{"title":"Early detection of tuberculosis using hybrid feature descriptors and deep learning network.","authors":"Garima Verma, Ajay Kumar, Sushil Dixit","doi":"10.5114/pjr.2023.131732","DOIUrl":"10.5114/pjr.2023.131732","url":null,"abstract":"<p><strong>Purpose: </strong>To detect tuberculosis (TB) at an early stage by analyzing chest X-ray images using a deep neural network, and to evaluate the efficacy of proposed model by comparing it with existing studies.</p><p><strong>Material and methods: </strong>For the study, an open-source X-ray images were used. Dataset consisted of two types of images, i.e., standard and tuberculosis. Total number of images in the dataset was 4,200, among which, 3,500 were normal chest X-rays, and the remaining 700 X-ray images were of tuberculosis patients. The study proposed and simulated a deep learning prediction model for early TB diagnosis by combining deep features with hand-engineered features. Gabor filter and Canny edge detection method were applied to enhance the performance and reduce computation cost.</p><p><strong>Results: </strong>The proposed model simulated two scenarios: without filter and edge detection techniques and only a pre-trained model with automatic feature extraction, and filter and edge detection techniques. The results achieved from both the models were 95.7% and 97.9%, respectively.</p><p><strong>Conclusions: </strong>The proposed study can assist in the detection if a radiologist is not available. Also, the model was tested with real-time images to examine the efficacy, and was better than other available models.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e445-e454"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9b/50/PJR-88-51566.PMC10551735.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41177728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"3D computed tomography intravascular endoscopy.","authors":"Haris Huseinagić, Alma Efendić, Irma Rušidović","doi":"10.5114/pjr.2023.131000","DOIUrl":"10.5114/pjr.2023.131000","url":null,"abstract":"<p><p>Using coronary computed tomography angiography (CCTA), coronary plaques can be characterized based on both their morphology and composition. Coronary plaques are generally assessed on 2D axial and multiplanar reformatted images. Nevertheless, these visualization tools are limited to observing extraluminal changes in the coronary artery. The presence of plaques prevents them from providing a visual representation of the intraluminal coronary wall. Since its invention in 2000, coronary fly-through or virtual angioscopy (VA) has been extensively studied. However, its application was limited because it required an optimal CT scan and time-consuming post-processing. In recent years, advances in post-processing software have made construction of VA easier, but until recently the quality of the images was insufficient for most patients. Using 3D intravascular endoscopy (3DIE) visualization, we present various intraluminal appearances of the coronary wall and plaque in relation to various types of plaque.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e435-e444"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/86/c7/PJR-88-51351.PMC10551738.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41177714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jakub Kufel, Iga Paszkiewicz, Michał Bielówka, Wiktoria Bartnikowska, Michał Janik, Magdalena Stencel, Łukasz Czogalik, Katarzyna Gruszczyńska, Sylwia Mielcarska
{"title":"Will ChatGPT pass the Polish specialty exam in radiology and diagnostic imaging? Insights into strengths and limitations.","authors":"Jakub Kufel, Iga Paszkiewicz, Michał Bielówka, Wiktoria Bartnikowska, Michał Janik, Magdalena Stencel, Łukasz Czogalik, Katarzyna Gruszczyńska, Sylwia Mielcarska","doi":"10.5114/pjr.2023.131215","DOIUrl":"10.5114/pjr.2023.131215","url":null,"abstract":"<p><strong>Purpose: </strong>Rapid development of artificial intelligence has aroused curiosity regarding its potential applications in medical field. The purpose of this article was to present the performance of ChatGPT, a state-of-the-art language model in relation to pass rate of national specialty examination (PES) in radiology and imaging diagnostics within Polish education system. Additionally, the study aimed to identify the strengths and limitations of the model through a detailed analysis of issues raised by exam questions.</p><p><strong>Material and methods: </strong>The present study utilized a PES exam consisting of 120 questions, provided by Medical Exami-nations Center in Lodz. Questions were administered using openai.com platform that grants free access to GPT-3.5 model. All questions were categorized according to Bloom's taxonomy to assess their complexity and difficulty. Following the answer to each exam question, ChatGPT was asked to rate its confidence on a scale of 1 to 5 to evaluate the accuracy of its response.</p><p><strong>Results: </strong>ChatGPT did not reach the pass rate threshold of PES exam (52%); however, it was close in certain question categories. No significant differences were observed in the percentage of correct answers across question types and sub-types.</p><p><strong>Conclusions: </strong>The performance of the ChatGPT model in the pass rate of PES exam in radiology and imaging diagnostics in Poland is yet to be determined, which requires further research on improved versions of ChatGPT.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e430-e434"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/e4/61/PJR-88-51387.PMC10551734.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41180809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jordan H Chamberlin, Carter D Smith, Zain Gowani, Mina Gad Elsayed, Shahin C Owji, Brandon Friedman, Dhruw Maisuria, Carly Berrios, Dhiraj Baruah, Uwe Joseph Schoepf, Ismail M Kabakus
{"title":"Left atrial calcification on chest CT: atrial ablation replaces rheumatic heart disease as the most identified etiology.","authors":"Jordan H Chamberlin, Carter D Smith, Zain Gowani, Mina Gad Elsayed, Shahin C Owji, Brandon Friedman, Dhruw Maisuria, Carly Berrios, Dhiraj Baruah, Uwe Joseph Schoepf, Ismail M Kabakus","doi":"10.5114/pjr.2023.131214","DOIUrl":"10.5114/pjr.2023.131214","url":null,"abstract":"<p><strong>Purpose: </strong>Left atrial calcification (LAC), a primarily radiologic diagnosis, has been associated with rheumatic heart disease (RHD) and rheumatic fever (RF). However, left atrial calcification continues to be observed despite a significant decrease in the prevalence of rheumatic heart disease. The purpose of this study was to investigate other possible etiologies of left atrial calcification.</p><p><strong>Material and methods: </strong>This retrospective, observational single-center study included patients from 2017 to 2022 identified as having left atrial calcification as well as age- and sex-matched controls. The prevalence of rheumatic heart disease, atrial ablation, and mitral valve disease was compared, and odds ratios were calculated for each independent variable.</p><p><strong>Results: </strong>Sixty-two patients with left atrial calcifications were included and compared with 62 controls. 87.1% of patients in the left atrial calcifications cohort had a history of atrial fibrillation compared with 21% in the control cohort (<i>p</i> < 0.001). 16.1% of patients in the calcifications cohort presented a history of rheumatic fever compared with zero in the control cohort (<i>p</i> = 0.004). 66.1% of the left atrial calcifications cohort had a history of atrial ablation compared with 6.5% of the control group (<i>p</i> < 0.001). The odds ratio for left atrial calcification was 19.0 vs. 4.8 for rheumatic fever (comparative odds = 4.0 for atrial ablation vs. rheumatic fever). Multivariable log model found atrial ablation to explain 79.8% of left atrial calcifications identified.</p><p><strong>Conclusions: </strong>Our study found a 4-fold higher association between history of atrial ablation and left atrial calcification compared with rheumatic heart disease, suggesting a potential shift in etiology.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e423-e429"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/cd/f9/PJR-88-51386.PMC10551739.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41180808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sylwia Grabowska, Anna Hitnarowicz, Anna Barczyk-Gutkowska, Katarzyna Gruszczyńska, Katarzyna Steinhof-Radwańska, Mateusz Winder
{"title":"Abbreviated magnetic resonance imaging protocols in oncology: improving accessibility in precise diagnostics.","authors":"Sylwia Grabowska, Anna Hitnarowicz, Anna Barczyk-Gutkowska, Katarzyna Gruszczyńska, Katarzyna Steinhof-Radwańska, Mateusz Winder","doi":"10.5114/pjr.2023.131213","DOIUrl":"10.5114/pjr.2023.131213","url":null,"abstract":"<p><p>Cancer, as the second leading cause of death in the world, is one of the major public health concerns today. Accurate diagnosis and prompt initiation of adequate treatment are of key importance for prognosis. Abbreviated magnetic resonance protocols (AMRI) are promising techniques based on magnetic resonance imaging (MRI) protocols that shorten acquisition time without significant loss of examination quality. Faster protocols that focus on detection of suspicious lesions with most precise sequences, can contribute to comparable diagnostic performance of a full MRI protocol. The purpose of this article was to review the current application of AMRI protocols in several oncological diseases.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e415-e422"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/5f/9a/PJR-88-51385.PMC10551741.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41176025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Computed tomography evaluation of variations in positions and measurements of appendix in patients with non-appendicular symptoms: time to revise the diagnostic criteria for appendicitis.","authors":"Neha Singh, Prasant Agrawal, Deepak Kumar Singh, Gaurav Raj Agrawal","doi":"10.5114/pjr.2023.131074","DOIUrl":"10.5114/pjr.2023.131074","url":null,"abstract":"<p><strong>Purpose: </strong>To estimate the frequency distribution of different anatomical positions, and to measure the diameter, wall thickness, and length of appendix in patients with non-appendicular symptoms.</p><p><strong>Material and methods: </strong>This retrospective observational study was conducted among 1,575 patients, who had undergone computed tomography (CT) scan of abdomen for various non-appendicular signs and symptoms. Frequency of distribution of different anatomic locations and measurements of various morphologic parameters were recorded.</p><p><strong>Results: </strong>The most common location of appendix was retrocecal, followed by sub-cecal, post-ileal, and pelvic locations. The mean length of appendix was 66.7 mm (range, 6.3-123 mm), and the diameter was 6.3 mm (range, 2.8-11.3 mm). Diameter of > 6 mm was noted in 48.12% patients. The mean wall thickness was 2.37 mm, ranging 1.2-4.2 mm. The most common intra-luminal content was air-mixed with hypodense or hyperdense material observed in 70.5% of cases.</p><p><strong>Conclusions: </strong>Although an appendix with diameter less than 6 mm may be considered normal, a diameter above 6 mm has an overlap between a normal and inflamed appendix. Therefore, it should be considered in association with clinical and secondary findings to avoid overdiagnosis and unnecessary appendicectomies. We strongly recommend that diameter-based CT criteria to diagnose appendicitis should be revised and standardized.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e407-e414"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/91/fe/PJR-88-51361.PMC10551737.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41180168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mustafa Orhan Nalbant, Irem Erdil, Nihal Akcay, Ercan Inci, Figen Palabiyik
{"title":"Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy.","authors":"Mustafa Orhan Nalbant, Irem Erdil, Nihal Akcay, Ercan Inci, Figen Palabiyik","doi":"10.5114/pjr.2023.131696","DOIUrl":"10.5114/pjr.2023.131696","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the whole brain, hippocampus, thalamus, and lentiform nucleus by volumetric apparent diffusion coefficient (ADC) histogram analysis in paediatric patients with hypoxic-ischaemic encephalopathy (HIE).</p><p><strong>Material and methods: </strong>This retrospective study included 25 patients with HIE and 50 patients as the control group. Diffusion-weighted imaging was obtained at <i>b</i>-values of 1000 mm<sup>2</sup>/s. The histogram parameters of ADC values, including the mean, minimum, maximum, 5<sup>th</sup>, 10<sup>th</sup>, 25<sup>th</sup>, 50<sup>th</sup>, 75<sup>th</sup>, 90<sup>th</sup>, and 95<sup>th</sup> percentiles, as well as skewness, kurtosis, and variance were determined. The interclass correlation coefficient (ICC) was used to assess the inter-observer agreement.</p><p><strong>Results: </strong>ADC<sub>min</sub>, ADC<sub>mean</sub>, and ADC<sub>max</sub>, as well as the 5<sup>th</sup>, 10<sup>th</sup>, 25<sup>th</sup>, 50<sup>th</sup>, 75<sup>th</sup>, 90<sup>th</sup>, and 95<sup>th</sup> percentiles of ADC values for the HIE group were all lower than those of the control group (<i>p</i> < 0.001) in the volumetric histogram analysis of the hippocampus, thalamus, and lentiform nucleus. In the whole-brain histogram analysis, ADC min, and the 50<sup>th</sup> and 75<sup>th</sup> percentiles of ADC values did not differ significantly, while other parameters were lower in the HIE group. The ROC curve revealed that the ADC histogram parameters of the hippocampus provided the most accurate results for the diagnosis of HIE. The area under the curve (AUC) of the 95<sup>th</sup> percentile of ADC values was the highest (AUC = 0.915; cut-off 1.262 × 10<sup>-3</sup> mm<sup>2</sup>/s; sensitivity 88% and specificity 84%).</p><p><strong>Conclusions: </strong>Volumetric ADC histogram analysis of the whole brain, hippocampus, thalamus, and lentiform nucleus with <i>b</i>-values of 1000 mm<sup>2</sup>/s can serve as an imaging marker for determining HIE.</p>","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"88 ","pages":"e399-e406"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/4d/b3/PJR-88-51550.PMC10551736.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41167786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis","authors":"Peyman Tabnak, Zanyar HajiEsmailPoor","doi":"10.5114/pjr.2023.132172","DOIUrl":"https://doi.org/10.5114/pjr.2023.132172","url":null,"abstract":"AMA Tabnak P, HajiEsmailPoor Z. Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis. Polish Journal of Radiology. 2023;88(1):472-482. doi:10.5114/pjr.2023.132172. APA Tabnak, P., & HajiEsmailPoor, Z. (2023). Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis. Polish Journal of Radiology, 88(1), 472-482. https://doi.org/10.5114/pjr.2023.132172 Chicago Tabnak, Peyman, and Zanyar HajiEsmailPoor. 2023. \"Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis\". Polish Journal of Radiology 88 (1): 472-482. doi:10.5114/pjr.2023.132172. Harvard Tabnak, P., and HajiEsmailPoor, Z. (2023). Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis. Polish Journal of Radiology, 88(1), pp.472-482. https://doi.org/10.5114/pjr.2023.132172 MLA Tabnak, Peyman et al. \"Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis.\" Polish Journal of Radiology, vol. 88, no. 1, 2023, pp. 472-482. doi:10.5114/pjr.2023.132172. Vancouver Tabnak P, HajiEsmailPoor Z. Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis. Polish Journal of Radiology. 2023;88(1):472-482. doi:10.5114/pjr.2023.132172.","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joanna Podgórska, Katarzyna Pasicz, Witold Skrzyński, Bogumił Gołębiewski, Piotr Kuś, Jakub Jasieniak, Agnieszka Rogowska, Paweł Kukołowicz, Andrzej Cieszanowski
{"title":"Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions","authors":"Joanna Podgórska, Katarzyna Pasicz, Witold Skrzyński, Bogumił Gołębiewski, Piotr Kuś, Jakub Jasieniak, Agnieszka Rogowska, Paweł Kukołowicz, Andrzej Cieszanowski","doi":"10.5114/pjr.2023.131911","DOIUrl":"https://doi.org/10.5114/pjr.2023.131911","url":null,"abstract":"AMA Podgórska J, Pasicz K, Skrzyński W, et al. Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions. Polish Journal of Radiology. 2023;88(1):455-460. doi:10.5114/pjr.2023.131911. APA Podgórska, J., Pasicz, K., Skrzyński, W., Gołębiewski, B., Kuś, P., & Jasieniak, J. et al. (2023). Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions. Polish Journal of Radiology, 88(1), 455-460. https://doi.org/10.5114/pjr.2023.131911 Chicago Podgórska, Joanna, Katarzyna Pasicz, Witold Skrzyński, Bogumił Gołębiewski, Piotr Kuś, Jakub Jasieniak, and Agnieszka Rogowska et al. 2023. \"Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions\". Polish Journal of Radiology 88 (1): 455-460. doi:10.5114/pjr.2023.131911. Harvard Podgórska, J., Pasicz, K., Skrzyński, W., Gołębiewski, B., Kuś, P., Jasieniak, J., Rogowska, A., Kukołowicz, P., and Cieszanowski, A. (2023). Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions. Polish Journal of Radiology, 88(1), pp.455-460. https://doi.org/10.5114/pjr.2023.131911 MLA Podgórska, Joanna et al. \"Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions.\" Polish Journal of Radiology, vol. 88, no. 1, 2023, pp. 455-460. doi:10.5114/pjr.2023.131911. Vancouver Podgórska J, Pasicz K, Skrzyński W, Gołębiewski B, Kuś P, Jasieniak J et al. Application of diffusion kurtosis imaging in differential diagnosis of focal liver lesions. Polish Journal of Radiology. 2023;88(1):455-460. doi:10.5114/pjr.2023.131911.","PeriodicalId":94174,"journal":{"name":"Polish journal of radiology","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136374447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}