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Article ; Online: MRI for axial SpA: Diagnosis, disease activity assessment, and recent advances.

Chan, Shirley Chiu Wai / Chung, Ho Yin

International journal of rheumatic diseases

2024 Volume 27, Issue 1, Page(s) e15014

Abstract: Magnetic resonance imaging (MRI) is a sensitive imaging modality to detect early inflammatory changes in axial spondyloarthritis (SpA). Over a decade has passed since the inclusion of MRI assessment in the 2009 Assessment of SpondyloArthritis ... ...

Abstract	Magnetic resonance imaging (MRI) is a sensitive imaging modality to detect early inflammatory changes in axial spondyloarthritis (SpA). Over a decade has passed since the inclusion of MRI assessment in the 2009 Assessment of SpondyloArthritis International Society (ASAS) classification criteria for axial SpA. Evidence and clinical experience of MRI in axial SpA have accumulated rapidly since. This has led to a better understanding of the clinical utility of MRI in early diagnosis, disease activity assessment, and monitoring of treatment response in axial SpA. Furthermore, technological advancements have paved the way for the development of novel MRI sequences for the quantification of inflammation and image optimization. The field of artificial intelligence has also been explored to aid medical imaging interpretation, including MRI in axial SpA. This review serves to provide an update on the latest understanding of the evolving roles of MRI in axial SpA.
MeSH term(s)	Humans ; Sacroiliac Joint/pathology ; Sacroiliitis/diagnosis ; Artificial Intelligence ; Spondylarthritis/diagnosis ; Magnetic Resonance Imaging ; Axial Spondyloarthritis
Language	English
Publishing date	2024-01-30
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2426924-4
ISSN	1756-185X ; 1756-1841
ISSN (online)	1756-185X
ISSN	1756-1841
DOI	10.1111/1756-185X.15014
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Article ; Online: A deep neural network for MRI spinal inflammation in axial spondyloarthritis.

Lin, Yingying / Chan, Shirley Chiu Wai / Chung, Ho Yin / Lee, Kam Ho / Cao, Peng

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society

2024

Abstract: Objective: To develop a deep neural network for the detection of inflammatory spine in short tau inversion recovery (STIR) sequence of magnetic resonance imaging (MRI) on patients with axial spondyloarthritis (axSpA).: Methods: A total 330 patients ... ...

Abstract	Objective: To develop a deep neural network for the detection of inflammatory spine in short tau inversion recovery (STIR) sequence of magnetic resonance imaging (MRI) on patients with axial spondyloarthritis (axSpA). Methods: A total 330 patients with axSpA were recruited. STIR MRI of the whole spine and clinical data were obtained. Regions of interests (ROIs) were drawn outlining the active inflammatory lesion consisting of bone marrow edema (BME). Spinal inflammation was defined by the presence of an active inflammatory lesion on the STIR sequence. The 'fake-color' images were constructed. Images from 270 and 60 patients were randomly separated into the training/validation and testing sets, respectively. Deep neural network was developed using attention UNet. The neural network performance was compared to the image interpretation by a radiologist blinded to the ground truth. Results: Active inflammatory lesions were identified in 2891 MR images and were absent in 14,590 MR images. The sensitivity and specificity of the derived deep neural network were 0.80 ± 0.03 and 0.88 ± 0.02, respectively. The Dice coefficient of the true positive lesions was 0.55 ± 0.02. The area under the curve of the receiver operating characteristic (AUC-ROC) curve of the deep neural network was 0.87 ± 0.02. The performance of the developed deep neural network was comparable to the interpretation of a radiologist with similar sensitivity and specificity. Conclusion: The developed deep neural network showed similar sensitivity and specificity to a radiologist with four years of experience. The results indicated that the network can provide a reliable and straightforward way of interpreting spinal MRI. The use of this deep neural network has the potential to expand the use of spinal MRI in managing axSpA.
Language	English
Publishing date	2024-01-08
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1115375-1
ISSN	1432-0932 ; 0940-6719
ISSN (online)	1432-0932
ISSN	0940-6719
DOI	10.1007/s00586-023-08099-0
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Zs.A 3437: Show issues

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Article ; Online: Deep Learning Algorithm of the SPARCC Scoring System in SI Joint MRI.

Lin, Yingying / Cao, Peng / Chan, Shirley Chiu Wai / Lee, Kam Ho / Lau, Vince Wing Hang / Chung, Ho Yin

Journal of magnetic resonance imaging : JMRI

2024

Abstract: Background: The Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system is a sacroiliitis grading system.: Purpose: To develop a deep learning-based pipeline for grading sacroiliitis using the SPARCC scoring system.: Study type: ... ...

Abstract	Background: The Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system is a sacroiliitis grading system. Purpose: To develop a deep learning-based pipeline for grading sacroiliitis using the SPARCC scoring system. Study type: Prospective. Population: The study included 389 participants (42.2-year-old, 44.6% female, 317/35/37 for training/validation/testing). A pretrained algorithm was used to differentiate image with/without sacroiliitis. Field strength/sequence: 3-T, short tau inversion recovery (STIR) sequence, fast spine echo. Assessment: The regions of interest as ground truth for models' training were identified by a rheumatologist (HYC, 10-year-experience) and a radiologist (KHL, 6-year-experience) using the Assessment of Spondyloarthritis International Society definition of MRI sacroiliitis independently. Another radiologist (YYL, 4.5-year-experience) solved the discrepancies. The bone marrow edema (BME) and sacroiliac region models were for segmentation. Frangi-filter detected vessels used as intense reference. Deep learning pipeline scored using SPARCC scoring system evaluating presence and features of BMEs. A rheumatologist (SCWC, 6-year-experience) and a radiologist (VWHL, 14-year-experience) scored using the SPARCC scoring system once. The radiologist (YYL) scored twice with 5-day interval. Statistical tests: Independent samples t-tests and Chi-squared tests were used. Interobserver and intraobserver reliability by intraclass correlation coefficient (ICC) and Pearson coefficient evaluated consistency between readers and the deep learning pipeline. We evaluated the performance using sensitivity, accuracy, positive predictive value, and Dice coefficient. A P-value <0.05 was considered statistically significant. Results: The ICC and the Pearson coefficient between the SPARCC scores from three readers and the deep learning pipeline were 0.83 and 0.86, respectively. The sensitivity in identifying BME and accuracy of identifying SI joints and blood vessels was 0.83, 0.90, and 0.88, respectively. The dice coefficients were 0.82 (sacrum) and 0.80 (ilium). Data conclusion: The high consistency with human readers indicated that deep learning pipeline may provide a SPARCC-informed deep learning approach for scoring of STIR images in spondyloarthritis. Evidence level: 1 TECHNICAL EFFICACY: Stage 2.
Language	English
Publishing date	2024-01-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.29211
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Zs.A 3648: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Systemic Lupus Erythematosus and Immunodeficiency.

Chan, Shirley Chiu Wai / Lau, Chak Sing

Rheumatology and immunology research

2021 Volume 2, Issue 3, Page(s) 131–138

Abstract: Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease caused by a combination of genetic, epigenetic, and environmental factors. Recent advances in genetic analysis coupled with better understanding of different immune regulatory and ... ...

Abstract	Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease caused by a combination of genetic, epigenetic, and environmental factors. Recent advances in genetic analysis coupled with better understanding of different immune regulatory and signaling pathways have revealed the complex relationship between autoimmunity, including SLE, and immunodeficiency. Furthermore, the expanding therapeutic armamentarium has led to the increasing awareness of secondary immunodeficiency in these patients. This article serves to update the current understanding of SLE and immunodeficiency by discussing the shared genetic factors and immunobiology. We also summarize the effects of immunosuppressive therapies with a focus on secondary antibody deficiency (SAD) after B-cell targeted therapies.
Language	English
Publishing date	2021-12-15
Publishing country	Germany
Document type	Journal Article ; Review
ISSN	2719-4523
ISSN (online)	2719-4523
DOI	10.2478/rir-2021-0019
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Article ; Online: Risk of nonpulmonary infections requiring hospitalization in spondyloarthritis.

Chung, Ho Yin / Chan, Shirley Chiu Wai / Sun, Frances Sze Kei

Immunity, inflammation and disease

2022 Volume 10, Issue 5, Page(s) e615

Abstract: Objectives: To compare the risk of five nonpulmonary infections leading to hospitalization between spondyloarthritis (SpA) and nonspecific back pain (NSBP), and to identify the risk factors.: Methods: A total of 3018 patients with SpA and 2527 ... ...

Abstract	Objectives: To compare the risk of five nonpulmonary infections leading to hospitalization between spondyloarthritis (SpA) and nonspecific back pain (NSBP), and to identify the risk factors. Methods: A total of 3018 patients with SpA and 2527 patients with NSBP were identified. Data from December 1995 to June 2019 was retrieved from a centralized electronic medical record system. The date of onset of five types of nonpulmonary infections including: urinary tract infection (UTI), skin infection, gastroenteritis (GE), septic arthritis, and pancreato-hepatobiliary tract infection were identified. Demographic data, comorbidities, and medications used were also retrieved. Comparative risk of each type of infection between SpA and NSBP was determined using propensity score adjustment method. Cox regression model was used to identified risk factors. Results: Patients with SpA were younger in age, predominantly male, with fewer comorbid diabetes mellitus (DM), renal impairment, and depression. Compared with NSBP, patients with SpA had higher risk of UTI (hazard ratio [HR] 1.91; p < .001), skin infection (HR 1.79; p < .001), and septic arthritis (HR 4.57; p = .04). Risk of GE (HR 1.42; p = 1.00), and pancreato-hepatobiliary tract infection (HR 1.67; p = .06) were not increased. Infliximab was an independent risk factor for UTI (HR 2.21; p = .04). Duration of steroid therapy >6 months (HR 2.22; p < .001), smoker (HR 1.81; p < .001), and psoriasis (HR 2.47; p < .001) were risk factors for skin infection. Conclusion: SpA was associated with increased risk of UTI, skin infection, and septic arthritis. Infliximab, prolonged steroid therapy, smoking, and psoriasis were associated risk factors.
MeSH term(s)	Arthritis, Infectious/epidemiology ; Female ; Hospitalization ; Humans ; Infliximab ; Male ; Psoriasis ; Spondylarthritis/drug therapy ; Spondylarthritis/epidemiology ; Steroids ; Urinary Tract Infections/epidemiology
Chemical Substances	Steroids ; Infliximab (B72HH48FLU)
Language	English
Publishing date	2022-04-27
Publishing country	England
Document type	Journal Article
ZDB-ID	2740382-8
ISSN	2050-4527 ; 2050-4527
ISSN (online)	2050-4527
ISSN	2050-4527
DOI	10.1002/iid3.615
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Article ; Online: Comment on: Deep learning algorithms for magnetic resonance imaging of inflammatory sacroiliitis in axial spondyloarthritis: reply.

Lin, Karina Ying Ying / Cao, Peng / Lee, Kam Ho / Chan, Shirley Chiu Wai / Chung, Ho Yin

Rheumatology (Oxford, England)

2022 Volume 61, Issue 10, Page(s) e318–e319

MeSH term(s)	Algorithms ; Axial Spondyloarthritis ; Deep Learning ; Humans ; Magnetic Resonance Imaging/methods ; Sacroiliac Joint/diagnostic imaging ; Sacroiliac Joint/pathology ; Sacroiliitis/diagnostic imaging ; Sacroiliitis/pathology ; Spondylarthritis/complications ; Spondylarthritis/diagnostic imaging ; Spondylarthritis/pathology
Language	English
Publishing date	2022-04-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	1464822-2
ISSN	1462-0332 ; 1462-0324
ISSN (online)	1462-0332
ISSN	1462-0324
DOI	10.1093/rheumatology/keac216
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Zs.B 240: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG)
Zs.MO 497: Show issues

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Article ; Online: Deep learning algorithms for magnetic resonance imaging of inflammatory sacroiliitis in axial spondyloarthritis.

Lin, Karina Ying Ying / Peng, Cao / Lee, Kam Ho / Chan, Shirley Chiu Wai / Chung, Ho Yin

Rheumatology (Oxford, England)

2022 Volume 61, Issue 10, Page(s) 4198–4206

Abstract: Objective: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI.: Methods: A total of 326 participants with axial SpA, and 63 participants ...

Abstract	Objective: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI. Methods: A total of 326 participants with axial SpA, and 63 participants with non-specific back pain (NSBP) were recruited. STIR MRI of the SI joints was performed and clinical data were collected. Region of interests (ROIs) were drawn outlining bone marrow oedema, a reliable marker of active inflammation, which formed the ground truth masks from which 'fake-colour' images were derived. Both the original and fake-colour images were randomly allocated into either the training and validation dataset or the testing dataset. Attention U-net was used for the development of deep learning algorithms. As a comparison, an independent radiologist and rheumatologist, blinded to the ground truth masks, were tasked with identifying bone marrow oedema in the MRI scans. Results: Inflammatory sacroiliitis was identified in 1398 MR images from 228 participants. No inflammation was found in 3944 MRI scans from 161 participants. The mean sensitivity of the algorithms derived from the original dataset and fake-colour image dataset were 0.86 (0.02) and 0.90 (0.01), respectively. The mean specificity of the algorithms derived from the original and the fake-colour image datasets were 0.92 (0.02) and 0.93 (0.01), respectively. The mean testing dice coefficients were 0.48 (0.27) for the original dataset and 0.51 (0.25) for the fake-colour image dataset. The area under the curve of the receiver operating characteristic (AUC-ROC) curve of the algorithms using the original dataset and the fake-colour image dataset were 0.92 and 0.96, respectively. The sensitivity and specificity of the algorithms were comparable with the interpretation by a radiologist, but outperformed that of the rheumatologist. Conclusion: An MRI deep learning algorithm was developed for detection of inflammatory sacroiliitis in axial SpA.
MeSH term(s)	Algorithms ; Axial Spondyloarthritis ; Bone Marrow Diseases/pathology ; Deep Learning ; Edema/diagnostic imaging ; Edema/pathology ; Humans ; Magnetic Resonance Imaging/methods ; Sacroiliac Joint/diagnostic imaging ; Sacroiliac Joint/pathology ; Sacroiliitis/diagnosis ; Spondylarthritis/complications ; Spondylarthritis/diagnostic imaging ; Spondylarthritis/pathology
Language	English
Publishing date	2022-02-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1464822-2
ISSN	1462-0332 ; 1462-0324
ISSN (online)	1462-0332
ISSN	1462-0324
DOI	10.1093/rheumatology/keac059
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Zs.MO 497: Show issues

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Article ; Online: Epidemiology, mortality and effectiveness of prophylaxis for Pneumocystis jiroveci pneumonia among rheumatic patients: a territory-wide study.

Chan, Shirley Chiu Wai / Chung, Ho Yin / Lau, Chak Sing / Li, Philip Hei

Annals of clinical microbiology and antimicrobials

2021 Volume 20, Issue 1, Page(s) 78

Abstract: Background: Pneumocystis jiroveci pneumonia (PJP) is an opportunistic infection affecting immunocompromised individuals. However, evidence regarding the burden and effectiveness of prophylaxis among rheumatic patients remains limited. Delineating the ... ...

Abstract	Background: Pneumocystis jiroveci pneumonia (PJP) is an opportunistic infection affecting immunocompromised individuals. However, evidence regarding the burden and effectiveness of prophylaxis among rheumatic patients remains limited. Delineating the epidemiology and efficacy of prophylaxis among rheumatic patients is urgently needed. Methods: We performed a territory-wide cohort study of rheumatic patients in Hong Kong. All patients with a diagnosis of anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV), immune-mediated myositis (IMM), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), or spondyloarthritis (SpA) between 2015 and 2019 were included. Prevalence, frequency of prophylaxis and mortality of PJP were calculated. Number needed to treat (NNT) analysis was also performed. Results: Out of 21,587 patients (54% RA, 25% SLE, 13% SpA, 5% IMM, 2% AAV and 1% SSc), 1141 (5.3%) patients were prescribed PJP prophylaxis. 48/21,587 (0.2%) developed PJP. No patients who developed PJP received prophylaxis prior to infection. The incidence of PJP was highest among SSc, AAV, and IMM patients. Among these diseases, the majority of PJP occurred while patients were on glucocorticoids at daily prednisolone-equivalent doses of 15 mg/day (P15) or above. PJP prophylaxis was effective with NNT for SSc, AAV and IIM being 36, 48 and 114 respectively. There were 19 PJP-related mortalities and the mortality rate was 39.6%. Conclusion: PJP is an uncommon but important infection among rheumatic patients, PJP prophylaxis is effective and should be considered in patients with SSc, AAV and IMM, especially those receiving glucocorticoid doses above P15.
MeSH term(s)	Aged ; Cohort Studies ; Female ; Glucocorticoids/administration & dosage ; Glucocorticoids/therapeutic use ; Humans ; Immunocompromised Host ; Incidence ; Longitudinal Studies ; Male ; Middle Aged ; Opportunistic Infections/complications ; Opportunistic Infections/immunology ; Pneumocystis carinii/drug effects ; Pneumocystis carinii/isolation & purification ; Pneumonia, Pneumocystis/diagnosis ; Pneumonia, Pneumocystis/mortality ; Pneumonia, Pneumocystis/prevention & control ; Rheumatic Diseases/complications ; Rheumatic Diseases/epidemiology
Chemical Substances	Glucocorticoids
Language	English
Publishing date	2021-11-11
Publishing country	England
Document type	Journal Article ; Observational Study
ZDB-ID	2097873-X
ISSN	1476-0711 ; 1476-0711
ISSN (online)	1476-0711
ISSN	1476-0711
DOI	10.1186/s12941-021-00483-2
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Article: Malignancies in spondyloarthritis with and without concomitant psoriasis, and the effect of disease modifying anti-rheumatic drugs.

Chung, Ho Yin / Chan, Shirley Chiu Wai / Chui, Eva Tsz Fung / Yau, Thomas / Lau, Chak Sing

Clinical and experimental rheumatology

2021 Volume 40, Issue 5, Page(s) 913–920

Abstract: Objectives: To determine the risk of 6 types of malignancies in spondyloarthritis (SpA) with and without psoriasis (PsO) and on disease-modifying anti-rheumatic drugs (DMARDs), compared to non-specific back pain (NSBP).: Methods: Medical records were ...

Abstract	Objectives: To determine the risk of 6 types of malignancies in spondyloarthritis (SpA) with and without psoriasis (PsO) and on disease-modifying anti-rheumatic drugs (DMARDs), compared to non-specific back pain (NSBP). Methods: Medical records were retrieved. Patients with SpA with and without PsO were identified and compared to those with NSBP. Clinical data; follow-up duration; comorbidities; dates and types of cancer diagnosed; types and duration of DMARD therapy were collected. Propensity score adjustment was used to compare the risks of malignancies between SpA, SpA with and without PsO, and NSBP. Cox regression analysis was used to determine the risk of malignancy in DMARD therapy. Results: A total of 3020 patients with SpA and 2527 patients with NSBP were studied. The mean follow-up duration in patients with SpA and NSBP was 9.6 years and 13.5 years respectively. Incidence and risk of malignancies were compatible between SpA and NSBP. The incidences of various carcinomas (per 1000 patient-years) in SpA were: 1.37 for colorectal carcinoma; 0.30 for carcinoma of pancreas; 0.30 for carcinoma of stomach; and 0.91 for lymphomas. Risk of colorectal carcinoma (HR 2.46; p=0.03) and lymphomas (HR 2.86; p=0.04) was increased in SpA with concomitant PsO. DMARD therapy was not associated with increased risks of malignancies after adjustment for confounding factors. Conclusions: Risk of malignancy was increased in SpA with PsO but not in other subtypes of SpA or DMARD therapy.
MeSH term(s)	Antirheumatic Agents/adverse effects ; Back Pain ; Carcinoma/drug therapy ; Colorectal Neoplasms/drug therapy ; Humans ; Psoriasis/complications ; Psoriasis/drug therapy ; Psoriasis/epidemiology ; Spondylarthritis/complications ; Spondylarthritis/drug therapy ; Spondylarthritis/epidemiology
Chemical Substances	Antirheumatic Agents
Language	English
Publishing date	2021-07-24
Publishing country	Italy
Document type	Journal Article
ZDB-ID	605886-3
ISSN	1593-098X ; 0392-856X
ISSN (online)	1593-098X
ISSN	0392-856X
DOI	10.55563/clinexprheumatol/o3rgv1
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Article ; Online: Clinical, radiological, and magnetic resonance imaging characteristics of axial spondyloarthritis with late onset.

Chung, Ho Yin / Huang, Jin Xian / Chan, Shirley Chiu Wai / Lee, Kam Ho / Tsang, Helen Hoi Lun / Lau, Chak Sing

Medicine

2022 Volume 101, Issue 29, Page(s) e29523

Abstract: We aimed to investigate the clinical, diagnostic, and imaging features of patients with late onset axial spondyloarthritis (SpA) with initial symptom manifestation aged over 45 years. Participants with axial SpA were consecutively recruited. Clinical, ... ...

Abstract	We aimed to investigate the clinical, diagnostic, and imaging features of patients with late onset axial spondyloarthritis (SpA) with initial symptom manifestation aged over 45 years. Participants with axial SpA were consecutively recruited. Clinical, demographic, blood, and imaging parameters were compared between the groups with early (≤45 years) and late onset (>45 years) at a cross-sectional level. Logistic regressions were used to determine the independent associations with axial SpA with late onset. A total of 455 participants were recruited. Among them, 70 (15.4%) had late onset disease. Multivariate analyses showed that axial SpA with late onset was associated with higher C-reactive protein based ankylosing spondylitis disease activity index (ASDAS-CRP) (B = 0.10; P = .04), higher intensity of spinal inflammation as measured by maximum apparent diffusion coefficient (spinal ADC max) (B = 0.27; P = .03) and mean ADC (spinal ADC mean) (B = 0.30; P = .004), lower modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) (B = -0.12; P = .02), more tender joint count (B = 0.12; P = .02), and fewer inflammatory back pain (IBP) (OR = 0.26; P < .001). Axial SpA with late onset had higher clinical disease activity, higher intensity of spinal MRI inflammation, less radiographic damage, and more tender joint count. There was also less inflammatory back pain, which could make the diagnosis more difficult.
MeSH term(s)	Aged ; Axial Spondyloarthritis ; Back Pain/diagnostic imaging ; Back Pain/etiology ; C-Reactive Protein/analysis ; Cross-Sectional Studies ; Humans ; Inflammation/complications ; Magnetic Resonance Imaging/methods ; Severity of Illness Index ; Spondylarthritis/complications ; Spondylitis, Ankylosing/diagnosis
Chemical Substances	C-Reactive Protein (9007-41-4)
Language	English
Publishing date	2022-07-22
Publishing country	United States
Document type	Journal Article
ZDB-ID	80184-7
ISSN	1536-5964 ; 0025-7974
ISSN (online)	1536-5964
ISSN	0025-7974
DOI	10.1097/MD.0000000000029523
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