Browsing by Author "Milic, Vera (24281704100)"

Objectives: Identifying genetic predictors of methotrexate (MTX) treatment response in patients with rheumatoid arthritis (RA) may have great importance for optimising drug doses required for clinical benefit without toxicity. In a group of 125 RA patients treated with MTX we investigated whether selected polymorphisms in genes relevant for MTX action (aminoimidazole-4-carboxiamide ribonucleotide transformylase, ATIC, and dihydrofolate reductase, DHFR) modulate disease activity and/or have impact on therapy side effects. Methods: The efficacy of treatment was estimated both by the disease activity score in 28 joints (DAS28), based on EULAR criteria, and relative DAS28 (rDAS28) score. Adverse drug events (ADEs) were also recorded. RA patients were genotyped using the PCR-RFLP method, followed by an association study between ATIC -129T>G, DHFR -216T>C and DHFR -317A>G polymorphisms and the efficacy and toxicity of MTX. Results: According to the EULAR response criteria, 96 RA patients (76.8%) were classified as responders (good/moderate response) and 29 (23.2%) as non-responders (poor response). rDAS28 values ranged from -0.01 to 0.80 (mean value 0.31±0.19). Among 125 patients enrolled in this study 39 experienced at least one side effect. The DHFR -317AA genotype was associated with the less favourable response (reduction in rDAS28 score, p=0.05). None of the analysed polymorphisms was associated with MTX toxicity. Conclusion: RA patients with DHFR-317AA genotype had less favourable response to MTX Further studies in larger patient populations are necessary to confirm the relationship between the analysed polymorphisms and MTX treatment response. © Clinical and Experimental Rheumatology 2012.

Objectives: Identifying genetic predictors of methotrexate (MTX) treatment response in patients with rheumatoid arthritis (RA) may have great importance for optimising drug doses required for clinical benefit without toxicity. In a group of 125 RA patients treated with MTX we investigated whether selected polymorphisms in genes relevant for MTX action (aminoimidazole-4-carboxiamide ribonucleotide transformylase, ATIC, and dihydrofolate reductase, DHFR) modulate disease activity and/or have impact on therapy side effects. Methods: The efficacy of treatment was estimated both by the disease activity score in 28 joints (DAS28), based on EULAR criteria, and relative DAS28 (rDAS28) score. Adverse drug events (ADEs) were also recorded. RA patients were genotyped using the PCR-RFLP method, followed by an association study between ATIC -129T>G, DHFR -216T>C and DHFR -317A>G polymorphisms and the efficacy and toxicity of MTX. Results: According to the EULAR response criteria, 96 RA patients (76.8%) were classified as responders (good/moderate response) and 29 (23.2%) as non-responders (poor response). rDAS28 values ranged from -0.01 to 0.80 (mean value 0.31±0.19). Among 125 patients enrolled in this study 39 experienced at least one side effect. The DHFR -317AA genotype was associated with the less favourable response (reduction in rDAS28 score, p=0.05). None of the analysed polymorphisms was associated with MTX toxicity. Conclusion: RA patients with DHFR-317AA genotype had less favourable response to MTX Further studies in larger patient populations are necessary to confirm the relationship between the analysed polymorphisms and MTX treatment response. © Clinical and Experimental Rheumatology 2012.

Purpose: Gamma-glutamyl hydrolase (GGH), cyclin D1 (CCND1) and thymidylate synthase (TS) genes encode enzymes that are involved in methotrexate (MTX) action. In a group of 184 RA patients treated with MTX, we have investigated whether selected polymorphisms in these genes modulate MTX efficacy and/or have impact on adverse drug effects (ADEs). Methods: The efficacy of the MTX therapy has been estimated using the disease activity score in 28 joints (DAS28-ESR) based on EULAR criteria and relative DAS28 values (rDAS28). All adverse drug events were recorded. Patients were genotyped for selected polymorphisms of the GGH (-354 G > T and 452 C > T), CCND1 (870 A > G) and TYMS (variable number of tandem repeats, VNTR, and G to C substitution of triple repeat, 3R allele) gene. Association studies have been performed between obtained genotypes and the efficacy and toxicity of MTX. Results: According to the EULAR response criteria, 146 RA patients (79.3 %) were classified as responders (good/moderate response) and 38 (20.7 %) as non-responders (poor response). Higher frequency of the TYMS 3 G/3 G genotype has been found among non-responders as compared to individuals with remaining genotypes (p = 0.02). ADEs were recorded in 53 patients. Among those patients eight experienced bone marrow toxicity, all of them carried GGH -354GG genotype (p = 0.003). No other significant association were observed. Conclusion: The 3 G/3 G genotype of the TYMS gene may indicate predisposition of poor response to MTX and GG genotype of GGH -354 T > G polymorphism may have high predictive value for myelosuppression in RA patients. © 2012 Springer-Verlag.

Purpose: Gamma-glutamyl hydrolase (GGH), cyclin D1 (CCND1) and thymidylate synthase (TS) genes encode enzymes that are involved in methotrexate (MTX) action. In a group of 184 RA patients treated with MTX, we have investigated whether selected polymorphisms in these genes modulate MTX efficacy and/or have impact on adverse drug effects (ADEs). Methods: The efficacy of the MTX therapy has been estimated using the disease activity score in 28 joints (DAS28-ESR) based on EULAR criteria and relative DAS28 values (rDAS28). All adverse drug events were recorded. Patients were genotyped for selected polymorphisms of the GGH (-354 G > T and 452 C > T), CCND1 (870 A > G) and TYMS (variable number of tandem repeats, VNTR, and G to C substitution of triple repeat, 3R allele) gene. Association studies have been performed between obtained genotypes and the efficacy and toxicity of MTX. Results: According to the EULAR response criteria, 146 RA patients (79.3 %) were classified as responders (good/moderate response) and 38 (20.7 %) as non-responders (poor response). Higher frequency of the TYMS 3 G/3 G genotype has been found among non-responders as compared to individuals with remaining genotypes (p = 0.02). ADEs were recorded in 53 patients. Among those patients eight experienced bone marrow toxicity, all of them carried GGH -354GG genotype (p = 0.003). No other significant association were observed. Conclusion: The 3 G/3 G genotype of the TYMS gene may indicate predisposition of poor response to MTX and GG genotype of GGH -354 T > G polymorphism may have high predictive value for myelosuppression in RA patients. © 2012 Springer-Verlag.

Salivary gland ultrasonography (SGUS) has proven to be a promising tool for diagnosing various diseases manifesting with abnormalities in salivary glands (SGs), including primary Sjögren's syndrome (pSS). At present, the major obstacle for establishing SUGS as a standardized tool for pSS diagnosis is its low inter/intra observer reliability. The aim of this study was to address this problem by proposing a robust deep learning-based solution for the automated segmentation of SGUS images. For these purposes, four architectures were considered: a fully convolutional neural network, fully convolutional “DenseNets” (FCN-DenseNet) network, U-Net, and LinkNet. During the course of the study, the growing HarmonicSS cohort included 1184 annotated SGUS images. Accordingly, the algorithms were trained using a transfer learning approach. With regard to the intersection-over-union (IoU), the top-performing FCN-DenseNet (IoU = 0.85) network showed a considerable margin above the inter-observer agreement (IoU = 0.76) and slightly above the intra-observer agreement (IoU = 0.84) between clinical experts. Considering its accuracy and speed (24.5 frames per second), it was concluded that the FCN-DenseNet could have wider applications in clinical practice. Further work on the topic will consider the integration of methods for pSS scoring, with the end goal of establishing SGUS as an effective noninvasive pSS diagnostic tool. To aid this progress, we created inference (frozen models) files for the developed models, and made them publicly available. © 2020 Elsevier Ltd

Salivary gland ultrasonography (SGUS) has proven to be a promising tool for diagnosing various diseases manifesting with abnormalities in salivary glands (SGs), including primary Sjögren's syndrome (pSS). At present, the major obstacle for establishing SUGS as a standardized tool for pSS diagnosis is its low inter/intra observer reliability. The aim of this study was to address this problem by proposing a robust deep learning-based solution for the automated segmentation of SGUS images. For these purposes, four architectures were considered: a fully convolutional neural network, fully convolutional “DenseNets” (FCN-DenseNet) network, U-Net, and LinkNet. During the course of the study, the growing HarmonicSS cohort included 1184 annotated SGUS images. Accordingly, the algorithms were trained using a transfer learning approach. With regard to the intersection-over-union (IoU), the top-performing FCN-DenseNet (IoU = 0.85) network showed a considerable margin above the inter-observer agreement (IoU = 0.76) and slightly above the intra-observer agreement (IoU = 0.84) between clinical experts. Considering its accuracy and speed (24.5 frames per second), it was concluded that the FCN-DenseNet could have wider applications in clinical practice. Further work on the topic will consider the integration of methods for pSS scoring, with the end goal of establishing SGUS as an effective noninvasive pSS diagnostic tool. To aid this progress, we created inference (frozen models) files for the developed models, and made them publicly available. © 2020 Elsevier Ltd

Objective. Ultrasonography (US) is a sensitive tool in the diagnosis of major salivary gland abnormalities in primary Sjögren's syndrome (pSS). The aim of this systematic review was to assess the metric properties of this technique. Methods. PUBMED and EMBASE databases were searched. All publications between January 1988 and January 2013 were considered. Data were extracted from the articles meeting the inclusion criteria according to US definition of salivary gland scoring system and metric properties studied. The type and number of glands tested, study design and metric properties according to OMERACT filter (truth, discrimination, feasibility) were assessed. Results. Of 167 publications identified initially with PUBMED and EMBASE, 31 met the inclusion criteria. The number of pSS patients varied among the studies from 16 to 140. The diagnosis of pSS was in line in most of the cases with the American-European Consensus Group (AECG) classification criteria for Sjögren's syndrome. The US examination was performed in suspected pSS only in studies in which the sensitivity ranged from 45.8 to 91.6% and specificity from 73 to 98.1%. There was heterogeneity in regard to the definition of US in B-mode and few studies used US in colour Doppler. Few studies reported reliability of US and sensitivity to change in pSS. Conclusion. US is a valuable tool for detecting salivary gland abnormalities in pSS. Its reliability has been poorly investigated and there is considerable variation in the definition of US abnormalities. Further studies are required to validate and standardize the US definition of salivary gland in pSS. © The Author 2015.

Salivary gland ultrasonography (SGUS) has shown good potential in the diagnosis of primary Sjögren's syndrome (pSS). However, a series of international studies have reported needs for improvements of the existing pSS scoring procedures in terms of inter/intra observer reliability before being established as standardized diagnostic tools. The present study aims to solve this problem by employing radiomics features and artificial intelligence (AI) algorithms to make the pSS scoring more objective and faster compared to human expert scoring. The assessment of AI algorithms was performed on a two-centric cohort, which included 600 SGUS images (150 patients) annotated using the original SGUS scoring system proposed in 1992 for pSS. For each image, we extracted 907 histogram-based and descriptive statistics features from segmented salivary glands. Optimal feature subsets were found using the genetic algorithm based wrapper approach. Among the considered algorithms (seven classifiers and five regressors), the best preforming was the multilayer perceptron (MLP) classifier (κ = 0.7). The MLP over-performed average score achieved by the clinicians (κ = 0.67) by the considerable margin, whereas its reliability was on the level of human intra-observer variability (κ = 0.71). The presented findings indicate that the continuously increasing HarmonicSS cohort will enable further advancements in AI-based pSS scoring methods by SGUS. In turn, this may establish SGUS as an effective noninvasive pSS diagnostic tool, with the final goal to supplement current diagnostic tests. © 2013 IEEE.

Salivary gland ultrasonography (SGUS) has shown good potential in the diagnosis of primary Sjögren's syndrome (pSS). However, a series of international studies have reported needs for improvements of the existing pSS scoring procedures in terms of inter/intra observer reliability before being established as standardized diagnostic tools. The present study aims to solve this problem by employing radiomics features and artificial intelligence (AI) algorithms to make the pSS scoring more objective and faster compared to human expert scoring. The assessment of AI algorithms was performed on a two-centric cohort, which included 600 SGUS images (150 patients) annotated using the original SGUS scoring system proposed in 1992 for pSS. For each image, we extracted 907 histogram-based and descriptive statistics features from segmented salivary glands. Optimal feature subsets were found using the genetic algorithm based wrapper approach. Among the considered algorithms (seven classifiers and five regressors), the best preforming was the multilayer perceptron (MLP) classifier (κ = 0.7). The MLP over-performed average score achieved by the clinicians (κ = 0.67) by the considerable margin, whereas its reliability was on the level of human intra-observer variability (κ = 0.71). The presented findings indicate that the continuously increasing HarmonicSS cohort will enable further advancements in AI-based pSS scoring methods by SGUS. In turn, this may establish SGUS as an effective noninvasive pSS diagnostic tool, with the final goal to supplement current diagnostic tests. © 2013 IEEE.

Introduction: Major salivary gland ultrasonography (SGUS) demonstrated its good metric properties as an outcome measure for diagnosing primary Sjögren’s disease (SD). The objective was to assess SGUS reliability among sonographers with different levels of experience, using web training. Methods: Sonographers from expert centers participated in the reliability exercise. Before exercises, training was done by videoconferencing. Reliability of the two most experienced sonographers (MES) was assessed and then compared to other sonographers. Intra-reader and inter-reader reliability of SGUS items were assessed by computing Cohen’s κ coefficients. Results: All sets were read twice by all 14 sonographers within a 4-month interval. Intra-reader reliability of MES was almost perfect for homogeneity, substantial for Outcome Measures in Rheumatology (OMERACT) scoring system (OMERACTss). Among LES (less experienced sonographers), reliability was moderate to almost perfect for homogeneity, fair to moderate for OMERACTss, and fair to almost perfect for binary OMERACTss. Inter-reader reliability between MES was almost perfect for homogeneity, substantial for diagnosis, moderate for OMERACTss, and substantial for binary OMERACTss. Compared to MES, reliabilities of LES were moderate to almost perfect for both homogeneity and diagnosis, only fair to moderate for OMERACTss, but increased in binary OMERACTss. Conclusions: Videoconferencing training sessions in an international reliability exercise could be an excellent tool to train experienced and less-experienced sonographers. SGUS homogeneity items is useful to distinguish normal from abnormal salivary glands parenchyma independently of diagnosis. Structural damage evaluations by OMERACT scoring system is a new comprehensive score to diagnose patients with SD and could be easily used by sonographers in a binary method. © The Author(s) 2024.

Objectives Ultrasonography (US) is sensitive for detecting echostructural abnormalities of the major salivary glands (SGs) in primary Sjögren's syndrome (pSS). Our objectives were to define selected US-SG echostructural abnormalities in pSS, set up a preliminary atlas of these definitions and evaluate the consensual definitions reliability in both static and acquisition US-SG images. Methods International experts in SG US in pSS participated in consensus meetings to select and define echostructural abnormalities in pSS. The US reliability of detecting these abnormalities was assessed using a two-step method. First 12 experts used a web-based standardised form to evaluate 60 static US-SG images. Intra observer and interobserver reliabilities were expressed in κ values. Second, five experts, who participated all throughout the study, evaluated US-SG acquisition interobserver reliability in pSS patients. Results Parotid glands (PGs) and submandibular glands (SMGs) intra observer US reliability on static images was substantial (κ > 0.60) for the two main reliable items (echogenicity and homogeneity) and for the advised pSS diagnosis. PG inter observer reliability was substantial for homogeneity. SMGs interobserver reliability was moderate for homogeneity (κ = 0.46) and fair for echogenicity (κ = 0.38). On acquisition images, PGs interobserver reliability was substantial (κ > 0.62) for echogenicity and moderate (κ = 0.52) for homogeneity. The advised pSS diagnosis reliability was substantial (κ = 0.66). SMGs interobserver reliability was fair (0.20< κ ≤ 0.40) for echogenicity and homogeneity and either slight or poor for all other US core items. Conclusion This work identified two most reliable US-SG items (echogenicity and homogeneity) to be used by US-SG trained experts. US-PG interobserver reliability result for echogenicity is in line with diagnosis of pSS. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Objectives Ultrasonography (US) is sensitive for detecting echostructural abnormalities of the major salivary glands (SGs) in primary Sjögren's syndrome (pSS). Our objectives were to define selected US-SG echostructural abnormalities in pSS, set up a preliminary atlas of these definitions and evaluate the consensual definitions reliability in both static and acquisition US-SG images. Methods International experts in SG US in pSS participated in consensus meetings to select and define echostructural abnormalities in pSS. The US reliability of detecting these abnormalities was assessed using a two-step method. First 12 experts used a web-based standardised form to evaluate 60 static US-SG images. Intra observer and interobserver reliabilities were expressed in κ values. Second, five experts, who participated all throughout the study, evaluated US-SG acquisition interobserver reliability in pSS patients. Results Parotid glands (PGs) and submandibular glands (SMGs) intra observer US reliability on static images was substantial (κ > 0.60) for the two main reliable items (echogenicity and homogeneity) and for the advised pSS diagnosis. PG inter observer reliability was substantial for homogeneity. SMGs interobserver reliability was moderate for homogeneity (κ = 0.46) and fair for echogenicity (κ = 0.38). On acquisition images, PGs interobserver reliability was substantial (κ > 0.62) for echogenicity and moderate (κ = 0.52) for homogeneity. The advised pSS diagnosis reliability was substantial (κ = 0.66). SMGs interobserver reliability was fair (0.20< κ ≤ 0.40) for echogenicity and homogeneity and either slight or poor for all other US core items. Conclusion This work identified two most reliable US-SG items (echogenicity and homogeneity) to be used by US-SG trained experts. US-PG interobserver reliability result for echogenicity is in line with diagnosis of pSS. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Objective: To test the diagnostic accuracy of modified American-European classification criteria (AEC) for primary SS (pSS) by replacing sialoscintigraphy (sSC) with ultrasonography of the major salivary glands. Methods: One hundred and ninety subjects were evaluated for the diagnosis of pSS, including US of the salivary glands. We tested the diagnostic accuracy of the three different sets of five diagnostic criteria for pSS. Each set combined these four criteria (ocular symptoms, oral symptoms, Schirmer-I test and auto-SS-A antibody) and one of the following: US (US set), sSC (sSC set) or biopsy (Biopsy set). The area under the receiver operating characteristics curve (AUC-ROC) was used to evaluate the diagnostic accuracy of each set of criteria. Results: Out of 190 subjects examined, 140 subjects fulfilled the AEC for the diagnosis of pSS, whereas 50 subjects were classified as non-pSS subjects. US score was positive in 129 (92%), sSC in 123 (88%) and biopsy in 93 (66%) of 140 pSS patients. Among 140 patients with pSS, 88 (63%) patients fulfilled the criteria of the US set, 85 (61%) patients of the sSC set and 71 (51%) patients of the Biopsy set. None of the subjects from the non-pSS group fulfilled any of the sets of criteria. Diagnostic accuracy of each of the three sets of criteria was high and similar [AUC-ROC (S.E.) for the US set was 0.99 (0.00), followed by the sSC set at 0.98 (0.00) and the Biopsy set at 0.97 (0.00)]. Conclusion: US finding of major salivary gland involvement could replace sSC in AEC for the diagnosis of pSS. © The Author 2012. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved.