducted with in-house software developed using Python (version 3.9.2). RESULTS: The means ± standard deviations of the gamma passing rates were 99.4 ± 1.5% (range, 92.8%-100%) and 99.2 ± 1.0% (range, 97.0%-100%) in the film and array evaluations, respectively. CONCLUSION: This pilot study demonstrated the feasibility of virtual audits. The proposed virtual audit system will contribute to more efficient, cheaper, and more rapid trial credentialing than on-site and postal audits; however, the limitations should be considered when operating our virtual audit system.

FOXP4 inhibits squamous differentiation of atypical cells in cervical intraepithelial neoplasia via an ELF3-dependent pathway.

Although the human papillomavirus (HPV) vaccine is effective for preventing cervical cancers, this vaccine does not eliminate pre-existing infections, and alternative strategies have been warranted. Here, we report that FOXP4 is a new target molecule for differentiation therapy of cervical intraepithelial neoplasia (CIN). An immunohistochemical study showed that FOXP4 was expressed in columnar epithelial, reserve, and immature squamous cells, but not in mature squamous cells of the normal uterine cervix. In contrast with normal mature squamous cells, FOXP4 was expressed in atypical squamous cells in CIN and squamous cell carcinoma lesions. The FOXP4-positive areas significantly increased according to the CIN stages from CIN1 to CIN3. In monolayer cultures, downregulation of FOXP4 attenuated proliferation and induced squamous differentiation in CIN1-derived HPV 16-positive W12 cells via an ELF3-dependent pathway. In organotypic raft cultures, FOXP4-downregulated W12 cells showed mature squamous phenotypes of CIN lesions. In human keratinocyte-derived HaCaT cells, FOXP4 downregulation also induced squamous differentiation via an ELF3-dependent pathway. These findings suggest that downregulation of FOXP4 inhibits cell proliferation and promotes the differentiation of atypical cells in CIN lesions. Based on these results, we propose that FOXP4 is a novel target molecule for nonsurgical CIN treatment that inhibits CIN progression by inducing squamous differentiation.

Enzymatic conversion of dehydrocoelenterazine to coelenterazine using FMN-bound flavin reductase of NAD(P)H:FMN oxidoreductase.

Coelenterazine (CTZ) is known as luciferin (a substrate) for the luminescence reaction with luciferase (an enzyme) in marine organisms and is unstable in aqueous solutions. The dehydrogenated form of CTZ (dehydrocoelenterazine, dCTZ) is stable and thought to be a storage form of CTZ and a recycling intermediate from the condensation reaction of coelenteramine and 4-hydroxyphenylpyruvic acid to CTZ. In this study, the enzymatic conversion of dCTZ to CTZ was successfully achieved using NAD(P)H:FMN oxidoreductase from the bioluminescent bacterium Vibrio fischeri ATCC 7744 (FRase) in the presence of NADH (the FRase-NADH reaction). CTZ reduced from dCTZ in the FRase-NADH reaction was identified by HPLC and LC/ESI-TOF-MS analyses. Thus, dCTZ can be enzymatically converted to CTZ in vitro. Furthermore, the concentration of dCTZ could be determined by the luminescence activity using the CTZ-utilizing luciferases (Gaussia luciferase or Renilla luciferase) coupled with the FRase-NADH reaction.

Analysis of Prednisolone-Induced Osteoporosis Using the Japanese Adverse Drug Event Report Database.

PURPOSE: Osteoporosis is an adverse event of prednisolone. This study aimed to assess prednisolone-induced osteoporosis (PIO) profiles and patient backgrounds by analyzing data from the Japanese Adverse Drug Event Report (JADER) database. METHODS: The current study focused only on orally administered prednisolone. PIO was defined using preferred terms from the Medical Dictionary for Regulatory Activities. Reporting odds ratio (ROR) at 95% confidence interval (CI) and the time-to-onset profile of PIO were used to evaluate adverse events. RESULTS: The RORs (95% CI) of the female and male subgroups were 4.73 (4.17-5.38) and 2.49 (2.06-3.00), respectively. The analysis of time-to-onset profiles demonstrated that the median values (interquartile range: 25.0-75.0%) of PIO were 136 (74.0-294.0). The prednisolone treatment duration was significantly longer in the PIO patient group than in the non-PIO patient group. The findings suggest that patients with rheumatoid arthritis, systemic lupus erythematosus, and nephrotic syndrome receiving prednisolone have different age-related PIO profiles. CONCLUSIONS: Our results suggest that longer prednisolone treatment duration and larger cumulative dose might be risk factors of PIO. The potential risk for PIO should not be overlooked, and careful observation is recommended.

Vulnerabilities of radiomic features to respiratory motion on four-dimensional computed tomography-based average intensity projection images: A phantom study.

PURPOSE: To evaluate the influence of respiratory motion on the robustness of radiomic features on four-dimensional computed tomography (4DCT)-based average intensity projection (AIP) images by employing an anthropomorphic chest phantom. METHODS: Three spherical objects (φ30 mm), namely, acrylic (100 Hounsfield unit [HU], homogeneous), rubber (-140 HU, homogeneous), and cork (-630 HU, heterogeneous), were moved with motion amplitudes of 0, 1, 2.5, 4, 6, 8, and 10 mm in the phantom, and 4DCT scans were repeated at four different locations. Thereafter, the AIP images were generated considering the average of the 10 respiratory phases of the 4DCT images. Further, the targets were manually delineated on the AIP images in the lung window setting. A total of 851 radiomic features, including 107 unfiltered features and 744 wavelet filter-based features, were extracted from the region of interest for each material. The feature robustness among the different target motion amplitude (ε) was evaluated by normalizing the feature variability of the target motion relative to the variability of data from 573 patients with early-stage non-small cell lung cancer. The features with absolute ε values ≤0.5 were considered highly robust to target motions. RESULTS: The percentage of robust unfiltered and wavelet filter-based features with a motion amplitude of 1 mm was greater than 83.2% and 93.4%, respectively; however, the percentage decreased by more than 24.3% and 17.6%, respectively, for motion amplitudes greater than 2.5 mm. The movement of cork had a small effect on the feature robustness compared to that of acrylic and rubber, regardless of the target motion amplitudes. CONCLUSIONS: Our phantom study demonstrated that target motion amplitudes ≤1 mm led to the robustness of radiomic features on the 4DCT-based AIP images of thoracic regions. The frequency components and directions of the wavelet filters may be essential factors in 4DCT-based radiomic analysis.

Deep learning-based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients.

PURPOSE: Adaptive radiotherapy requires auto-segmentation in patients with head and neck (HN) cancer. In the current study, we propose an auto-segmentation model using a generative adversarial network (GAN) on magnetic resonance (MR) images of HN cancer for MR-guided radiotherapy (MRgRT). MATERIAL AND METHODS: In the current study, we used a dataset from the American Association of Physicists in Medicine MRI Auto-Contouring (RT-MAC) Grand Challenge 2019. Specifically, eight structures in the MR images of HN region, namely submandibular glands, lymph node level II and level III, and parotid glands, were segmented with the deep learning models using a GAN and a fully convolutional network with a U-net. These images were compared with the clinically used atlas-based segmentation. RESULTS: The mean Dice similarity coefficient (DSC) of the U-net and GAN models was significantly higher than that of the atlas-based method for all the structures (p < 0.05). Specifically, the maximum Hausdorff distance (HD) was significantly lower than that in the atlas method (p < 0.05). Comparing the 2.5D and 3D U-nets, the 3D U-net was superior in segmenting the organs at risk (OAR) for HN patients. The DSC was highest for 0.75-0.85, and the HD was lowest within 5.4 mm of the 2.5D GAN model in all the OARs. CONCLUSIONS: In the current study, we investigated the auto-segmentation of the OAR for HN patients using U-net and GAN models on MR images. Our proposed model is potentially valuable for improving the efficiency of HN RT treatment planning.

Assessment of using a gamma index analysis for patient-specific quality assurance in Japan.

PURPOSE: The Task Group 218 (TG-218) report was published by the American Association of Physicists in Medicine in 2018, recommending the appropriate use of gamma index analysis for patient-specific quality assurance (PSQA). The paper demonstrates that PSQA for radiotherapy in Japan appropriately applies the gamma index analysis considering TG-218. MATERIALS/METHODS: This survey estimated the acceptance state of radiotherapeutic institutes or facilities in Japan for the guideline using a web-based questionnaire. To investigate an appropriate PSQA of the facility-specific conditions, we researched an optimal tolerance or action level for various clinical situations, including different treatment machines, clinical policies, measurement devices, staff or their skills, and patient conditions. The responded data were analyzed using principal component analysis (PCA) and multidimensional scaling (MDS). The PCA focused on factor loading values of the first contribution over 0.5, whereas the MDS focused on mapped distances among data. RESULTS: Responses were obtained from 148 facilities that use intensity-modulated radiation therapy (IMRT), which accounted for 42.8% of the probable IMRT use in Japan. This survey revealed the appropriate application of the following universal criteria for gamma index analysis from the guideline recommendation despite the facility-specific variations (treatment machines/the number of IMRT cases/facility attributes/responded [representative] expertise or staff): (a) 95% pass rate, (b) 3% dose difference and 2-mm distance-to-agreement, and (c) 10% threshold dose. Conditions (a)-(c) were the principal components of the data by the PCA method and were mapped in a similar distance range, which was easily clustered from other gamma index analytic factors by the MDS method. Conditions (a)-(c) were the universally essential factors for the PSQA in Japan. CONCLUSION: We found that the majority of facilities using IMRT in each region of Japan complied with the guideline and conducted PSQA with deliberation under the individual facility-specific conditions.

Uterine Deletion of Bmal1 Impairs Placental Vascularization and Induces Intrauterine Fetal Death in Mice.

Recently, it was demonstrated that the expression of BMAL1 was decreased in the endometrium of women suffering from recurrent spontaneous abortion. To investigate the pathological roles of uterine clock genes during pregnancy, we produced conditional deletion of uterine Bmal1 (cKO) mice and found that cKO mice could receive embryo implantation but not sustain pregnancy. Gene ontology analysis of microarray suggested that uterine NK (uNK) cell function was suppressed in cKO mice. Histological examination revealed the poor formation of maternal vascular spaces in the placenta. In contrast to WT mice, uNK cells in the spongiotrophoblast layer, where maternal uNK cells are directly in contact with fetal trophoblast, hardly expressed an immunosuppressive NK marker, CD161, in cKO mice. By progesterone supplementation, pregnancy could be sustained until the end of pregnancy in some cKO mice. Although this treatment did not improve the structural abnormalities of the placenta, it recruited CD161-positive NK cells into the spongiotrophoblast layer in cKO mice. These findings indicate that the uterine clock system may be critical for pregnancy maintenance after embryo implantation.

Mucinous, endometrioid, and serous ovarian cancers with peritoneal dissemination are potent candidates for P-cadherin targeted therapy: a retrospective cohort study.

BACKGROUND: Aberrant expression of P-cadherin has been reported in various cancers, and has been attracting attention as a target for cancer treatment. Ovarian cancer, the leading cause of death among gynecologic malignancies, is classified into four histological subtypes: serous, mucinous, endometrioid, and clear cell, and each has distinct biological behavior. Although a negative survival impact in serous ovarian cancer patients and some functional role in peritoneal dissemination have been reported, differences of P-cadherin expression in histological subtypes and the proportion and distribution of positive cells remain to be investigated. The aims of this study were to clarify the histological and distributional profiles of P-cadherin expression in ovarian cancer for development of target-therapy in near future. METHODS: A total of 162 primary, 60 metastatic, and 8 recurrent tumors (all cases from 162 ovarian cancer patients) were enrolled in the study. Immunohistochemistry was performed for P-cadherin expression. Associations with clinicopathological characteristics and survival were analyzed. RESULTS: P-cadherin expression showed a strong correlation with the FIGO stage, histological subtypes, positive peritoneal dissemination (P < 0.01), positive distant metastasis (P < 0.05), and trend toward negative overall survival probability (P = 0.050). P-cadherin was intensely and broadly expressed in mucinous, endometrioid, and serous subtypes (P < 0.01). Disseminated tumors demonstrated similar P-cadherin expression to primary tumors whereas metastatic lymph nodes demonstrated significantly decreased expression (P < 0.01). CONCLUSIONS: Mucinous, endometrioid, and serous ovarian cancer patients accompanied with peritoneal disseminations are the most potent candidates for P-cadherin targeted drug delivery strategies. P-cadherin-targeted therapy may benefit and improve survival of poor-prognosis populations.