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Delibaş D, Evrimler Ş, Ercan K, Gümüş M, Sarıyıldırım A, Arslan H. Iron overload in hemodialysis patients: Comparison of serum iron parameters with T2* MRI sequence. J Clin Ultrasound 2024; 52:124-130. [PMID: 37933208 DOI: 10.1002/jcu.23608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/17/2023] [Accepted: 10/27/2023] [Indexed: 11/08/2023]
Abstract
PURPOSE To evaluate correlation between serum iron parameters and liver T2* value in hemodialysis patients with iron overload due to parenteral iron therapy. MATERIALS AND METHODS We evaluated 30 hemodialysis patients using a multiecho T2*-weighted MRI sequence. Age, sex, duration of dialysis, iron and erythropoietin doses taken in the past year, and serum iron parameters were recorded. Liver T2* values were averaged from three distinct liver regions. A T2* value of 33 ± 7 ms is considered normal. Declines below 24, 21, and 14 ms signify iron overload grades 1, 2, and 3, respectively. RESULTS There was no statistically significant difference comparing the measurements of 3 different ROIs (p > 0.05). A total of 23 patients (76.6%) had iron overload. Serum ferritin levels of patients with iron overload were significantly higher than those without iron overload (687.25 [186.5-1489] ng/mL vs. 371.25 [127.5-542.5] ng/mL, p = 0.008). No linear correlation was observed between age, dialysis duration, serum iron metrics, medication doses, and T2* values. Likewise, no significant differences were found among patients based on iron overload status or its grades concerning these parameters. CONCLUSION While standard serum markers might overlook iron overload, elevated ferritin levels are promising. MRI reliably detects iron overload in patients receiving parenteral iron.
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Affiliation(s)
- Deniz Delibaş
- Department of Radiology, Ankara Education and Research Hospital, Ankara, Turkey
| | - Şehnaz Evrimler
- Department of Radiology, Ankara Etlik City Hospital, Ankara, Turkey
| | - Karabekir Ercan
- Department of Radiology, Ankara Bilkent City Hospital, Ankara, Turkey
| | - Mehmet Gümüş
- Faculty of Medicine, Ankara City Hospital, Department of Radiology, Yıldırım Beyazıt University, Ankara, Turkey
| | | | - Halil Arslan
- Faculty of Medicine, Ankara City Hospital, Department of Radiology, Yıldırım Beyazıt University, Ankara, Turkey
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Koç U, Sezer EA, Özkaya YA, Yarbay Y, Beşler MS, Taydaş O, Yalçın A, Evrimler Ş, Kızıloğlu HA, Kesimal U, Atasoy D, Oruç M, Ertuğrul M, Karakaş E, Karademir F, Sebik NB, Topuz Y, Aktan ME, Sezer Ö, Aydın Ş, Varlı S, Akdoğan E, Ülgü MM, Birinci Ş. Elevating healthcare through artificial intelligence: analyzing the abdominal emergencies data set (TR_ABDOMEN_RAD_EMERGENCY) at TEKNOFEST-2022. Eur Radiol 2023:10.1007/s00330-023-10391-y. [PMID: 37947834 DOI: 10.1007/s00330-023-10391-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 08/28/2023] [Accepted: 09/08/2023] [Indexed: 11/12/2023]
Abstract
OBJECTIVES The artificial intelligence competition in healthcare at TEKNOFEST-2022 provided a platform to address the complex multi-class classification challenge of abdominal emergencies using computer vision techniques. This manuscript aimed to comprehensively present the methodologies for data preparation, annotation procedures, and rigorous evaluation metrics. Moreover, it was conducted to introduce a meticulously curated abdominal emergencies data set to the researchers. METHODS The data set underwent a comprehensive central screening procedure employing diverse algorithms extracted from the e-Nabız (Pulse) and National Teleradiology System of the Republic of Türkiye, Ministry of Health. Full anonymization of the data set was conducted. Subsequently, the data set was annotated by a group of ten experienced radiologists. The evaluation process was executed by calculating F1 scores, which were derived from the intersection over union values between the predicted bounding boxes and the corresponding ground truth (GT) bounding boxes. The establishment of baseline performance metrics involved computing the average of the highest five F1 scores. RESULTS Observations indicated a progressive decline in F1 scores as the threshold value increased. Furthermore, it could be deduced that class 6 (abdominal aortic aneurysm/dissection) was relatively straightforward to detect compared to other classes, with class 5 (acute diverticulitis) presenting the most formidable challenge. It is noteworthy, however, that if all achieved outcomes for all classes were considered with a threshold of 0.5, the data set's complexity and associated challenges became pronounced. CONCLUSION This data set's significance lies in its pioneering provision of labels and GT-boxes for six classes, fostering opportunities for researchers. CLINICAL RELEVANCE STATEMENT The prompt identification and timely intervention in cases of emergent medical conditions hold paramount significance. The handling of patients' care can be augmented, while the potential for errors is minimized, particularly amidst high caseload scenarios, through the application of AI. KEY POINTS • The data set used in artificial intelligence competition in healthcare (TEKNOFEST-2022) provides a 6-class data set of abdominal CT images consisting of a great variety of abdominal emergencies. • This data set is compiled from the National Teleradiology System data repository of emergency radiology departments of 459 hospitals. • Radiological data on abdominal emergencies is scarce in literature and this annotated competition data set can be a valuable resource for further studies and new AI models.
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Affiliation(s)
- Ural Koç
- Department of Radiology, Ankara Bilkent City Hospital, Ankara, Türkiye.
| | - Ebru Akçapınar Sezer
- Artificial Intelligence Division, Department of Computer Engineering, Hacettepe University, Ankara, Türkiye
| | | | - Yasin Yarbay
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
| | | | - Onur Taydaş
- Department of Radiology, Faculty of Medicine, Sakarya University, Sakarya, Türkiye
| | - Ahmet Yalçın
- Department of Radiology, Faculty of Medicine, Erzurum Atatürk University, Erzurum, Türkiye
| | - Şehnaz Evrimler
- Department of Radiology, Ankara Etlik City Hospital, Ankara, Türkiye
| | | | - Uğur Kesimal
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Türkiye
| | - Dilara Atasoy
- Department of Radiology, Sivas Numune State Hospital, Sivas, Türkiye
| | - Meltem Oruç
- Department of Radiology, Karaman Training and Research Hospital, Karaman, Türkiye
| | - Mustafa Ertuğrul
- Department of Radiology, Ürgüp State Hospital, Nevşehir, Türkiye
| | - Emrah Karakaş
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
| | | | - Nihat Barış Sebik
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
| | | | | | - Özgür Sezer
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
| | - Şahin Aydın
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
| | - Songül Varlı
- Health Institutes of Türkiye, İstanbul, Türkiye
- Department of Computer Engineering, Yıldız Technical University, İstanbul, Türkiye
| | - Erhan Akdoğan
- Health Institutes of Türkiye, İstanbul, Türkiye
- Department of Mechatronics Engineering, Faculty of Mechanical Engineering, Yıldız Technical University, İstanbul, Türkiye
| | - Mustafa Mahir Ülgü
- General Directorate of Health Information Systems, Ministry of Health, Ankara, Türkiye
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Erdoğan M, Evrimler Ş, Aydın H, Karaibrahimoğlu A, Şengül SS. Solitary Pulmonary Nodule: Morphological Effects on Metabolic Activity Assessment. Mol Imaging Radionucl Ther 2019; 28:112-119. [PMID: 31507144 PMCID: PMC6746010 DOI: 10.4274/mirt.galenos.2019.65707] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Objectives We aimed to evaluate the effects of morphological characteristics of the solitary pulmonary nodules (SPN) on metabolic activity assessment. To the best of our knowledge, this is the first study to compare the volumetric metabolic activity parameters according to the morphologic parameters of the nodules. Methods In this retrospective study, 18F-FDG positron emission tomography and computed tomography scans performed between 2011 and 2018 were evaluated by a nuclear and diagnostic radiologist. One hundred thirteen patients with SPNs with biopsy-proven diagnosis were included. SPNs were classified as solid, partially solid (PS), and ground glass opacity (GGO). Results SPN diameter, SUVmax, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and density were significantly higher in the malignant group. SUVmax, MTV, TLG increased in direct proportion to the diameter. There was no a significant difference between GGO, PS, and solid nodules in terms of SUVmax values. MTV and TLG values increased in parallel with the density of the nodules, but this increase was only significant in the malignant group. There was a significant difference between SPNs <2 cm and SPNs ≥2 cm in terms of MTV, while there was no difference in terms of SUVmax. The cut-off value determined by the ROC curve was found to be 4.39 for SUVmax, 7.33 mL for MTV and 31.88 g for TLG. The cut-off values for SUVmax of solid and subsolid nodules were close to each other, but cut-off values for MTV and TLG were higher in solid nodules. Conclusion SUVmax, MTV, and TLG are affected by diameter and attenuation. We suggest using different MTV and TLG cut-off values for solid and subsolid nodules, but we suggest using same SUVmax values. MTV can be a more reliable parameter than SUVmax in prediction of malignancy in smaller nodules.
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Affiliation(s)
- Mehmet Erdoğan
- Süleyman Demirel University Faculty of Medicine, Department of Nuclear Medicine, Isparta, Turkey
| | - Şehnaz Evrimler
- Süleyman Demirel University Faculty of Medicine, Department of Radiology, Isparta, Turkey
| | - Hüseyin Aydın
- Süleyman Demirel University Faculty of Medicine, Department of Radiology, Isparta, Turkey
| | - Adnan Karaibrahimoğlu
- Süleyman Demirel University Faculty of Medicine, Department of Biostatistics and Medical Informatics, Isparta, Turkey
| | - Sevim Süreyya Şengül
- Süleyman Demirel University Faculty of Medicine, Department of Nuclear Medicine, Isparta, Turkey
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Özmen E, Algın O, Evrimler Ş, Arslan H. The Impact of Gd-Eob-Dtpa-Enhanced MR Cholangiography in Biliary Diseases: Comparison with T2-Weighted MR Cholangiopancreatography. Balkan Med J 2016; 33:275-82. [PMID: 27308071 DOI: 10.5152/balkanmedj.2016.140872] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 06/03/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Contrast enhanced magnetic resonance cholangiography is a novel technique and promising method in demonstrating biliary tree anatomy and evaluating biliary disorders. However, to date, there are a limited number of studies that have focused on the impact of this technique. AIMS We aimed to evaluate the additional role of contrast enhanced MR cholangiography (MRC) and compare contrast enhanced MRC with T2-weighted (w) magnetic resonance cholangiopancreatography (MRCP) in the diagnosis of biliary disorders. STUDY DESIGN Diagnostic accuracy study. METHODS The T2w-MRCP and contrast enhanced MRC sequences of 31 patients whose gold standard test results were available were scored visually for the existence of pathological findings with regard to any of the biliary diseases. Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) was used as the contrast agent. The correlation values were determined according to the statistical analysis made from those scores and the sensitivity, specificity and accuracy values of each sequence were detected as well. RESULTS We detected that the correlation values with gold standard methods of contrast enhanced MRC sequences were significantly higher than the ones of T2w-MRCP sequences. The correlation ratios of T2w-MRCP sequences were between 26 and 34%, while those for contrast enhanced MRC sequences were between 81 and 83% for the first reader and the correlation ratios of T2w-MRCP sequences were between 10 and 61%, whereas those of contrast enhanced MRC were between 79 and 81% for the second reader The mean sensitivity, specificity and accuracy values of T2w-MRCP sequences were 14.3-42.5%, 85-89.2% and 59.3-72.5%, respectively, while the mean sensitivity, specificity and accuracy values of contrast enhanced MRC sequences were 100%, 86.7% and 93.2-93.3%, respectively. CONCLUSION We suggest that obtaining of contrast enhanced MRC sequences in addition to the T2w-MRCP can be useful in the diagnosis of many diseases in relation with biliary tree.
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Affiliation(s)
- Evrim Özmen
- Department of Radiology, İstanbul University Cerrahpaşa School of Medicine, İstanbul, Turkey
| | - Oktay Algın
- Department of Radiology, Atatürk Training and Research Hospital, Ankara, Turkey
| | - Şehnaz Evrimler
- Department of Radiology, Atatürk Training and Research Hospital, Ankara, Turkey
| | - Halil Arslan
- Department of Radiology, Atatürk Training and Research Hospital, Ankara, Turkey
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