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Purpose: The real-time tumor tracking radiotherapy (RTRT) system requires periodic quality assurance (QA) and quality control. The goal of this study is to propose QA procedures from the viewpoint of imaging devices in the RTRT system. Methods: Tracking by the RTRT system (equips two sets of colored image intensifiers (colored I.I.s) fluoroscopy units) for the moving gold-marker (diameter 2.0 mm) in a rotating phantom were performed under various X-ray conditions. To analyze the relationship between fluoroscopic image quality and precision of gold marker coordinate calculation, the standard deviation of the 3D coordinate (sigma 3D [mm]) of the gold marker, the mean of the pattern recognition score (PRS) and the standard deviation of the distance between rays (DBR) (sigma DBR [mm]) were evaluated. Results: When tracking with speed of 10-60 mm/s, sigma DBR increased, though the mean PRS did not change significantly (p>0.05). On the contrary, the mean PRS increased depending on the integral noise equivalent quanta (integral NEQ) that is an indicator of image quality calculated from the modulation transfer function (MTF) as an indicator of spatial resolution and the noise power spectrum (NPS) as an indicator of noise characteristic. Conclusion: The indicators of NEQ, MTF, and NPS were useful for managing the tracking accuracy of the RTRT system. We propose observing the change of these indicators as additional QA procedures for each imaging device from the commissioning baseline.

The purpose of this study was to illustrate the clinical and imaging properties of giant intraosseous cyst-like lesions (GICLs) of the metacarpal bones extending beyond the central diaphysis in rheumatoid arthritis (RA) patients on magnetic resonance (MR) images. A keyword search was conducted to extract GICLs of the metacarpal bones out of MR reports in RA patients. There were nine GICLs extending from the subchondral bone region beyond the central diaphysis of the metacarpal bones on MR images in eight subjects with RA (seven females, one male). The age range was from 60 to 87 years with a median age of 65.5 years. The average disease duration was 13.1 years. As for the disease activity, one was low, six were moderate and one was high. None of the nine lesions were visible on radiography. The Steinbrocker stage distribution was as follows: I (n = 3), II (n = 2), and III (n = 3). Intraosseous cyst-like lesion of the metacarpal bones on MR images is a relatively rare manifestation in patients with long-standing RA. Although the lesion seems to be derived from subcortical bone break, it is not necessarily erosive in nature.

In rheumatoid arthritis (RA), the radiographic progression of joint space narrowing (JSN) is evaluated using visual assessments. However, those methods are complicated and time-consuming. We developed an automatic system that can detect joint locations and compute the joint space difference index (JSDI), which was defined as the chronological change in JSN between two radiographs. The purpose of this study was to establish the validity of the software that automatically evaluates the temporal change of JSN. This study consisted of 39 patients with RA. All patients were treated with tocilizumab and underwent hand radiography (left and right hand separately) at 0, 6, and 12 months. The JSN was evaluated using mTSS (modified Total Sharp Score) by one musculoskeletal radiologist as well as our automatic system. Software measurement showed that JSDI between 0 and 12 months was significantly higher than that between 0 and 6 months (p < 0.01). While, there was no significant difference in mTSS between 0, 6, and 12 months. The group with higher disease activity at 0 months had significantly higher JSDI between 0 and 6 months than that with lower disease activity (p = 0.02). The automatic software can evaluate JSN progression of RA patients in the finger joint on X-ray. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10278-020-00390-6) contains supplementary material, which is available to authorized users.

This research aimed to study the application of deep learning to the diagnosis of rheumatoid arthritis (RA). Definite criteria or direct markers for diagnosing RA are lacking. Rheumatologists diagnose RA according to an integrated assessment based on scientific evidence and clinical experience. Our novel idea was to convert various clinical information from patients into simple two-dimensional images and then use them to fine-tune a convolutional neural network (CNN) to classify RA or nonRA. We semi-quantitatively converted each type of clinical information to four coloured square images and arranged them as one image for each patient. One rheumatologist modified each patient’s clinical information to increase learning data. In total, 1037 images (252 RA, 785 nonRA) were used to fine-tune a pretrained CNN with transfer learning. For clinical data (10 RA, 40 nonRA), which were independent of the learning data and were used as testing data, we compared the classification ability of the fine-tuned CNN with that of three expert rheumatologists. Our simple system could potentially support RA diagnosis and therefore might be useful for screening RA in both specialised hospitals and general clinics. This study paves the way to enabling deep learning in the diagnosis of RA.

In this paper, we compare two radiation effect models: the average surviving fraction (ASF) model and the integral biologically effective dose (IBED) model for deriving the optimal irradiation scheme and show the superiority of ASF. Minimizing the effect on an organ at risk (OAR) is important in radiotherapy. The biologically effective dose (BED) model is widely used to estimate the effect on the tumor or on the OAR, for a fixed value of dose. However, this is not always appropriate because the dose is not a single value but is distributed. The IBED and ASF models are proposed under the assumption that the irradiation is distributed. Although the IBED and ASF models are essentially equivalent for deriving the optimal irradiation scheme in the case of uniform distribution, they are not equivalent in the case of non-uniform distribution. We evaluate the differences between them for two types of cancers: high α/β ratio cancer (e.g. lung) and low α/β ratio cancer (e.g. prostate), and for various distributions i.e. various dose–volume histograms. When we adopt the IBED model, the optimal number of fractions for low α/β ratio cancers is reasonable, but for high α/β ratio cancers or for some DVHs it is extremely large. However, for the ASF model, the results keep within the range used in clinical practice for both low and high α/β ratio cancers and for most DVHs. These results indicate that the ASF model is more robust for constructing the optimal irradiation regimen than the IBED model.

We have developed a refined computer-based method to detect joint space narrowing (JSN) progression with the joint space narrowing progression index (JSNPI) by superimposing sequential hand radiographs. The purpose of this study is to assess the validity of a computer-based method using images obtained from multiple institutions in rheumatoid arthritis (RA) patients. Sequential hand radiographs of 42 patients (37 females and 5 males) with RA from two institutions were analyzed by a computer-based method and visual scoring systems as a standard of reference. The JSNPI above the smallest detectable difference (SDD) defined JSN progression on the joint level. The sensitivity and specificity of the computer-based method for JSN progression was calculated using the SDD and a receiver operating characteristic (ROC) curve. Out of 314 metacarpophalangeal joints, 34 joints progressed based on the SDD, while 11 joints widened. Twenty-one joints progressed in the computer-based method, 11 joints in the scoring systems, and 13 joints in both methods. Based on the SDD, we found lower sensitivity and higher specificity with 54.2 and 92.8%, respectively. At the most discriminant cutoff point according to the ROC curve, the sensitivity and specificity was 70.8 and 81.7%, respectively. The proposed computer-based method provides quantitative measurement of JSN progression using sequential hand radiographs and may be a useful tool in follow-up assessment of joint damage in RA patients.

The scintillator with optical fiber (SOF) dosimeter consists of a miniature scintillator mounted on the tip of an optical fiber. The scintillator of the current SOF dosimeter is a 1-mm diameter hemisphere. For a scintillation dosimeter coupled with an optical fiber, measurement accuracy is influenced by signals due to Cerenkov radiation in the optical fiber. We have implemented a spectral filtering technique for compensating for the Cerenkov radiation effect specifically for our plastic scintillator-based dosimeter, using a wavelength-separated counting method. A dichroic mirror was used for separating input light signals. Individual signal counting was performed for high- and low-wavelength light signals. To confirm the accuracy, measurements with various amounts of Cerenkov radiation were performed by changing the incident direction while keeping the Ir-192 source-to-dosimeter distance constant, resulting in a fluctuation of

The purpose of the study is to validate the semi-automated method using tomosynthesis images for the assessment of finger joint space narrowing (JSN) in patients with rheumatoid arthritis (RA), by using the semi-quantitative scoring method as the reference standard. Twenty patients (14 females and 6 males) with RA were included in this retrospective study. All patients underwent radiography and tomosynthesis of the bilateral hand and wrist. Two rheumatologists and a radiologist independently scored JSN with two modalities according to the Sharp/van der Heijde score. Two observers independently measured joint space width on tomosynthesis images using an in-house semi-automated method. More joints with JSN were revealed with tomosynthesis score (243 joints) and the semi-automated method (215 joints) than with radiography (120 joints), and the associations between tomosynthesis scores and radiography scores were demonstrated (P

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within +/- 2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction.

The visual assessment of joint space narrowing (JSN) on radiographs of rheumatoid arthritis (RA) patients such as the Genant-modified Sharp score (GSS) is widely accepted but limited by its subjectivity and insufficient sensitivity. We developed a software application which can assess JSN quantitatively using a temporal subtraction technique for radiographs, in which the chronological change in JSN between two radiographs was defined as the joint space difference index (JSDI). The aim of this study is to prove the superiority of the software in terms of detecting fine radiographic progression in finger JSN over human observers. A micrometer measurement apparatus that can adjust arbitrary joint space width (JSW) in a phantom joint was developed to define true JSW. We compared the smallest detectable changes in JSW between the JSDI and visual assessment using phantom images. In a clinical study, 222 finger joints without interval score change on GSS in 15 RA patients were examined. We compared the JSDI between joints with and without synovial vascularity (SV) on power Doppler ultrasonography during the follow-up period. True JSW difference was correlated with JSDI for JSW differences ranging from 0.10 to 1.00 mm at increments of 0.10 mm (R2 = 0.986 and P

Clock genes are expressed throughout the body, although how they oscillate in unrestrained animals is not known. Here, we show an in vivo imaging technique that enables long-term simultaneous imaging of multiple tissues. We use dual-focal 3D tracking and signal-intensity calibration to follow gene expression in a target area. We measure circadian rhythms of clock genes in the olfactory bulb, right and left ears and cortices, and the skin. In addition, the kinetic relationship between gene expression and physiological responses to experimental cues is monitored. Under stable conditions gene expression is in phase in all tissues. In response to a long-duration light pulse, the olfactory bulb shifts faster than other tissues. In Cry1−/− Cry2−/− arrhythmic mice circadian oscillation is absent in all tissues. Thus, our system successfully tracks circadian rhythms in clock genes in multiple tissues in unrestrained mice., The circadian rhythms of peripheral clocks are difficult to study. Here the authors demonstrate a technique to image clock gene expression simultaneously in various tissues of freely moving mice, and use it to show that a long duration light pulse resets the rhythms in the olfactory bulb faster than other tissues.

Purpose Hypofractionated irradiation is often used in precise radiotherapy instead of conventional multifractionated irradiation. We propose a novel mathematical method for selecting a hypofractionated or multifractionated irradiation regimen based on physical dose distribution adding to biologic consideration. Methods and Materials The linear–quadratic model was used for the radiation effects on tumor and normal tissues, especially organs at risk (OARs). On the basis of the assumption that the OAR receives a fraction of the dose intended for the tumor, the minimization problem for the damage effect on the OAR was treated under the constraint that the radiation effect on the tumor is fixed. Results For an N -time fractionated irradiation regimen, the constraint of tumor lethality was described by an N -dimensional hypersphere. The total dose of the fractionated irradiations was considered for minimizing the damage effect on the OAR under the hypersphere condition. It was found that the advantage of hypofractionated or multifractionated irradiation therapies depends on the magnitude of the ratio of α/β parameters for the OAR and tumor in the linear–quadratic model and the ratio of the dose for the OAR and tumor. Conclusions Our mathematical method shows that multifractionated irradiation with a constant dose is better if the ratio of α/β for the OAR and tumor is less than the ratio of the dose for the OAR and tumor, whereas hypofractionated irradiation is better otherwise.

The track structure of electrons generated in bio-tissues exposed to X-rays (or other radiation particles) is essential to cell damage. This paper reports on Monte Carlo track simulations of electrons to determine the degree of concentration of ionization and excitation events as the aggregation index (AI). AI is expected to correlate with the number of lesions in a cell nucleus, such as double-strand breaks (DSBs), which may lead to lethality of cells. The simulation results show that AI as a function of electron energy has a peak in low energy (sub-keV) regions and the induction of the lesions may be attributed to the ionization and excitation clusters generated in the tissues. The track pattern, associated with the primary track and secondary branch tracks, is also illustrated by counting the number of the branching points given by the ionization.

The purpose of this study was to evaluate a custom portal image — digitally reconstructed radiograph (DRR) registration software application. The software works by transforming the portal image into the coordinate space of the DRR image using three control points placed on each image by the user, and displaying the fused image. In order to test statistically that the software actually improves setup error estimation, an intra‐ and interobserver phantom study was performed. Portal images of anthropomorphic thoracic and pelvis phantoms with virtually placed irradiation fields at known setup errors were prepared. A group of five doctors was first asked to estimate the setup errors by examining the portal and DRR image side‐by‐side, not using the software. A second group of four technicians then estimated the same set of images using the registration software. These two groups of human subjects were then compared with an auto‐registration feature of the software, which is based on the mutual information between the portal and DRR images. For the thoracic case, the average distance between the actual setup error and the estimated error was 4.3±3.0 mm for doctors using the side‐by‐side method, 2.1±2.4 mm for technicians using the registration method, and 0.8±0.4 mm for the automatic algorithm. For the pelvis case, the average distance between the actual setup error and estimated error was 2.0±0.5 mm for the doctors using the side‐by‐side method, 2.5±0.4 mm for technicians using the registration method, and 2.0±1.0 mm for the automatic algorithm. The ability of humans to estimate offset values improved statistically using our software for the chest phantom that we tested. Setup error estimation was further improved using our automatic error estimation algorithm. Estimations were not statistically different for the pelvis case. Consistency improved using the software for both the chest and pelvis phantoms. We also tested the automatic algorithm with a database of over 5,000 clinical cases from our hospital. The algorithm performed well for head and breast but performed poorly for pelvis cases, probably due to lack of contrast in the megavoltage portal image. The software incorporates an original algorithm to fuse portal and DRR images, which we describe in detail. The offset optimization algorithm used in the automatic mode of operation is also unique, and may be useful if the contrast of the portal images can be improved. PACS numbers: 87.55.Qr, 87.57.nj

Objective: Power Doppler ultrasonography (PDUS) and MRI are independently useful to predict structural damage in patients with rheumatoid arthritis (RA). We hypothesize that there is a complementary relationship between these modalities. The aim of this study is, therefore, to investigate the usefulness of the predictive value of composite assessment of PDUS and contrast-enhanced MRI in radiographic outcomes in patients with RA. Methods: 20 patients (17 females and 3 males) with RA on disease-modifying antirheumatic drugs underwent PDUS and MRI of both hands at baseline. Radiography of the bilateral hands was performed at baseline and at 1 year, Articular synovitis on PDUS was evaluated according to quantitative measurement. Synovitis, bone marrow edema and bone erosion were scored according to the RA MRI scoring method. The changes of joint space narrowing and bone erosion on radiograph were assessed by the Sharp/van der Heijde method. We applied t-statistics to combine the assessment of quantitative PDUS with semiquantitative MRI. Results: Structural damage progression for radiography was not correlated with any evaluations for MRI, while it showed significant correlation with synovitis on PDUS (r(s) = 0.597, p = 0.005). The composite assessment of both modalities (synovitis for PDUS and bone marrow edema for MRI) was correlated with structural damage progression on radiograph (r(s) = 0.792, p < 0.0001). Conclusion: Composite assessment of PDUS and MRI may have a stronger predictive value in radiographic progression than PDUS or MRI alone in RA. Advances In knowledge: Composite assessment of PDUS and MRI may be an effective predictor of structural damage in RA.

This paper reports on Monte Carlo simulations of electrons in liquid water using a set of electron collision cross-sections constructed with data published recently. The track history of electrons having initial energy ranged from 1 keV to 10 keV is investigated looking at the ionization and excitation processes. The results show that the ratio of the ionization and excitation events per track history is unique independent of the initial electron energy above a couple of 100 eV and these inelastic processes occur with low energy electrons frequently below 100 eV. In particular, the excitation processes are dominated by the electrons below 50 eV. Flight distance distributions between the inelastic collisions are also discussed.

Production probabilities of ions and excited particle species along the proton beam track in liquid water are estimated around the Bragg peak region, taking into account charge-changing processes and energetic secondary electron (δ-ray) behavior. Ionization and excitation processes are divided into two categories in this study: primary processes associated with direct proton (or hydrogen) interaction and secondary processes arising from the electrons ejected by the primary process. We show that the number of events in the secondary processes producing ions and excited particles is larger than that of the primary processes around the Bragg peak while neutralized protons (i.e., hydrogen) with low energy have a large contribution to direct ionization. Effects of charge-changing processes on ionization and excitation are also discussed.

Objective: Measurement of visceral adipose tissue (VAT) needs to be accurate and sensitive to change for risk monitoring. The purpose of this study is to determine the CT slice location where VAT area can best reflect changes in VAT volume and body weight. Methods: 60 plain abdominal CT images from 30 males [mean age (range) 51 (41-68) years, mean body weight (range) 71.1 (101.9-50.9) kg] who underwent workplace screenings twice within a 1-year interval were evaluated. Automatically calculated and manually corrected areas of the VAT of various scan levels using "freeform curve" region of interest on CT were recorded and compared with body weight changes. Results: The strongest correlations of VAT area with VAT volume and body weight changes were shown in a slice 3 cm above the lower margin of L3 with r values of 0.853 and 0.902, respectively. Conclusion: VAT area measurement at a single level 3 cm above the lower margin of the L3 vertebra is feasible and can reflect changes in VAT volume and body weight. Advances in knowledge: As VAT area at a CT slice 3 cm above the lower margin of L3 can best reflect interval changes in VAT volume and body weight, VAT area measurement should be selected at this location.

Objective: To improve on the reproducibility and sensitivity of the assessment of patients with rheumatoid arthritis (RA), two semi-automated measurement methods of the area of enhancing pannus (AEP), based on thresholding (AEP_THRES) and pixel-by-pixel time-intensity curve analysis (AEP_TIC), were evaluated as an alternative for the gold-standard manual contouring method (AEP_MANUAL). Methods: 8 patients (7 females and 1 male) with RA of the wrist or finger joints participated in the study. A three-dimensional contrast-enhanced dynamic sequence was used at 3 T. After identifying the most relevant time-intensity curve (TIC) shape in terms of synovitis by comparing with the synovitis score using the RA-MRI scoring system, three different approaches for measuring the AEP were performed. Spearman's test of rank correlation was used to compare AEPs via two semi-automated methods (AEP_THRES and AEP_TIC) against manual segmentation (AEP_MANUAL) in the entire hand region as well as the wrist and the finger regions. Results: The TIC shape of "washout after fast initial enhancement" had excellent correlation with synovitis score (r = 0.809). The correlation coefficient between AEP_TIC and AEP_MANUAL was evaluated to be better than that of AEP_THRES and AEP_MANUAL in the wrist region (AEP_THRES: r = 0.716, AEP_TIC: r = 0.815), whereas these were of comparable accuracy for the entire hand and the finger regions. Conclusion: This study suggests that TIC analysis may be an alternative to manual contouring for pannus quantification and provides important clinical information of the extent of the disease in patients with RA. Advances in knowledge: TIC shape analysis can be applied for new quantitative assessment for RA synovitis in the wrist.