Fully automatic quantification for hand synovitis in rheumatoid arthritis using pixel-classification-based segmentation network in DCE-MRI

PURPOSE

A classification-based segmentation method is proposed to quantify synovium in rheumatoid arthritis (RA) patients using a deep learning (DL) method based on time-intensity curve (TIC) analysis in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

This retrospective study analyzed a hand MR dataset of 28 RA patients (six males, mean age 53.7 years). A researcher, under expert guidance, used in-house software to delineate regions of interest (ROIs) for hand muscles, bones, and synovitis, generating a dataset with 27,255 pixels with corresponding TICs (muscle: 11,413, bone: 8502, synovitis: 7340). One experienced musculoskeletal radiologist performed ground truth segmentation of enhanced pannus in the joint bounding box on the 10th DCE phase, or around 5 min after contrast injection. Data preprocessing included median filtering for noise reduction, phase-only correlation algorithm for motion correction, and contrast-limited adaptive histogram equalization for improved image contrast and noise suppression. TIC intensity values were normalized using zero-mean normalization. A DL model with dilated causal convolution and SELU activation function was developed for enhanced pannus segmentation, tested using leave-one-out cross-validation.

RESULTS

407 joint bounding boxes were manually segmented, with 129 synovitis masks. On the pixel-based level, the DL model achieved sensitivity of 85%, specificity of 98%, accuracy of 99% and precision of 84% for enhanced pannus segmentation, with a mean Dice score of 0.73. The false-positive rate for predicting cases without synovitis was 0.8%. DL-measured enhanced pannus volume strongly correlated with ground truth at both pixel-based (r = 0.87, p < 0.001) and patient-based levels (r = 0.84, p < 0.001). Bland-Altman analysis showed the mean difference for hand joints at the pixel-based and patient-based levels were -9.46 mm3 and -50.87 mm3, respectively.

CONCLUSION

Our DL-based DCE-MRI TIC shape analysis has the potential for automatic segmentation and quantification of enhanced synovium in the hands of RA patients.

A Deep Learning-Based Model for Classifying Osteoporotic Lumbar Vertebral Fractures on Radiographs: A Retrospective Model Development and Validation Study

Early diagnosis and initiation of treatment for fresh osteoporotic lumbar vertebral fractures (OLVF) are crucial. Magnetic resonance imaging (MRI) is generally performed to differentiate between fresh and old OLVF. However, MRIs can be intolerable for patients with severe back pain. Furthermore, it is difficult to perform in an emergency. MRI should therefore only be performed in appropriately selected patients with a high suspicion of fresh fractures. As radiography is the first-choice imaging examination for the diagnosis of OLVF, improving screening accuracy with radiographs will optimize the decision of whether an MRI is necessary. This study aimed to develop a method to automatically classify lumbar vertebrae (LV) conditions such as normal, old, or fresh OLVF using deep learning methods with radiography. A total of 3481 LV images for training, validation, and testing and 662 LV images for external validation were collected. Visual evaluation by two radiologists determined the ground truth of LV diagnoses. Three convolutional neural networks were ensembled. The accuracy, sensitivity, and specificity were 0.89, 0.83, and 0.92 in the test and 0.84, 0.76, and 0.89 in the external validation, respectively. The results suggest that the proposed method can contribute to the accurate automatic classification of LV conditions on radiography.

A deep registration method for accurate quantification of joint space narrowing progression in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to progressive articular destruction and severe disability. Joint space narrowing (JSN) has been regarded as an important indicator for RA progression and has received significant attention. Radiology plays a crucial role in the diagnosis and monitoring of RA through the assessment of joint space. A new framework for monitoring joint space by quantifying joint space narrowing (JSN) progression through image registration in radiographic images has emerged as a promising research direction. This framework offers the advantage of high accuracy; however, challenges still exist in reducing mismatches and improving reliability. In this work, we utilize a deep intra-subject rigid registration network to automatically quantify JSN progression in the early stages of RA. In our experiments, the mean-square error of the Euclidean distance between the moving and fixed images was 0.0031, the standard deviation was 0.0661 mm and the mismatching rate was 0.48%. Our method achieves sub-pixel level accuracy, surpassing manual measurements significantly. The proposed method is robust to noise, rotation and scaling of joints. Moreover, it provides misalignment visualization, which can assist radiologists and rheumatologists in assessing the reliability of quantification, exhibiting potential for future clinical applications. As a result, we are optimistic that our proposed method will make a significant contribution to the automatic quantification of JSN progression in RA. Code is available at https://github.com/pokeblow/Deep-Registration-QJSN-Finger.git.

Analysis of the Anticipatory Behavior Formation Mechanism Induced by Methamphetamine Using a Single Hair

While the suprachiasmatic nucleus (SCN) coordinates many daily rhythms, some circadian patterns of expression are controlled by SCN-independent systems. These include responses to daily methamphetamine (MAP) injections. Scheduled daily injections of MAP resulted in anticipatory activity, with an increase in locomotor activity immediately prior to the time of injection. The MAP-induced anticipatory behavior is associated with the induction and a phase advance in the expression rhythm of the clock gene Period1 (Per1). However, this unique formation mechanism of MAP-induced anticipatory behavior is not well understood. We recently developed a micro-photomultiplier tube (micro-PMT) system to detect a small amount of Per1 expression. In the present study, we used this system to measure the formation kinetics of MAP-induced anticipatory activity in a single whisker hair to reveal the underlying mechanism. Our results suggest that whisker hairs respond to daily MAP administration, and that Per1 expression is affected. We also found that elevated Per1 expression in a single whisker hair is associated with the occurrence of anticipatory behavior rhythm. The present results suggest that elevated Per1 expression in hairs might be a marker of anticipatory behavior formation.

Fully automatic software for detecting radiographic joint space narrowing progression in rheumatoid arthritis: phantom study and comparison with visual assessment

PURPOSE

We have developed an in-house software equipped with partial image phase-only correlation (PIPOC) which can automatically quantify radiographic joint space narrowing (JSN) progression. The purpose of this study was to evaluate the software in phantom and clinical assessments.

MATERIALS AND METHODS

In the phantom assessment, the software's performance on radiographic images was compared to the joint space width (JSW) difference using a micrometer as ground truth. A phantom simulating a finger joint was scanned underwater. In the clinical assessment, 15 RA patients were included. The software measured the radiological progression of the finger joints between baseline and the 52nd week. The cases were also evaluated with the Genant-modified Sharp score (GSS), a conventional visual scoring method. We also quantitatively assessed these joints' synovial vascularity (SV) on power Doppler ultrasonography (0, 8, 20 and 52 weeks).

RESULTS

In the phantom assessment, the PIPOC software could detect changes in JSN with a smallest detectable difference of 0.044 mm at 0.1 mm intervals. In the clinical assessment, the JSW change of the joints with GSS progression detected by the software was significantly greater than those without GSS progression (p = 0.004). The JSW change of joints with positive SV at baseline was significantly higher than those with negative SV (p = 0.024).

CONCLUSION

Our in-house software equipped with PIPOC can automatically and quantitatively detect slight radiographic changes of JSW in clinically inactive RA patients.

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.

Giant Intraosseous Cyst-Like Lesions of the Metacarpal Bones in Rheumatoid Arthritis

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.

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.

Fully automatic quantitative software for assessment of minute finger joint space narrowing progression on radiographs: evaluation in rheumatoid arthritis patients with long-term sustained clinical low disease activity

PURPOSE

Rheumatoid arthritis (RA) causes joint space narrowing (JSN) as a form of joint destruction. 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. This study aims to evaluate the application of "machine vision" for radiographic image of the finger joints.

MATERIALS AND METHODS

Fifteen RA patients with long-term sustained clinical low disease activity were recruited. All patients underwent hand radiography and power Doppler ultrasonography (PDUS). The JSN was evaluated using the Genant-modified Sharp scoring (GSS) method and the automatic system. Synovial vascularity (SV) was assessed quantitatively using ultrasonography.

RESULTS

There were no significant differences in the JSDI between the joints with JSN and those without JSN on GSS (p = 0.052). The JSDI of the joints with SV was significantly higher than those without SV (p = 0.043). The JSDI of the no therapeutic response group was significantly higher than those of the response group (p < 0.001).

CONCLUSION

Our software can automatically evaluate temporal changes of JSN, which might free rheumatologists / radiologists from the burden of scoring hand radiography.

Convolutional neural network for classification of two-dimensional array images generated from clinical information may support diagnosis of rheumatoid arthritis

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.

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.

Critical Issues in Dental and Medical Management of Obstructive Sleep Apnea

This critical review focuses on obstructive sleep apnea (OSA) and its management from a dental medicine perspective. OSA is characterized by ≥10-s cessation of breathing (apnea) or reduction in airflow (hypopnea) ≥5 times per hour with a drop in oxygen and/or rise in carbon dioxide. It can be associated with sleepiness and fatigue, impaired mood and cognition, cardiometabolic complications, and risk for transportation and work accidents. Although sleep apnea is diagnosed by a sleep physician, its management is interdisciplinary. The dentist’s role includes 1) screening patients for OSA risk factors (e.g., retrognathia, high arched palate, enlarged tonsils or tongue, enlarged tori, high Mallampati score, poor sleep, supine sleep position, obesity, hypertension, morning headache or orofacial pain, bruxism); 2) referring to an appropriate health professional as indicated; and 3) providing oral appliance therapy followed by regular dental and sleep medical follow-up. In addition to the device features and provider expertise, anatomic, behavioral, demographic, and neurophysiologic characteristics can influence oral appliance effectiveness in managing OSA. Therefore, OSA treatment should be tailored to each patient individually. This review highlights some of the putative action mechanisms related to oral appliance effectiveness and proposes future research directions.

Detection of Fine Radiographic Progression in Finger Joint Space Narrowing Beyond Human Eyes: Phantom Experiment and Clinical Study with Rheumatoid Arthritis Patients

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 < 0.001). Rheumatologists were difficult to detect JSW difference of 0.30 mm or less. The JSDI of finger joints with SV was significantly higher than those without SV (P = 0.030). The software can detect fine differences in JSW that are visually unrecognizable.

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.

Composite assessment of power Doppler ultrasonography and MRI in rheumatoid arthritis: a pilot study of predictive value in radiographic progression after one year

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.

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.

Longitudinal CT study of sarcopenia due to hepatic failure after living donor liver transplantation

Background

The quantity and quality of skeletal muscle have been observed to be closely related with post-transplantation mortality in patients undergoing living donor liver transplantation (LDLT). However, the effect of LDLT on skeletal muscle has not been thoroughly investigated. The aim of this study was to investigate the change of trunk muscle mass and adiposity in recipients of LDLT.

Methods

The study population included LDLT recipients at Hokkaido University Hospital who underwent pre- and post-operative computed tomography (CT) scans (31 recipients; 14 males, and 17 females). The cross-sectional area of the dorsal muscle group at the 12th thoracic vertebra (Th12) was measured with the dorsal muscle group mass index (DMGMI), while the psoas muscle at the upper border of 4th lumber vertebra (L4) was measured with the psoas muscle mass index (PMI). Muscle adiposity of the dorsal muscle group was also measured with the intramuscular adipose tissue content (IMAC). For these data, the correlation between pre-operative values and follow-up changes (post-operative values minus pre-operative values) were analyzed. Each sex was evaluated separately.

Results

A statistically significant correlation was detected between pre-operative values and follow-up differences in DMGMI for both sexes (male: r=-0.675, P=0.008; female: r=-0.687, P=0.002) and in PMI for both sexes (males: r=-0.739, P=0.003; females: r=-0.641, P=0.006). The correlation of pre-operative values and follow-up differences for IMAC was not statistically significant with r=0.132 (P=0.700) and r=-0.498 (P=0.071) for males and females, respectively.

Conclusions

Improvement of sarcopenia in recipients of LDLT can be demonstrated regardless of sex using volumetric CT.

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.

Visceral adipose tissue area measurement at a single level: can it represent visceral adipose tissue volume?

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 3cm 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.

Cartilage quantification using contrast-enhanced MRI in the wrist of rheumatoid arthritis: cartilage loss is associated with bone marrow edema

OBJECTIVE

To quantify wrist cartilage using contrast MRI and compare with the extent of adjacent synovitis and bone marrow edema (BME) in patients with rheumatoid arthritis (RA).

METHODS

18 patients with RA underwent post-contrast fat-suppressed T₁weighted coronal imaging. Cartilage area at the centre of the scaphoid-capitate and radius-scaphoid joints was measured by in-house developed software. We defined cartilage as the pixels with signal intensity between two thresholds (lower: 0.4, 0.5 and 0.6 times the muscle signal, upper: 0.9, 1.0, 1.1, 1.2 and 1.3 times the muscle signal). We investigated the association of cartilage loss with synovitis and BME score derived from RA MRI scoring system.

RESULTS

Cartilage area was correlated with BME score when thresholds were adequately set with lower threshold at 0.6 times the muscle signal and upper threshold at 1.2 times the muscle signal for both SC (r_s=-0.469, p < 0.05) and RS (r_s=-0.486, p < 0.05) joints, while it showed no significant correlation with synovitis score at any thresholds.

CONCLUSION

Our software can accurately quantify cartilage in the wrist and BME associated with cartilage loss in patients with RA. Advances in knowledge: Our software can quantify cartilage using conventional MR images of the wrist. BME is associated with cartilage loss in RA patients.

Pre-operative volume rather than area of skeletal muscle is a better predictor for post-operative risks for respiratory complications in living-donor liver transplantation

OBJECTIVE

To demonstrate the superiority of total psoas volume (TPV) over total psoas area (TPA) in terms of predicting post-operative complications in living-donor liver transplantation (LDLT).

METHODS

The TPA and TPV were assessed in 32 recipients who underwent CT before LDLT. The TPA was measured using an axial CT image at the level of the upper margin of the fourth lumbar vertebral body. The TPV was calculated using all the CT images from the muscle origin through the level of the pubic symphysis. Patients were divided into a sarcopenia group and no-sarcopenia group based on the medians of normalized TPA (nTPA) and normalized TPV (nTPV). We calculated the odds ratio (OR) of post-operative respiratory complications in relation to nTPA and nTPV, respectively.

RESULTS

Out of 32 recipients, 17 recipients experienced at least 1 post-operative respiratory complication. The OR for males according to nTPV [OR = 15.00, 95% confidence interval (CI) = 1.03-218.31; p = 0.031] was higher than that for nTPA (OR = 3.33, 95% CI = 0.36-30.70; p = 0.280). The OR for females according to nTPV (OR = 4.00, 95% CI = 0.56-28.40; p = 0.16) was the same as that for nTPA (OR = 4.00, 95% CI = 0.56-28.40; p = 0.16).

CONCLUSION

Pre-operative volume of the skeletal muscle might be a better predictor for post-operative risks in LDLT recipients than pre-operative area of the skeletal muscle. Advances in knowledge: Post-operative risks for respiratory complications in LDLT recipients might be evaluated more accurately by using TPV instead of TPA.

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.

Pixel-by-Pixel Arterial Spin Labeling Blood Flow Pattern Variation Analysis for Discrimination of Rheumatoid Synovitis: A Pilot Study

We examined the capability of a gray-scale arterial spin labeling blood flow pattern variation (BFPV) map with two different post labeling delay (PLD) times to discriminate pannus in patients with rheumatoid arthritis (RA) at 3T. There was a statistically significant difference in the BFPV values between artery, pannus, and surrounding tissue. Furthermore, the color-coded BFPV map was able to accurately distinguish pannus from other tissues. These results suggest this approach may be capable of identifying pannus noninvasively.

Microbialite response to an anthropogenic salinity gradient in Great Salt Lake, Utah

A railroad causeway across Great Salt Lake, Utah (GSL), has restricted water flow since its construction in 1959, resulting in a more saline North Arm (NA; 24%-31% salinity) and a less saline South Arm (SA; 11%-14% salinity). Here, we characterized microbial carbonates collected from the SA and the NA to evaluate the effect of increased salinity on community composition and abundance and to determine whether the communities present in the NA are still actively precipitating carbonate or if they are remnant features from prior to causeway construction. SSU rRNA gene abundances associated with the NA microbialite were three orders of magnitude lower than those associated with the SA microbialite, indicating that the latter community is more productive. SSU rRNA gene sequencing and functional gene microarray analyses indicated that SA and NA microbialite communities are distinct. In particular, abundant sequences affiliated with photoautotrophic taxa including cyanobacteria and diatoms that may drive carbonate precipitation and thus still actively form microbialites were identified in the SA microbialite; sequences affiliated with photoautotrophic taxa were in low abundance in the NA microbialite. SA and NA microbialites comprise smooth prismatic aragonite crystals. However, the SA microbialite also contained micritic aragonite, which can be formed as a result of biological activity. Collectively, these observations suggest that NA microbialites are likely to be remnant features from prior to causeway construction and indicate a strong decrease in the ability of NA microbialite communities to actively precipitate carbonate minerals. Moreover, the results suggest a role for cyanobacteria and diatoms in carbonate precipitation and microbialite formation in the SA of GSL.

Tomosynthesis can facilitate accurate measurement of joint space width under the condition of the oblique incidence of X-rays in patients with rheumatoid arthritis

OBJECTIVE

Accurate evaluation of joint space width (JSW) is important in the assessment of rheumatoid arthritis (RA). In clinical radiography of bilateral hands, the oblique incidence of X-rays is unavoidable, which may cause perceptional or measurement error of JSW. The objective of this study was to examine whether tomosynthesis, a recently developed modality, can facilitate a more accurate evaluation of JSW than radiography under the condition of oblique incidence of X-rays.

METHODS

We investigated quantitative errors derived from the oblique incidence of X-rays by imaging phantoms simulating various finger joint spaces using radiographs and tomosynthesis images. We then compared the qualitative results of the modified total Sharp score of a total of 320 joints from 20 patients with RA between these modalities.

RESULTS

A quantitative error was prominent when the location of the phantom was shifted along the JSW direction. Modified total Sharp scores of tomosynthesis images were significantly higher than those of radiography, that is to say JSW was regarded as narrower in tomosynthesis than in radiography when finger joints were located where the oblique incidence of X-rays is expected in the JSW direction.

CONCLUSION

Tomosynthesis can facilitate accurate evaluation of JSW in finger joints of patients with RA, even with oblique incidence of X-rays.

ADVANCES IN KNOWLEDGE

Accurate evaluation of JSW is necessary for the management of patients with RA. Through phantom and clinical studies, we demonstrate that tomosynthesis may achieve more accurate evaluation of JSW.

Accurate quantitative assessment of synovitis in rheumatoid arthritis using pixel-by-pixel, time-intensity curve shape analysis

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.

Radiographic quantifications of joint space narrowing progression by computer-based approach using temporal subtraction in rheumatoid wrist

OBJECTIVE

To investigate the validity of a computer-based method using temporal subtraction in carpal joints of patients with rheumatoid arthritis (RA), which can detect the difference in joint space between two images with the joint space difference index (JSDI).

METHODS

The study consisted of 43 patients with RA (39 females and 4 males) who underwent radiography at baseline and at 1-year follow-up. The joint space narrowing (JSN) of carpal joints on bilateral hand radiographs was assessed by our computer-based method, using the Sharp/van der Heijde method as the standard of reference. We compared the JSDI of joints with JSN progression in the follow-up period with that of those without JSN progression. In addition, we examined whether there is a significant difference in JSDI in terms of laterality or topology of the joint.

RESULTS

The JSDI of joints with JSN progression was significantly higher than that of those without JSN progression (Mann-Whitney U test, p < 0.001). There was no statistically significant difference in the JSDI between the left and right carpal joints, which was analysed for five different joints altogether and each joint separately (Mann-Whitney U test, p > 0.05). There was statistically significant difference in JSDI among different joints (Kruskal-Wallis test, p = 0.003).

CONCLUSION

These results suggest that our computer-based method may be useful to recognize the JSN progression on radiographs of rheumatoid wrists.

ADVANCES IN KNOWLEDGE

The computer-based temporal subtraction method can detect the JSN progression in the wrist, which is the single most commonly involved site in RA.

Performance of computer-based analysis using temporal subtraction to assess joint space narrowing progression in rheumatoid patients

Our computer-based method can detect the chronological change in joint space width between baseline and follow-up images as the joint space difference index (JSDI). The aim of this study was to verify the sensitivity and specificity of our computer-based method in assessment of joint space narrowing progression in rheumatoid patients. Twenty-seven patients (24 women and 3 men) with rheumatoid arthritis underwent radiography of the bilateral hand at baseline and at 1 year. The joint space narrowing (JSN) of a total of 252 metacarpophalangeal (MCP) joints and 229 carpal joints was assessed by our computer-based method, setting the Sharp/van der Heijde method as the gold standard. We constructed a receiver operating characteristic curve by using the Sharp/van der Heijde method as the gold standard and set the optimal cutoff on JSDI for MCP, carpal, and MCP/carpal joints. We then calculated the sensitivity and specificity for each cutoff in assessment of JSN progression. At the most discriminant cutoff, the sensitivity and specificity of the computer-based method for MCP joints was 78.6 versus 85.3 %, respectively (AUC = 0.837; P < 0.001). Carpal joints revealed a lower sensitivity and specificity with 64.7 and 86.8 % (AUC = 0.775; P < 0.001). Furthermore, the sensitivity and specificity for MCP/carpal joints was 71.0 versus 83.6 %, respectively (AUC = 0.778; P < 0.001). The computer-based method presented a reliable assessment of JSN progression with high sensitivity and specificity and may be useful in follow-up assessment of the joint damage in rheumatoid patients.