Artificial Intelligence Quantification of Enhanced Synovium Throughout the Entire Hand in Rheumatoid Arthritis on Dynamic Contrast-Enhanced MRI.

BACKGROUND: Challenges persist in achieving automatic and efficient inflammation quantification using dynamic contrast-enhanced (DCE) MRI in rheumatoid arthritis (RA) patients. PURPOSE: To investigate an automatic artificial intelligence (AI) approach and an optimized dynamic MRI protocol for quantifying disease activity in RA in whole hands while excluding arterial pixels. STUDY TYPE: Retrospective. SUBJECTS: Twelve RA patients underwent DCE-MRI with 27 phases for creating the AI model and tested on images with a variable number of phases from 35 RA patients. FIELD STRENGTH/SEQUENCE: 3.0 T/DCE T1-weighted gradient echo sequence (mDixon, water image). ASSESSMENT: The model was trained with various DCE-MRI time-intensity number of phases. Evaluations were conducted for similarity between AI segmentation and manual outlining in 51 ROIs with synovitis. The relationship between synovial volume via AI segmentation with rheumatoid arthritis magnetic resonance imaging scoring (RAMRIS) across whole hands was then evaluated. The reference standard was determined by an experienced musculoskeletal radiologist. STATISTICAL TEST: Area under the curve (AUC) of receiver operating characteristic (ROC), Dice and Spearman's rank correlation coefficients, and interclass correlation coefficient (ICC). A P-value <0.05 was considered statistically significant. RESULTS: A minimum of 15 phases (acquisition time at least 2.5 minutes) was found to be necessary. AUC ranged from 0.941 ± 0.009 to 0.965 ± 0.009. The Dice score was 0.557-0.615. Spearman's correlation coefficients between the AI model and ground truth were 0.884-0.927 and 0.736-0.831, for joint ROIs and whole hands, respectively. The Spearman's correlation coefficient for the additional test set between the model trained with 15 phases and RAMRIS was 0.768. CONCLUSION: The AI-based classification model effectively identified synovitis pixels while excluding arteries. The optimal performance was achieved with at least 15 phases, providing a quantitative assessment of inflammatory activity in RA while minimizing acquisition time. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

A new predictive parameter for dose-volume metrics in intensity-modulated radiation therapy planning for prostate cancer: Initial phantom study.

BACKGROUND: Organ-at-risk (OAR) sparing is often assessed using an overlap volume-based parameter, defined as the ratio of the volume of OAR that overlaps the planning target volume (PTV) to the whole OAR volume. However, this conventional overlap-based predictive parameter (COPP) does not consider the volume relationship between the PTV and OAR. PURPOSE: We propose a new overlap-based predictive parameter that consider the PTV volume. The effectiveness of proposed overlap-based predictive parameter (POPP) is evaluated compared with COPP. METHODS: We defined as POPP = (overlap volume between OAR and PTV/OAR volume) × (PTV volume/OAR volume). We generated intensity modulated radiation therapy (IMRT) based on step and shoot technique, and volumetric modulated arc therapy (VMAT) plans with the Auto-Planning module of Pinnacle3 treatment planning system (v14.0, Philips Medical Systems, Fitchburg, WI) using the American Association of Physicists in Medicine Task Group (TG119) prostate phantom. The relationship between the position and size of the prostate phantom was systematically modified to simulate various geometric arrangements. The correlation between overlap-based predictive parameters (COPP and POPP) and dose-volume metrics (mean dose, V70Gy, V60Gy, and V37.5 Gy for rectum and bladder) was investigated using linear regression analysis. RESULTS: Our results indicated POPP was better than COPP in predicting intermediate-dose metrics. The bladder results showed a trend similar to that of the rectum. The correlation coefficient of POPP was significantly greater than that of COPP in < 62 Gy (82% of the prescribed dose) region for IMRT and in < 55 Gy (73% of the prescribed dose) region for VMAT regarding the rectum (p < 0.05). CONCLUSIONS: POPP is superior to COPP for creating predictive models at an intermediate-dose level. Because rectal bleeding and bladder toxicity can be associated with intermediate-doses as well as high-doses, it is important to predict dose-volume metrics for various dose levels. POPP is a useful parameter for predicting dose-volume metrics and assisting the generation of treatment plans.

Subtle Radiographic Progression at Six Months Can Be Detected Using Automated Quantitative Software in Rheumatoid Arthritis While Receiving Tocilizumab.

OBJECTIVES: We investigated whether our in-house software equipped with partial image phase-only correlation (PIPOC) can detect subtle radiographic joint space narrowing (JSN) progression at six months and predict JSN progression in rheumatoid arthritis (RA) patients receiving Tocilizumab. METHODS: The study included 39 RA patients who were treated with Tocilizumab. Radiological progression of the metacarpophalangeal and the proximal interphalangeal joints was evaluated according to the Genant-modified Sharp score (GSS) at 0, 6, and 12 months. Automatic measurements were performed with the software. We validated the software in terms of accuracy in detecting the JSN progression. RESULTS: The success rate of the software for joint space width (JSW) measurement was 96.8% (449/464). The 0-12-month JSW change by the software was significantly greater in joints with the 0-6-month PIPOC (+) group than the 0-6-month PIPOC (-) group (p < 0.001). The 0-12-month JSW change by the software was 0-12-month GSS (+) than with 0-12-month GSS (-) (p = 0.02). Here, "(+)" indicates the JSN progression during the follow-up period. Meanwhile, "(-)" indicates no JSN progression during the follow-up period. Linear regression tests showed significant correlations between the 0-6-month and the 0-12-month PIPOC in the left 2nd and 3rd MCP joints (R2 = 0.554 and 0.420, respectively). CONCLUSIONS: Our in-house software equipped with PIPOC could predict subsequent JSN progression with only short-term observations.

The analysis of Period1 gene expression in vivo and in vitro using a micro PMT system.

To detect a small amount of Period1 (Per1) expression, we developed a micro-photomultiplier tube (µPMT) system which can be used both in vivo and in vitro. Using this system, we succeeded in detecting Per1 gene expression in the skin of freely moving mice over 240 times higher compared with that of the tissue contact optical sensor (TCS) as previously reported. For in vitro studies, we succeeded in detecting elevated Per1 expression by streptozotocin (STZ) treatment in the scalp hairs at an early stage of diabetes, when glucose content in the blood was still normal. In addition, we could detect elevated Per1 expression in a single whisker hair at the time of diabetes onset. These results show that our µPMT system responds to minute changes in gene expression in freely moving mice in vivo and in mice hair follicles in vitro. Furthermore, Per1 in the hair can be used for a marker of diabetic aggravation.

Period1 gene expression in the olfactory bulb and liver of freely moving streptozotocin-treated diabetic mouse.

Clock genes express circadian rhythms in most organs. These rhythms are organized throughout the whole body, regulated by the suprachiasmatic nucleus (SCN) in the brain. Disturbance of these clock gene expression rhythms is a risk factor for diseases such as obesity. In the present study, to explore the role of clock genes in developing diabetes, we examined the effect of streptozotocin (STZ)-induced high glucose on Period1 (Per1) gene expression rhythm in the liver and the olfactory bub (OB) in the brain. We found a drastic increase of Per1 expression in both tissues after STZ injection while blood glucose content was low. After a rapid expression peak, Per1 expression showed no rhythm. Associated with an increase of glucose content, behavior became arrhythmic. Finally, we succeeded in detecting an increase of Per1 expression in mice hair follicles on day 1 after STZ administration, before the onset of symptoms. These results show that elevated Per1 expression by STZ plays an important role in the aggravation of diabetes.

Stability of d-luciferin for bioluminescence to detect gene expression in freely moving mice for long durations.

Circadian disturbance of clock gene expression is a risk factor for diseases such as obesity, cancer, and sleep disorders. To study these diseases, it is necessary to monitor and analyze the expression rhythm of clock genes in the whole body for a long duration. The bioluminescent reporter enzyme firefly luciferase and its substrate d-luciferin have been used to generate optical signals from tissues in vivo with high sensitivity. However, little information is known about the stability of d-luciferin to detect gene expression in living animals for a long duration. In the present study, we examined the stability of a luciferin solution over 21 days. l-Luciferin, which is synthesized using racemization of d-luciferin, was at high concentrations after 21 days. In addition, we showed that bioluminescence of Period1 (Per1) expression in the liver was significantly decreased compared with the day 1 solution, although locomotor activity rhythm was not affected. These results showed that d-luciferin should be applied to the mouse within, at most, 7 days to detect bioluminescence of Per1 gene expression rhythm in vivo.

Fundamental study on quality assurance (QA) procedures for a real-time tumor tracking radiotherapy (RTRT) system from the viewpoint of imaging devices.

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 (σ3D [mm]) of the gold marker, the mean of the pattern recognition score (PRS) and the standard deviation of the distance between rays (DBR) (σDBR [mm]) were evaluated. RESULTS: When tracking with speed of 10-60 mm/s, σDBR 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 (∫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.

Quantification of Joint Space Width Difference on Radiography Via Phase-Only Correlation (POC) Analysis: a Phantom Study Comparing with Various Tomographical Modalities Using Conventional Margin-Contouring.

Several visual scoring methods are currently used to assess progression of rheumatoid arthritis (RA) on radiography. However, they are limited by its subjectivity and insufficient sensitivity. We have developed an original measurement system which uses a technique called phase-only correlation (POC). The purpose of this study is to validate the system by using a phantom simulating the joint of RA patients.A micrometer measurement apparatus that can adjust arbitrary joint space width (JSW) in a phantom joint was developed to define true JSW. The phantom was scanned with radiography, 320 multi detector CT (MDCT), high-resolution peripheral quantitative CT (HR-pQCT), cone beam CT (CBCT), and tomosynthesis. The width was adjusted to the average size of a women's metacarpophalangeal joint, from 1.2 to 2.2 mm with increments of 0.1 mm and 0.01 mm. Radiographical images were analyzed by the POC-based system and manual method, and images from various tomographical modalities were measured via the automatic margin detection method. Correlation coefficients between true JSW difference and measured JSW difference were all strong at 0.1 mm intervals with radiography (POC-based system and manual method), CBCT, 320MDCT, HR-pQCT, and tomosynthesis. At 0.01 mm intervals, radiography (POC-based system), 320MDCT, and HR-pQCT had strong correlations, while radiography (manual method) and CBCT had low correlations, and tomosynthesis had no statistically significant correlation. The smallest detectable changes for radiography (POC-based system), radiography (manual method), 320MDCT, HR-pQCT, CBCT, and tomosynthesis were 0.020 mm, 0.041 mm, 0.076 mm, 0.077 mm, 0.057 mm, and 0.087 mm, respectively. We conclude that radiography analyzed with the POC-based system might sensitively detect minute joint space changes of the finger joint.

Double recording system of Period1 gene expression rhythm in the olfactory bulb and liver in freely moving mouse.

Clock genes express circadian rhythms in most organs. These rhythms are organized throughout the whole body, regulated by the suprachiasmatic nucleus (SCN) in the brain. Disturbance of these clock gene expression rhythms is a risk factor for diseases such as obesity and cancer. To understand the mechanism of regulating clock gene expression rhythms in vivo, multiple real time recording systems are required. In the present study, we developed a double recording system of Period1 expression rhythm in peripheral tissue (liver) and the brain. In peripheral tissue, quantification of gene expression in a steadily moving target was achieved by using a photomultiplier tube (PMT) attached to a tissue contact optical sensor (TCS). Using this technique, we were able to analyze circadian rhythms of clock gene expression over a prolonged period in the liver and olfactory bub (OB) of the brain. The present double recording system has no effect on behavioral activity or rhythm. Our novel system thus successfully quantifies clock gene expression in deep areas of the body in freely moving mice for a period sufficient to analyze circadian dynamics. In addition, our double recording system can be widely applied to many areas of biomedical research, as well as applications beyond medicine.

Mouse period1 gene expression recording from olfactory bulb under free moving conditions with a portable optic fibre device.

Because the disruption of circadian clock gene is a risk factor in many diseases such as obesity and cancer, it is important to monitor and analyzed the expression of the rhythm of the clock gene throughout the body over a long period of time. Although we previously reported on a new gene expression analysis system tracking a target position on the body surface of freely moving mice, the experimental apparatus required a large space. We have therefore developed an in vivo recording system using a portable photomultiplier tube (PMT) system attached to an optical fibre. Directly connecting the target area with the device, we could easily measure the photon counts in a very small space. However, little information is known about the characteristics of optical fibres when exposed to twisting/looping in association with a moving mouse and the effect of the surface of optical fibre. In the present study, we report on the characteristics of optical fibres to detect gene expression rhythm in freely moving mice. Using this portable optical device directly connected with a target area, we were able to measure the circadian rhythm of clock gene expression over a prolonged period in freely moving mice in a small space.

Validation of Fully Automatic Quantitative Software for Finger Joint Space Narrowing Progression for Rheumatoid Arthritis Patients.

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.

Quick and accurate selection of hand images among radiographs from various body parts using deep learning.

BACKGROUND: Although rheumatoid arthritis (RA) causes destruction of articular cartilage, early treatment significantly improves symptoms and delays progression. It is important to detect subtle damage for an early diagnosis. Recent software programs are comparable with the conventional human scoring method regarding detectability of the radiographic progression of RA. Thus, automatic and accurate selection of relevant images (e.g. hand images) among radiographic images of various body parts is necessary for serial analysis on a large scale. OBJECTIVE: In this study we examined whether deep learning can select target images from a large number of stored images retrieved from a picture archiving and communication system (PACS) including miscellaneous body parts of patients. METHODS: We selected 1,047 X-ray images including various body parts and divided them into two groups: 841 images for training and 206 images for testing. The training images were augmented and used to train a convolutional neural network (CNN) consisting of 4 convolution layers, 2 pooling layers and 2 fully connected layers. After training, we created software to classify the test images and examined the accuracy. RESULTS: The image extraction accuracy was 0.952 and 0.979 for unilateral hand and both hands, respectively. In addition, all 206 test images were perfectly classified into unilateral hand, both hands, and the others. CONCLUSIONS: Deep learning showed promise to enable efficiently automatic selection of target X-ray images of RA patients.

Intravoxel incoherent motion MRI for discrimination of synovial proliferation in the hand arthritis: A prospective proof-of-concept study.

BACKGROUND: Postcontrast-enhanced MRI is currently the reference standard for synovial proliferation in rheumatoid arthritis (RA). However, the technique is somewhat invasive due to the use of gadolinium contrast agents, which may cause severe adverse/side effects. Intravoxel incoherent motion (IVIM) simultaneously permits quantification of perfusion as well as diffusion using a single imaging scan. PURPOSE/HYPOTHESIS: To test the capability of IVIM MRI for noninvasive discrimination of synovial proliferation in hand arthritis. STUDY TYPE: Prospective. SUBJECTS: Seven suspected RA patients (three women and four men; mean age, 61 years; range, 26-74 years). FIELD STRENGTH/SEQUENCE: 3 T/short tau inversion recovery (STIR), IVIM, postcontrast-enhanced MRI. ASSESSMENT: Region of interest (ROI) was identified based on STIR. Contrast-enhanced MRI was evaluated using a 5-point grading scale of 0 (water) to 4 (synovial proliferation) according to the degree of contrast enhancement within the ROI. For each ROI, we calculated the apparent diffusion coefficient (ADC) and IVIM parameters (molecular diffusion coefficient [D], perfusion fraction [f], and perfusion-related diffusion coefficient [D*]). These parameters were subsequently compared with ROI contrast enhancement grades. STATISTICAL TESTS: Spearman's rank correlation test and a receiver operating characteristic (ROC) curve. RESULTS: A total of 90 ROIs of suspected synovial proliferation and/or joint effusion were identified. ROI grades were correlated with ADC and D values (r S = -0.385, P < 0.001, r S = -0.458, P < 0.0001, respectively), but not with the f and D* values (r S = -0.010, P = 0.936, r S = -0.084, P = 0.505, respectively). The area under the curves (AUCs) of D values (0.708-0.888, P = 0.002-0.0002) were slightly larger than those of ADC values (0.692-0.791, P = 0.013-0.001) when comparing low- vs. high-contrast enhancement grades. DATA CONCLUSION: The IVIM parameter D and ADC may be useful for the noninvasive identification of synovial proliferation in hand arthritis. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1199-1206.

Quantitative power Doppler signal assessment in the subchondral bone region of the metacarpophalangeal joint is an effective predictor of radiographic progression in the hand of rheumatoid arthritis: a pilot study.

Ultrasonography is useful for assessment of synovitis in the hand of rheumatoid arthritis (RA) patients. The aim of this study was to investigate the predictive value of the quantitative power Doppler (PD) signal assessment in the subchondral bone region of the metacarpophalangeal (MCP) joint in patients with RA showing radiographic progression of the hand by comparing with those of previously reported scoring systems. Twenty-two patients (20 women) with RA who underwent power Doppler ultrasonography (PDUS) of the bilateral one to five MCP joints at baseline were included in the study. Radiography of both hands was performed at baseline and at 1 year. PDUS of the synovial space was evaluated according to semi-quantitative scoring (0-3) and quantitative measurement (0-100%). The PD signal in the subchondral bone region was qualitatively (0, 1) and quantitatively (mm2) assessed. The performance of PDUS assessment was compared using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the risk ratio (RR). As a predictor for radiographic progression, the quantitative PD signal assessment in the subchondral bone region (AUC = 0.842, p < 0.01) was equivalent to quantitative vascularity (AUC = 0.817, p < 0.05) and semi-quantitative scoring (AUC = 0.754, p < 0.05). As for the RR of the PD signal in the subchondral bone region for radiographic progression, the quantitative PD signal assessment was 5.40 (p < 0.01), whereas the qualitative PD signal assessment was 1.60 (p = 0.204). Quantitative PD signal assessment in the subchondral bone region can predict radiographic progression in the hand of RA patients.

Quantification of hand synovitis in rheumatoid arthritis: Arterial mask subtraction reinforced with mutual information can improve accuracy of pixel-by-pixel time-intensity curve shape analysis in dynamic MRI.

BACKGROUND: Synovitis, which is a hallmark of rheumatoid arthritis (RA), needs to be precisely quantified to determine the treatment plan. Time-intensity curve (TIC) shape analysis is an objective assessment method for characterizing the pixels as artery, inflamed synovium, or other tissues using dynamic contrast-enhanced MRI (DCE-MRI). PURPOSE/HYPOTHESIS: To assess the feasibility of our original arterial mask subtraction method (AMSM) with mutual information (MI) for quantification of synovitis in RA. STUDY TYPE: Prospective study. SUBJECTS: Ten RA patients (nine women and one man; mean age, 56.8 years; range, 38-67 years). FIELD STRENGTH/SEQUENCE: 3T/DCE-MRI. ASSESSMENT: After optimization of TIC shape analysis to the hand region, a combination of TIC shape analysis and AMSM was applied to synovial quantification. The MI between pre- and postcontrast images was utilized to determine the arterial mask phase objectively, which was compared with human subjective selection. The volume of objectively measured synovitis by software was compared with that of manual outlining by an experienced radiologist. Simple TIC shape analysis and TIC shape analysis combined with AMSM were compared in slices without synovitis according to subjective evaluation. STATISTICAL TESTS: Pearson's correlation coefficient, paired t-test and intraclass correlation coefficient (ICC). RESULTS: TIC shape analysis was successfully optimized in the hand region with a correlation coefficient of 0.725 (P < 0.01) with the results of manual assessment regarded as ground truth. Objective selection utilizing MI had substantial agreement (ICC = 0.734) with subjective selection. Correlation of synovial volumetry in combination with TIC shape analysis and AMSM with manual assessment was excellent (r = 0.922, P < 0.01). In addition, negative predictive ability in slices without synovitis pixels was significantly increased (P < 0.01). DATA CONCLUSIONS: The combination of TIC shape analysis and image subtraction reinforced with MI can accurately quantify synovitis of RA in the hand by eliminating arterial pixels. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Radiographic temporal subtraction analysis can detect finger joint space narrowing progression in rheumatoid arthritis with clinical low disease activity.

Background Recent papers suggest that finger joints with positive synovial vascularity (SV) assessed by ultrasonography under clinical low disease activity (CLDA) in rheumatoid arthritis (RA) patients may cause joint space narrowing (JSN) progression. Purpose To investigate the performance of a computer-based method by directly comparing with the conventional scoring method in terms of the detectability of JSN progression in hand radiography of RA patients with CLDA. Material and Methods Fifteen RA patients (13 women, 2 men) with long-term sustained CLDA of >2 years were included. Radiological progression of finger joints was measured or scored using the computer-based method which can detect JSN progression between two radiographic images as the joint space difference index (JSDI), as well as the Genant-modified Sharp score (GSS). We also quantitatively assessed SV of these joints using ultrasonography. Results Out of 270 joints, we targeted 259 finger joints after excluding nine damaged joints (four ankylosis, three complete luxation, and two subluxation) and two improved joints according to the GSS results. The JSDI of finger joints with JSN progression was significantly higher than those without JSN progression ( P = 0.018). The JSDI of finger joints with ultrasonographic SV was significantly higher than those without ultrasonographic SV ( P = 0.004). Progression in JSDI showed stronger associations with ultrasonographic SV than progression in GSS (odds ratio [95% confidence interval]: 7.19 [3.37-15.36] versus 5.84 [2.76-12.33]). Conclusion The computer-based method was comparable to the conventional scoring method regarding the detectability of JSN progression in RA patients with CLDA.

A reliability study using computer-based analysis of finger joint space narrowing in rheumatoid arthritis patients.

The joint space difference index (JSDI) is a newly developed radiographic index which can quantitatively assess joint space narrowing progression of rheumatoid arthritis (RA) patients by using an image subtraction method on a computer. The aim of this study was to investigate the reliability of this method by non-experts utilizing RA image evaluation. Four non-experts assessed JSDI for radiographic images of 510 metacarpophalangeal joints from 51 RA patients twice with an interval of more than 2 weeks. Two rheumatologists and one radiologist as well as the four non-experts examined the joints by using the Sharp-van der Heijde Scoring (SHS) method. The radiologist and four non-experts repeated the scoring with an interval of more than 2 weeks. We calculated intra-/inter-observer reliability using the intra-class correlation coefficients (ICC) for JSDI and SHS scoring, respectively. The intra-/inter-observer reliabilities for the computer-based method were almost perfect (inter-observer ICC, 0.966-0.983; intra-observer ICC, 0.954-0.996). Contrary to this, intra-/inter-observer reliability for SHS by experts was moderate to almost perfect (inter-observer ICC, 0.556-0.849; intra-observer ICC, 0.589-0.839). The results suggest that our computer-based method has high reliability to detect finger joint space narrowing progression in RA patients.

Power Doppler signal calibration in the finger joint between two models of ultrasound machine: a pilot study using a phantom and joints in patients with rheumatoid arthritis.

Background Despite the advantages of ultrasound (US) in the management of rheumatoid arthritis (RA) patients, power Doppler (PD) US may be highly dependent on the type of US machine used. Purpose To present a method to calibrate the PD signal of two models of US machines by use of a flow phantom and finger joints of patients with RA. Material and Methods For the phantom study, the PD signal count was measured in the flow phantom perfusing blood mimicking fluid at various injection rates and pulse repetition frequencies (PRFs). The quantitative PD index was calculated with ImageJ. For the clinical study, the second and third metacarpophalangeal joints of five consecutive patients with RA were examined. The quantitative PD index was measured at various PRFs by use of two models of machine (the same models as the phantom study). Results For the phantom and clinical studies, negative correlations were found between the PRF and the quantitative PD index when the flow velocity was constant and positive correlations between flow velocity and the quantitative PD index at constant PRF. There was a significant difference in the depiction performance of synovial blood flow between the two models, which can be calibrated by adjusting the PRF values derived from the phantom study in each model. Conclusion Signal calibration of pannus vascularity between US machines may be possible by adjusting the PRF value according to flow phantom data. Different US machines can thus provide equivalent examination results concerning the pannus vascularity.

Semi-Automated Quantification of Finger Joint Space Narrowing Using Tomosynthesis in Patients with Rheumatoid Arthritis.

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 < 0.001). There was significant, negative correlation between measured joint space width and tomosynthesis scores with r = -0.606 (P < 0.001) in metacarpophalangeal joints and r = -0.518 (P < 0.001) in proximal interphalangeal joints. Inter-observer and intra-observer agreement of the semi-automated method using tomosynthesis images was in almost perfect agreement with intra-class correlation coefficient (ICC) values of 0.964 and 0.963, respectively. The semi-automated method using tomosynthesis images provided sensitive, quantitative, and reproducible measurement of finger joint space in patients with RA.

Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions.

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.