Prediction of patient-specific quality assurance for volumetric modulated arc therapy using radiomics-based machine learning with dose distribution.

PURPOSE: We sought to develop machine learning models to predict the results of patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), which were represented by several dose-evaluation metrics-including the gamma passing rates (GPRs)-and criteria based on the radiomic features of 3D dose distribution in a phantom. METHODS: A total of 4,250 radiomic features of 3D dose distribution in a cylindrical dummy phantom for 140 arcs from 106 clinical VMAT plans were extracted. We obtained the following dose-evaluation metrics: GPRs with global and local normalization, the dose difference (DD) in 1% and 2% passing rates (DD1% and DD2%) for 10% and 50% dose threshold, and the distance-to-agreement in 1-mm and 2-mm passing rates (DTA1 mm and DTA2 mm) for 0.5%/mm and 1.0%.mm dose gradient threshold determined by measurement using a diode array in patient-specific QA. The machine learning regression models for predicting the values of the dose-evaluation metrics using the radiomic features were developed based on the elastic net (EN) and extra trees (ET) models. The feature selection and tuning of hyperparameters were performed with nested cross-validation in which four-fold cross-validation is used within the inner loop, and the performance of each model was evaluated in terms of the root mean square error (RMSE), the mean absolute error (MAE), and Spearman's rank correlation coefficient. RESULTS: The RMSE and MAE for the developed machine learning models ranged from <1% to nearly <10% depending on the dose-evaluation metric, the criteria, and dose and dose gradient thresholds used for both machine learning models. It was advantageous to focus on high dose region for predicating global GPR, DDs, and DTAs. For certain metrics and criteria, it was possible to create models applicable for patients' heterogeneity by training only with dose distributions in phantom. CONCLUSIONS: The developed machine learning models showed high performance for predicting dose-evaluation metrics especially for high dose region depending on the metric and criteria. Our results demonstrate that the radiomic features of dose distribution can be considered good indicators of the plan complexity and useful in predicting measured dose evaluation metrics.

Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect and classify errors of multi-leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor (TF) and the dosimetric leaf gap (DLG). METHODS: A total of 33 clinical VMAT plans for prostate and head-and-neck cancer were used, assuming a cylindrical and homogeneous phantom, and error plans were created by altering the original value of the TF and the DLG by ± 10, 20, and 30% in the treatment planning system (TPS). The Gaussian filters of σ = 0.5 $\sigma = 0.5$ and 1.0 were applied to the planar dose maps of the error-free plan to mimic the measurement dose map, and thus dose difference maps between the error-free and error plans were obtained. We evaluated 3 deep learning-based models, created to perform the following detections/classifications: (1) error-free versus TF error, (2) error-free versus DLG error, and (3) TF versus DLG error. Models to classify the sign of the errors were also created and evaluated. A gamma analysis was performed for comparison. RESULTS: The detection and classification of TF and DLG error were feasible for σ = 0.5 $\sigma = 0.5$ ; however, a considerable reduction of accuracy was observed for σ = 1.0 $\sigma = 1.0$ depending on the magnitude of error and treatment site. The sign of errors was detectable by the specifically trained models for σ = 0.5 $\sigma = 0.5$ and 1.0. The gamma analysis could not detect errors. CONCLUSIONS: We demonstrated that the deep learning-based models could feasibly detect and classify TF and DLG errors in VMAT dose distributions, depending on the magnitude of the error, treatment site, and the degree of mimicked measurement doses.

Exogenous expression of both matrix protein and glycoprotein facilitates infectious viral particle production of Borna disease virus 1.

Borna disease virus 1 (BoDV-1) is a non-segmented, negative-strand RNA virus that is characterized by persistent infection in the nucleus and low production of progeny virions. This feature impedes not only the harvesting of infectious viral particles from infected cells but also the rescue of high titres of recombinant BoDV-1 (rBoDV-1) by reverse genetics. Here, we demonstrate that exogenous expression of both matrix protein (M) and glycoprotein (G), which are constituents of the viral lipid envelope, significantly facilitates the formation of infectious particles and propagation of BoDV-1 without affecting its viral RNA synthesis. Furthermore, simultaneous transfection of M and G expression plasmids with N, P and L helper plasmids by reverse genetics drastically enhances the rescue efficiency of rBoDV-1. On the other hand, we also show that overexpression of M induces obvious cytotoxicity similar to that of other Mononegaviruses. Together with our recent report showing that excess expression of G induces aberrant accumulation of immature G, a potential stimulator of the host innate immune response, it is conceivable that BoDV-1 may suppress excess expression of M and G to reduce the cytopathic effect, thereby leading to maintenance of persistent infection. Our results contribute not only to the establishment of an efficient method to recover high-titre BoDV-1 but also to understanding the unique mechanism of persistent BoDV-1 infection.

Optimal Expression of the Envelope Glycoprotein of Orthobornaviruses Determines the Production of Mature Virus Particles.

An RNA virus-based episomal vector (REVec) whose backbone is Borna disease virus 1 (BoDV-1) can provide long-term gene expression in transduced cells. To improve the transduction efficiency of REVec, we evaluated the role of the viral envelope glycoprotein (G) of the genus Orthobornavirus, including that of BoDV-1, in the production of infectious particles. By using G-pseudotype assay in which the lack of G in G-deficient REVec (ΔG-REVec) was compensated for expression of G, we found that excess expression of BoDV-1-G does not affect particle production itself but results in uncleaved and aberrant mature G expression in the cells, leading to the production of REVec particles with low transduction titers. We revealed that the expression of uncleaved G in the cells inhibits the incorporation of mature G and vgRNA into the particles. This feature of G was conserved among mammalian and avian orthobornaviruses; however, the cleavage efficacy of canary bornavirus 1 (CnBV-1)-G was exceptionally not impaired by its excess expression, which led to the production of the pseudotype ΔG-REVec with the highest titer. Chimeric G proteins between CnBV-1 and -2 revealed that the signal peptide of CnBV-1-G was responsible for the cleavage efficacy through the interaction with intracellular furin. We showed that CnBV-1 G leads to the development of pseudotyped REVec with high transduction efficiency and a high-titer recombinant REVec. Our study demonstrated that the restricted expression of orthobornavirus G contributes to the regulation of infectious particle production, the mechanism of which can improve the transduction efficiency of REVec.IMPORTANCE Most viruses causing persistent infection produce few infectious particles from the infected cells. Borna disease virus 1, a member of the genus Orthobornavirus, is an RNA virus that persistently infects the nucleus and has been applied to vectors for long-term gene expression. In this study, we showed that, common among orthobornaviruses, excessive G expression does not affect particle production itself but reduces the production of infectious particles with mature G and genomic RNA. This result suggested that limited G expression contributes to suppressing abnormal viral particle production. On the other hand, we found that canary bornavirus 1 has an exceptional G maturation mechanism and produces a high-titer virus. Our study will contribute to not only understanding the mechanism of infectious particle production but also improving the vector system of orthobornaviruses.

Stability of Borna disease virus-based episomal vector under physical and chemical stimulation.

Borna disease virus (BoDV), a nonsegmented, negative-sense RNA virus, establishes persistent infection and replicates in the cell nucleus. Since BoDV genomic RNA exists as episomal RNA, the host genome is not invaded by BoDV infection. These unique features make BoDV a promising gene delivery system as an RNA virus-based episomal vector (REVec). Previously, the stable expression of genes of interest in vitro and in vivo using a REVec was reported. For the clinical application of a REVec, the fundamental properties under various physical and chemical conditions must be determined to develop purification processes, supply chains, and biosafety management. This study investigated the effects of the following conditions on the inducibility of transmission-defective ΔG-REVec: freeze-thaw cycles, dehydration, UV, temperature, pH, and reagents for virucides and laboratory experiments. Although the titer of ΔG-REVec was not influenced by the freeze-thaw process or 5 minute incubation at ≤50°C, ΔG-REVec was significantly inactivated by incubation at ≥70°C for 5 minutes. The induction titer of ΔG-REVec was decreased by long-term incubation, dehydration, and UV irradiation in a temperature- and time-dependent manner. ΔG-REVec was sensitive to lower pH and inactivated by chemical reagents under general conditions. These results provide important knowledge for developing the clinical use of REVec and biosafety management.

ADAR2 Is Involved in Self and Nonself Recognition of Borna Disease Virus Genomic RNA in the Nucleus.

Cells sense pathogen-derived double-stranded RNA (dsRNA) as nonself. To avoid autoimmune activation by self dsRNA, cells utilize A-to-I editing by adenosine deaminase acting on RNA 1 (ADAR1) to disrupt dsRNA structures. Considering that viruses have evolved to exploit host machinery, A-to-I editing could benefit innate immune evasion by viruses. Borna disease virus (BoDV), a nuclear-replicating RNA virus, may require escape from nonself RNA-sensing and immune responses to establish persistent infection in the nucleus; however, the strategy by which BoDV evades nonself recognition is unclear. Here, we evaluated the involvement of ADARs in BoDV infection. The infection efficiency of BoDV was markedly decreased in both ADAR1 and ADAR2 knockdown cells at the early phase of infection. Microarray analysis using ADAR2 knockdown cells revealed that ADAR2 reduces immune responses even in the absence of infection. Knockdown of ADAR2 but not ADAR1 significantly reduced the spread and titer of BoDV in infected cells. Furthermore, ADAR2 knockout decreased the infection efficiency of BoDV, and overexpression of ADAR2 rescued the reduced infectivity in ADAR2 knockdown cells. However, the growth of influenza A virus, which causes acute infection in the nucleus, was not affected by ADAR2 knockdown. Moreover, ADAR2 bound to BoDV genomic RNA and induced A-to-G mutations in the genomes of persistently infected cells. We finally demonstrated that BoDV produced in ADAR2 knockdown cells induces stronger innate immune responses than those produced in wild-type cells. Taken together, our results suggest that BoDV utilizes ADAR2 to edit its genome to appear as "self" RNA in order to maintain persistent infection in the nucleus.IMPORTANCE Cells use the editing activity of adenosine deaminase acting on RNA proteins (ADARs) to prevent autoimmune responses induced by self dsRNA, but viruses can exploit this process to their advantage. Borna disease virus (BoDV), a nuclear-replicating RNA virus, must escape nonself RNA sensing by the host to establish persistent infection in the nucleus. We evaluated whether BoDV utilizes ADARs to prevent innate immune induction. ADAR2 plays a key role throughout the BoDV life cycle. ADAR2 knockdown reduced A-to-I editing of BoDV genomic RNA, leading to the induction of a strong innate immune response. These data suggest that BoDV exploits ADAR2 to edit nonself genomic RNA to appear as self RNA for innate immune evasion and establishment of persistent infection.

Radiobiological evaluation considering setup error on single-isocenter irradiation in stereotactic radiosurgery.

PURPOSE: We calculated the dosimetric indices and estimated the tumor control probability (TCP) considering six degree-of-freedom (6DoF) patient setup errors in stereotactic radiosurgery (SRS) using a single-isocenter technique. METHODS: We used simulated spherical gross tumor volumes (GTVs) with diameters of 1.0 cm (GTV 1), 2.0 cm (GTV 2), and 3.0 cm (GTV 3), and the distance (d) between the target center and isocenter was set to 0, 5, and 10 cm. We created the dose distribution by convolving the blur component to uniform dose distribution. The prescription dose was 20 Gy and the dose distribution was adjusted so that D95 (%) of each GTV was covered by 100% of the prescribed dose. The GTV was simultaneously rotated within 0°-1.0° (δR) around the x-, y-, and z-axes and then translated within 0-1.0 mm (δT) in the x-, y-, and z-axis directions. D95, conformity index (CI), and conformation number (CN) were evaluated by varying the distance from the isocenter. The TCP was estimated by translating the calculated dose distribution into a biological response. In addition, we derived the x-y-z coordinates with the smallest TCP reduction rate that minimize the sum of squares of the residuals as the optimal isocenter coordinates using the relationship between 6DoF setup error, distance from isocenter, and GTV size. RESULTS: D95, CI, and CN were decreased with increasing isocenter distance, decreasing GTV size, and increasing setup error. TCP of GTVs without 6DoF setup error was estimated to be 77.0%. TCP were 25.8% (GTV 1), 35.0% (GTV 2), and 53.0% (GTV 3) with (d, δT, δR) = (10 cm, 1.0 mm, 1.0°). The TCP was 52.3% (GTV 1), 54.9% (GTV 2), and 66.1% (GTV 3) with (d, δT, δR) = (10 cm, 1.0 mm, 1.0°) at the optimal isocenter position. CONCLUSION: The TCP in SRS for multiple brain metastases with a single-isocenter technique may decrease with increasing isocenter distance and decreasing GTV size when the 6DoF setup errors are exceeded (1.0 mm, 1.0°). Additionally, it might be possible to better maintain TCP for GTVs with 6DoF setup errors by using the optimal isocenter position.

Radiobiological effects of the interruption time with Monte Carlo Simulation on multiple fields in photon beams.

PURPOSE: The interruption time is the irradiation interruption that occurs at sites and operations such as the gantry, collimator, couch rotation, and patient setup within the field in radiotherapy. However, the radiobiological effect of prolonging the treatment time by the interruption time for tumor cells is little evaluated. We investigated the effect of the interruption time on the radiobiological effectiveness with photon beams based on a modified microdosimetric kinetic (mMK) model. METHODS: The dose-mean lineal energy yD (keV/µm) of 6-MV photon beams was calculated by the particle and heavy ion transport system (PHITS). We set the absorbed dose to 2 or 8 Gy, and the interruption time (τ) was set to 1, 3, 5, 10, 30, and 60 min. The biological parameters such as α0, ß0, and DNA repair constant rate (a + c) values were acquired from a human non-small-cell lung cancer cell line (NCI-H460) for the mMK model. We used two-field and four-field irradiation with a constant dose rate (3 Gy/min); the photon beams were paused for interruption time τ. We calculated the relative biological effectiveness (RBE) to evaluate the interruption time's effect compared with no interrupted as a reference. RESULTS: The yD of 6-MV photon beams was 2.32 (keV/µm), and there was little effect by changing the water depth (standard deviation was 0.01). The RBE with four-field irradiation for 8 Gy was decreased to 0.997, 0.975, 0.900, and 0.836 τ = 1, 10, 30, 60 min, respectively. In addition, the RBE was affected by the repair constant rate (a + c) value, the greater the decrease in RBE with the longer the interruption time when the (a + c) value was large. CONCLUSION: The ~10-min interruption of 6-MV photon beams did not significantly impact the radiobiological effectiveness, since the RBE decrease was <3%. Nevertheless, the RBE's effect on tumor cells was decreased about 30% by increasing the 60 min interruption time at 8 Gy with four-field irradiation. It is thus necessary to make the interruption time as short as possible.

Human Metapneumovirus M2-2 Protein Acts as a Negative Regulator of Alpha Interferon Production by Plasmacytoid Dendritic Cells.

Human metapneumovirus (HMPV) has the ability to inhibit Toll-like receptor 7 (TLR7)- and TLR9-dependent alpha interferon (IFN-α) production by plasmacytoid dendritic cells (pDCs). However, the inhibition mechanism remains largely unknown. To identify viral proteins responsible for this inhibition, we performed a screening of HMPV open reading frames (ORFs) for the ability to block TLR7/9-dependent signaling reconstituted in HEK293T cells by transfection with myeloid differentiation factor 88 (MyD88), tumor necrosis factor receptor-associated factor 6 (TRAF6), IKKα, and IFN regulatory factor 7 (IRF7). This screening demonstrated that the M2-2 protein was the most potent inhibitor of TLR7/9-dependent IFN-α induction. A recombinant HMPV in which the M2-2 ORF was silenced indeed induced greater IFN-α production by human pDCs than wild-type HMPV did. Immunoprecipitation experiments showed direct physical association of the M2-2 protein with the inhibitory domain (ID) of IRF7. As a natural consequence of this, transfection of IRF7 lacking the ID, a constitutively active mutant, resulted in activation of the IFN-α promoter even in the presence of M2-2. Bioluminescence resonance energy transfer assays and split Renilla luciferase complementation assays revealed that M2-2 inhibited MyD88/TRAF6/IKKα-induced homodimerization of IRF7. In contrast, expression of the M2-2 protein did not result in inhibition of IPS-1-induced homodimerization and resultant activation of IRF7. This indicates that inhibition of MyD88/TRAF6/IKKα-induced IRF7 homodimerization does not result from a steric effect of M2-2 binding. Instead, it was found that M2-2 inhibited MyD88/TRAF6/IKKα-induced phosphorylation of IRF7 on Ser477. These results suggest that M2-2 blocks TLR7/9-dependent IFN-α induction by preventing IRF7 homodimerization, possibly through its effects on the phosphorylation status of IRF7.IMPORTANCE The family Paramyxoviridae is divided into two subfamilies, the Paramyxovirinae and the Pneumovirinae Members of the subfamily Paramyxovirinae have the ability to inhibit TLR7/9-dependent IFN-α production, and the underlying inhibition mechanism has been intensively studied. In contrast, little is known about how members of the subfamily Pneumovirinae regulate IFN-α production by pDCs. We identified the M2-2 protein of HMPV, a member of the subfamily Pneumovirinae, as a negative regulator of IFN-α production by pDCs and uncovered the underlying mechanism. This study explains in part why the M2-2 knockout recombinant HMPV is attenuated and further suggests that M2-2 is a potential target for HMPV therapy.

Degradation of amyloid ß peptide by neprilysin expressed from Borna disease virus vector.

Accumulation of amyloid ß (Aß40 and Aß42) in the brain is a characteristic of Alzheimer's disease (AD). Because neprilysin (NEP) is a major Aß-degrading enzyme, NEP delivery in the brain is a promising gene therapy for AD. Borna disease virus (BoDV) vector enables long-term transduction of foreign genes in the central nerve system. Here, we evaluated the proteolytic ability of NEP transduced by the BoDV vector and found that the amounts of Aß40 and Aß42 significantly decreased, which suggests that NEP expressed from the BoDV vector is functional to degrade Aß.

Dual function of the nuclear export signal of the Borna disease virus nucleoprotein in nuclear export activity and binding to viral phosphoprotein.

BACKGROUND: Borna disease virus (BoDV), which has a negative-sense, single-stranded RNA genome, causes persistent infection in the cell nucleus. The nuclear export signal (NES) of the viral nucleoprotein (N) consisting of leucine at positions 128 and 131 and isoleucine at positions 133 and 136 overlaps with one of two predicted binding sites for the viral phosphoprotein (P). A previous study demonstrated that higher expression of BoDV-P inhibits nuclear export of N; however, the function of N NES in the interaction with P remains unclear. We examined the subcellular localization, viral polymerase activity, and P-binding ability of BoDV-N NES mutants. We also characterized a recombinant BoDV (rBoDV) harboring an NES mutation of N. RESULTS: BoDV-N with four alanine-substitutions in the leucine and isoleucine residues of the NES impaired its cytoplasmic localization and abolished polymerase activity and P-binding ability. Although an alanine-substitution at position 131 markedly enhanced viral polymerase activity as determined by a minigenome assay, rBoDV harboring this mutation showed expression of viral RNAs and proteins relative to that of wild-type rBoDV. CONCLUSIONS: Our results demonstrate that BoDV-N NES has a dual function in BoDV replication, i.e., nuclear export of N and an interaction with P, affecting viral polymerase activity in the nucleus.

Genome-scale CRISPR-Cas9 screen identifies host factors as potential therapeutic targets for SARS-CoV-2 infection.

Although many host factors important for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported, the mechanisms by which the virus interacts with host cells remain elusive. Here, we identified tripartite motif containing (TRIM) 28, TRIM33, euchromatic histone lysine methyltransferase (EHMT) 1, and EHMT2 as proviral factors involved in SARS-CoV-2 infection by CRISPR-Cas9 screening. Our result suggested that TRIM28 may play a role in viral particle formation and that TRIM33, EHMT1, and EHMT2 may be involved in viral transcription and replication. UNC0642, a compound that specifically inhibits the methyltransferase activity of EHMT1/2, strikingly suppressed SARS-CoV-2 growth in cultured cells and reduced disease severity in a hamster infection model. This study suggests that EHMT1/2 may be a therapeutic target for SARS-CoV-2 infection.

The Relationship between the Contouring Time of the Metal Artifacts Area and Metal Artifacts in Head and Neck Radiotherapy.

(1) Background: The impacts of metal artifacts (MAs) on the contouring workload for head and neck radiotherapy have not yet been clarified. Therefore, this study evaluated the relationship between the contouring time of the MAs area and MAs on head and neck radiotherapy treatment planning. (2) Methods: We used treatment planning computed tomography (CT) images for head and neck radiotherapy. MAs were classified into three severities by the percentage of CT images containing MAs: mild (<25%), moderate (25−75%), and severe (>75%). We randomly selected nine patients to evaluate the relationship between MAs and the contouring time of the MAs area. (3) Results: The contouring time of MAs showed moderate positive correlations with the MAs volume and the number of CT images containing MAs. Interobserver reliability of the extracted MAs volume and contouring time were excellent and poor, respectively. (4) Conclusions: Our study suggests that the contouring time of MAs areas is related to individual commitment rather than clinical experience. Therefore, the development of software combining metal artifact reduction methods with automatic contouring methods is necessary to reducing interobserver variability and contouring workload.

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.

Efficacy of oligodendrocyte precursor cells as delivery vehicles for single-chain variable fragment to misfolded SOD1 in ALS rat model.

Superoxide dismutase1 (SOD 1) mutation is a leading cause of familial amyotrophic lateral sclerosis (ALS). Growing evidence suggests that antibody therapy against misfolded SOD1 protein can be therapeutic. However, the therapeutic effects are limited, partly because of the delivery system. Therefore, we investigated the efficacy of oligodendrocyte precursor cells (OPCs) as a drug delivery vehicle of single-chain variable fragments (scFv). Using a Borna disease virus vector that is pharmacologically removable and episomally replicable in the recipient cells, we successfully transformed wild-type OPCs to secrete scFv of a novel monoclonal antibody (D3-1), specific for misfolded SOD1. Single intrathecal injection of OPCs scFvD3-1, but not OPCs alone, significantly delayed disease onset and prolonged the lifespan of ALS rat models expressing SOD1 H46R . The effect of OPC scFvD3-1 surpassed that of a 1 month intrathecal infusion of full-length D3-1 antibody alone. scFv-secreting OPCs suppressed neuronal loss and gliosis, reduced levels of misfolded SOD1 in the spinal cord, and suppressed the transcription of inflammatory genes, including Olr1, an oxidized low-density lipoprotein receptor 1. The use of OPCs as a delivery vehicle for therapeutic antibodies is a new option for ALS in which misfolded protein and oligodendrocyte dysfunction are implicated in the pathogenesis.

The impact of target positioning error and tumor size on radiobiological parameters in robotic stereotactic radiosurgery for metastatic brain tumors.

This study aimed to evaluate the effect of target positioning error (TPE) on radiobiological parameters, such as tumor control probability (TCP) and normal tissue complication probability (NTCP), in stereotactic radiosurgery (SRS) for metastatic brain tumors of different sizes using CyberKnife. The reference SRS plans were created using the circular cone of the CyberKnife for each spherical gross tumor volume (GTV) with diameters (φ) of 5, 7.5, 10, 15, and 20 mm, contoured on computed tomography images of the head phantom. Subsequently, plans involving TPE were created by shifting the beam center by 0.1-2.0 mm in three dimensions relative to the reference plans using the same beam arrangements. Conformity index (CI), generalized equivalent uniform dose (gEUD)-based TCP, and NTCP of estimated brain necrosis were evaluated for each plan. When the gEUD parameter "a" was set to - 10, the CI and TCP for the reference plan at the φ5-mm GTV were 0.90 and 80.8%, respectively. The corresponding values for plans involving TPE of 0.5-mm, 1.0-mm, and 2.0-mm were 0.62 and 77.4%, 0.40 and 62.9%, and 0.12 and 7.2%, respectively. In contrast, the NTCP for all GTVs were the same. The TCP for the plans involving a TPE of 2-mm was 7.2% and 68.8% at the φ5-mm and φ20-mm GTV, respectively. The TPEs corresponding to a TCP reduction rate of 3% at the φ5-mm and φ20-mm GTV were 0.41 and 0.99 mm, respectively. TPE had a significant effect on TCP in SRS for metastatic brain tumors using CyberKnife, particularly for small GTVs.

Extraction of water-soluble polysaccharides from kidney beans and examination of their protein dispersion and stabilization properties under acidic conditions.

The extraction conditions of kidney bean water-soluble polysaccharides (SKPSs) from kidney bean fibers were examined. The factors such as temperature, pH, and time were combined to derive the conditions for obtaining high yields of high molecular mass polysaccharides. The optimal extraction temperature, time, and pH were 120 °C, 30 min, and 9, respectively. Under these conditions, the yield of SKPS (SKPS9) obtained was as high as 26.4%. The weight average molecular mass of SKPS9 measured using size exclusion chromatography equipped with a multi-angle laser light scattering detector was 2,530 kg/mole. The main constituent sugars of SKPS9 were arabinose (67.2%) and galacturonic acid (15.6%). SKPS9 carbohydrate molecules observed using a scanning probe microscope showed the mixed structures of a multi-branched structure, whose sugar chains extended outward from the center to the periphery of the molecule, and a little-branched straight chain structure. SKPS9 had protein dispersing and stabilizing properties under acidic conditions. In the acidified milk system containing 3% non-fat milk solids, 0.4% SKPS9 was able to maintain a mono-modal distribution of fine protein particles in pH level ranging from 3.8 to 4.4. This work suggests the potential for the creation of a value added ingredient from kidney bean.

Calculated relative biological effectiveness (RBE) for initial DNA double-strand breaks (DSB) from flattening filter and flattening filter-free 6 MV X-ray fields.

OBJECTIVES: We evaluated the radiobiological effectiveness based on the yields of DNA double-strand breaks (DSBs) of field induction with flattening filter (FF) and FF-free (FFF) photon beams. METHODS: We used the particle and heavy ion transport system (PHITS) and a water equivalent phantom (30 × 30 × 30 cm3) to calculate the physical qualities of the dose-mean lineal energy (yD) with 6 MV FF and FFF. The relative biological effectiveness based on the yields of DNA-DSBs (RBEDSB) was calculated for standard radiation such as 220 kVp X-rays by using the estimating yields of SSBs and DSBs. The measurement points used to calculate the in-field yD and RBEDSB were located at a depth of 3, 5, and 10 cm in the water equivalent phantom on the central axis. Measurement points at 6, 8, and 10 cm in the lateral direction of each of the three depths from the central axis were set to calculate the out-of-field yD and RBEDSB. RESULTS: The RBEDSB of FFF in-field was 1.7% higher than FF at each measurement depth. The RBEDSB of FFF out-of-field was 1.9 to 6.4% higher than FF at each depth measurement point. As the distance to out-of-field increased, the RBEDSB of FFF rose higher than those of FF. FFF has a larger RBEDSB than FF based on the yields of DNA-DSBs as the distance to out-of-field increased. CONCLUSIONS: The out-of-field radiobiological effect of FFF could thus be greater than that of FF since the spreading of the radiation dose out-of-field with FFF could be a concern compared to the FF. ADVANCES IN KNOWLEDGE: The RBEDSB of FFF of out-of-field might be larger than FF.

Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling errors with the use of radiomic features of fluence maps measured in patient-specific quality assurance (QA) for intensity-modulated radiation therapy (IMRT) with an electric portal imaging device (EPID). METHODS: Fluence maps measured with EPID for 38 beams from 19 clinical IMRT plans were assessed. Plans with various degrees of error in MLC modeling parameters [i.e., MLC transmission factor (TF) and dosimetric leaf gap (DLG)] and plans with an MLC positional error for comparison were created. For a total of 152 error plans for each type of error, we calculated fluence difference maps for each beam by subtracting the calculated maps from the measured maps. A total of 837 radiomic features were extracted from each fluence difference map, and we determined the number of features used for the training dataset in the machine learning models by using random forest regression. Machine learning models using the five typical algorithms [decision tree, k-nearest neighbor (kNN), support vector machine (SVM), logistic regression, and random forest] for binary classification between the error-free plan and the plan with the corresponding error for each type of error were developed. We used part of the total dataset to perform fourfold cross-validation to tune the models, and we used the remaining test dataset to evaluate the performance of the developed models. A gamma analysis was also performed between the measured and calculated fluence maps with the criteria of 3%/2 and 2%/2 mm for all of the types of error. RESULTS: The radiomic features and its optimal number were similar for the models for the TF and the DLG error detection, which was different from the MLC positional error. The highest sensitivity was obtained as 0.913 for the TF error with SVM and logistic regression, 0.978 for the DLG error with kNN and SVM, and 1.000 for the MLC positional error with kNN, SVM, and random forest. The highest specificity was obtained as 1.000 for the TF error with a decision tree, SVM, and logistic regression, 1.000 for the DLG error with a decision tree, logistic regression, and random forest, and 0.909 for the MLC positional error with a decision tree and logistic regression. The gamma analysis showed the poorest performance in which sensitivities were 0.737 for the TF error and the DLG error and 0.882 for the MLC positional error for 3%/2 mm. The addition of another type of error to fluence maps significantly reduced the sensitivity for the TF and the DLG error, whereas no effect was observed for the MLC positional error detection. CONCLUSIONS: Compared to the conventional gamma analysis, the radiomics-based machine learning models showed higher sensitivity and specificity in detecting a single type of the MLC modeling error and the MLC positional error. Although the developed models need further improvement for detecting multiple types of error, radiomics-based IMRT QA was shown to be a promising approach for detecting the MLC modeling error.

Maximum distance in single-isocenter technique of stereotactic radiosurgery with rotational error using margin-based analysis.

Through geometrical simulation, we evaluated the effect of rotational error in patient setup on geometrical coverage and calculated the maximum distance between the isocenter and target, where the clinical PTV margin secures geometrical coverage with a single-isocenter technique. We used simulated spherical GTVs with diameters of 1.0 (GTV 1), 1.5 (GTV 2), 2.0 (GTV 3), and 3.0 cm (GTV 4). The location of the target center was set such that the distance between the target and isocenter ranged from 0 to 15 cm. We created geometrical coverage vectors so that each target was entirely covered by 100% of the prescribed dose. The vectors of the target positions were simultaneously rotated within a range of 0°-2.0° around the x-, y-, and z-axes. For each rotational error, the reduction in geometrical coverage of the targets was calculated and compared with that obtained for a rotational error of 0°. The tolerance value of the geometrical coverage reduction was defined as 5% of the GTV. The maximum distance that satisfied the 5% tolerance value for different values of rotational error at a clinical PTV margin of 0.1 cm was calculated. When the rotational errors were 0.5° for a 0.1 cm PTV margin, the maximum distances were as follows: GTV 1: 7.6 cm; GTV 2: 10.9 cm; GTV 3: 14.3 cm; and GTV 4: 21.4 cm. It might be advisable to exclude targets that are > 7.6 cm away from the isocenter with a single-isocenter technique to satisfy the tolerance value for all GTVs.