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Oktay A, Aslan Ö, Taşkın F, Tunçbilek N, Esen İçten SG, Balcı P, Arıbal ME, Çelik L, Örgüç İŞ, Başaran Demirkazık F, Gültekin S, Aydın AM, Durmaz E, Kul S, Binokay F, Çetin M, Emlik GD, Akpınar MG, Kadıoğlu Voyvoda SN, Polat AV, Başara Akın I, Yıldız Ş, Poyraz N, Özsoy A, Öztekin PS, Elverici E, Bayrak İK, İkizceli T, Dinç F, Sezgin G, Gülşen G, Tunçbilek I, Yalçın SR, Çolakoğlu G, Ağlamış S, Yılmaz R, Rona G, Durhan G, Güner DC, Çelik Yabul F, Günbey Karabekmez L, Tutar B, Göktaş M, Buğdaycı O, Suner A, Özdemir N. Outcomes of high-risk breast lesions diagnosed using image-guided core needle biopsy: results from a multicenter retrospective study. Diagn Interv Radiol 2023; 29:579-587. [PMID: 36994925 PMCID: PMC10679644 DOI: 10.4274/dir.2022.221790] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 08/27/2022] [Indexed: 01/15/2023]
Abstract
PURPOSE The clinical management of high-risk lesions using image-guided biopsy is challenging. This study aimed to evaluate the rates at which such lesions were upgraded to malignancy and identify possible predictive factors for upgrading high-risk lesions. METHODS This retrospective multicenter analysis included 1.343 patients diagnosed with high-risk lesions using an image-guided core needle or vacuum-assisted biopsy (VAB). Only patients managed using an excisional biopsy or with at least one year of documented radiological follow-up were included. For each, the Breast Imaging Reporting and Data System (BI-RADS) category, number of samples, needle thickness, and lesion size were correlated with malignancy upgrade rates in different histologic subtypes. Pearson's chi-squared test, the Fisher-Freeman-Halton test, and Fisher's exact test were used for the statistical analyses. RESULTS The overall upgrade rate was 20.6%, with the highest rates in the subtypes of intraductal papilloma (IP) with atypia (44.7%; 55/123), followed by atypical ductal hyperplasia (ADH) (38.4%; 144/375), lobular neoplasia (LN) (12.7%; 7/55), papilloma without atypia (9.4%; 58/611), flat epithelial atypia (FEA) (8.7%; 10/114), and radial scars (RSs) (4.6%; 3/65). There was a significant relationship between the upgrade rate and BI-RADS category, number of samples, and lesion size Lesion size was the most predictive factor for an upgrade in all subtypes. CONCLUSION ADH and atypical IP showed considerable upgrade rates to malignancy, requiring surgical excision. The LN, IP without atypia, pure FEA, and RS subtypes showed lower malignancy rates when the BI-RADS category was lower and in smaller lesions that had been adequately sampled using VAB. After being discussed in a multidisciplinary meeting, these cases could be managed with follow-up instead of excision.
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Affiliation(s)
- Ayşenur Oktay
- Department of Radiology, Ege University Faculty of Medicine, İzmir, Turkey
| | - Özge Aslan
- Department of Radiology, Ege University Faculty of Medicine, İzmir, Turkey
| | - Füsun Taşkın
- Department of Radiology, Acıbadem MAA University Faculty of Medicine; Acıbadem MAA University Senology Research Institute, Acıbadem Atakent Hospital, İstanbul, Turkey
| | - Nermin Tunçbilek
- Department of Radiology, Trakya University Faculty of Medicine, Edirne, Turkey
| | - Selma Gül Esen İçten
- Department of Radiology, Acıbadem MAA University Faculty of Medicine; Acıbadem MAA University Senology Research Institute, İstanbul, Turkey
| | - Pınar Balcı
- Department of Radiology, Dokuz Eylül University Faculty of Medicine, İzmir, Turkey
| | - Mustafa Erkin Arıbal
- Department of Radiology, Acıbadem MAA University Faculty of Medicine, İstanbul, Turkey
| | - Levent Çelik
- Department of Radiology, Maltepe University Faculty of Medicine; İstanbul, Turkey
| | - İhsan Şebnem Örgüç
- Department of Radiology, Manisa Celal Bayar University Faculty of Medicine, Manisa, Turkey
| | | | - Serap Gültekin
- Department of Radiology, Gazi University Faculty of Medicine, Ankara, Turkey
| | - Ayşe Murat Aydın
- Department of Radiology, Fırat University Faculty of Medicine, Elazığ, Turkey
| | - Emel Durmaz
- Department of Radiology, Akdeniz University Faculty of Medicine, Antalya, Turkey
| | - Sibel Kul
- Department of Radiology, Karadeniz Techinal University Faculty of Medicine, Trabzon, Turkey
| | - Figen Binokay
- Department of Radiology, Çukurova University Faculty of Medicine, Adana, Turkey
| | - Meltem Çetin
- Department of Radiology, Süleyman Demirel University Faculty of Medicine, Isparta, Turkey
| | - Ganime Dilek Emlik
- Department of Radiology, Necmettin Erbakan University Meram Faculty of Medicine, Konya, Turkey
| | | | - Sadiye Nuray Kadıoğlu Voyvoda
- Department of Radiology, University of Health Sciences Turkey, Kartal Dr. Lütfi Kırdar City Hospital, İstanbul, Turkey
| | - Ahmet Veysel Polat
- Department of Radiology, Ondokuz Mayıs University Faculty of Medicine, Samsun, Turkey
| | - Işıl Başara Akın
- Department of Radiology, Dokuz Eylül University Faculty of Medicine, İzmir, Turkey
| | - Şeyma Yıldız
- Department of Radiology, Bezmialem Vakıf University Faculty of Medicine, İstanbul, Turkey
| | - Necdet Poyraz
- Department of Radiology, Necmettin Erbakan University Meram Faculty of Medicine, Konya, Turkey
| | - Arzu Özsoy
- Department of Radiology, University of Health Sciences Turkey, Ankara City Hospital, Ankara, Turkey
| | - Pelin Seher Öztekin
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Turkey
| | - Eda Elverici
- Department of Radiology, University of Health Sciences Turkey, Ankara City Hospital, Ankara, Turkey
| | - İlkay Koray Bayrak
- Department of Radiology, Ondokuz Mayıs University Faculty of Medicine, Samsun, Turkey
| | - Türkan İkizceli
- Department of Radiology, University of Health Sciences Turkey, İstanbul Haseki Training and Research Hospital, İstanbul, Turkey
| | - Funda Dinç
- Department of Radiology, Muğla Sıtkı Koman University Faculty of Medicine, Muğla Turkey
| | - Gülten Sezgin
- Department of Radiology, İzmir Katip Çelebi University, Atatürk Training and Research Hospital, İzmir, Turkey
| | - Gökçe Gülşen
- Department of Radiology, University of Health Sciences Turkey, İstanbul Haseki Training and Research Hospital, İstanbul, Turkey
| | - Işıl Tunçbilek
- Department of Radiology, Medsentez Private Clinic, Ankara, Turkey
| | | | - Gül Çolakoğlu
- Department of Radiology, University of Health Sciences Turkey, İzmir Tepecik Training and Research Hospital, İzmir, Turkey
| | - Serpil Ağlamış
- Department of Radiology, Fırat University Faculty of Medicine, Elazığ, Turkey
| | - Ravza Yılmaz
- Department of Radiology, İstanbul University, İstanbul Faculty of Medicine, İstanbul, Turkey
| | - Günay Rona
- Department of Radiology, University of Health Sciences Turkey, Kartal Dr. Lütfi Kırdar City Hospital, İstanbul, Turkey
| | - Gamze Durhan
- Department of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Davut Can Güner
- Department of Radiology, Maltepe University Faculty of Medicine; İstanbul, Turkey
| | - Fatma Çelik Yabul
- Department of Radiology, Bezmialem Vakıf University Faculty of Medicine, İstanbul, Turkey
| | - Leman Günbey Karabekmez
- Department of Radiology, Ankara Yıldırım Beyazıt University Faculty of Medicine, Ankara, Turkey
| | - Burçin Tutar
- Department of Radiology, Acıbadem Maslak Hospital, İstanbul, Turkey
| | - Muhammet Göktaş
- Department of Radiology, Ministry of Health Çerkezköy State Hospital, İstanbul, Turkey
| | - Onur Buğdaycı
- Department of Radiology, Marmara University Faculty of Medicine, İstanbul, Turkey
| | - Aslı Suner
- Department of Biostatistics and Medical Informatics, Ege University Faculty of Medicine, İzmir, Turkey
| | - Necmettin Özdemir
- Department of Medical Pathology, Ege University Faculty of Medicine, İzmir, Turkey
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Lafcı O, Celepli P, Seher Öztekin P, Koşar PN. DCE-MRI Radiomics Analysis in Differentiating Luminal A and Luminal B Breast Cancer Molecular Subtypes. Acad Radiol 2023; 30:22-29. [PMID: 35595629 DOI: 10.1016/j.acra.2022.04.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [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: 03/07/2022] [Revised: 03/30/2022] [Accepted: 04/06/2022] [Indexed: 12/26/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of the present study was to investigate the association between Luminal A and Luminal B molecular subtypes and radiomic features of dynamic contrast‑enhanced magnetic resonance imaging in patients with invasive breast cancer. MATERIALS AND METHODS Seventy-three patients with histopathologically proven invasive ductal cancer (IDC) were selected. Tumors were classified into molecular subtypes: Luminal A (estrogen receptor (ER)-positive and/or progesterone receptor (PR)-positive, human epidermal growth factor receptor type 2 (HER2) -negative, proliferation marker Ki-67<20) and Luminal B (ER-positive and/or PR-positive, HER2-positive or HER2-negative with high Ki-67 ≥20). A total of 81 tumoral lesions were evaluated on T1-weighted fat-suppressed sagittal post-contrast late-phase MRI images after the required "pre-process" steps and 3D segmentations were made. Forty-three radiomic features including: 1 conventional, 4 shape, 6 histogram, 7 Grey-Level Co-occurrence Matrix (GLCM), 11 Grey-Level Run-Length Matrix (GLRLM), 3 Neighborhood Grey-Level Difference Matrix (NGLDM), 11 Grey-Level Zone-Length Matrix (GLZLM) were extracted by using the software LIFEX. RESULTS A statistically significant difference was found in radiomic features including; a) Histogram: "skewness", b) Shape: "volume-ml, volume-voxel," c) GLCM: "entropy.log10, entropy.log2, energy", d) GLRLM: "GLNU, RLNU, HGRE," e) NGLDM: "busyness," f) GLZLM: "GLNU, HGZE, ZLNU, SZE" between two different molecular subtypes. The model combining Shape-volume (ml) and GLZLM-HGZE yielded 0.746 area under the curve (AUC), 0.744 sensitivity, 0.643 specificity and 0.694 accuracy. CONCLUSION Radiomic properties that may distinguish Luminal A and Luminal B molecular subtypes of IDC were identified. The radiomic features were thought to reflect the intratumoral heterogeneity in molecular subtypes. This study demonstrated that the characterization of Luminal A and Luminal B tumors could be made non-invasively by radiomics analysis.
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Affiliation(s)
- Oğuz Lafcı
- Department of Radiology, Ankara Training and Research Hospital, University of Health Sciences, Hacettepe Mh. Ulucanlar Cd. No:89 Altındağ, Ankara, Turkey.
| | - Pınar Celepli
- Department of Pathology, Ankara Training and Research Hospital, University of Health Sciences, Ankara, Turkey
| | - Pelin Seher Öztekin
- Department of Radiology, Ankara Training and Research Hospital, University of Health Sciences, Hacettepe Mh. Ulucanlar Cd. No:89 Altındağ, Ankara, Turkey
| | - Pınar Nercis Koşar
- Department of Radiology, Ankara Training and Research Hospital, University of Health Sciences, Hacettepe Mh. Ulucanlar Cd. No:89 Altındağ, Ankara, Turkey
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Karaer Büberci R, Öztekin PS, Duranay M. The relationship between apelin and carotid intima media thickness, and the presence of plaque in dialysis patients. Semin Dial 2022; 35:337-342. [PMID: 35118706 DOI: 10.1111/sdi.13052] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/26/2021] [Accepted: 12/23/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Apelin is a peptide that has important effects on the cardiovascular system due to its anti-atherogenic properties and regulating blood pressure. There is not enough research evaluating the effects of apelin levels on the cardiovascular system in hemodialysis (HD) and peritoneal dialysis (PD) patients concurrently. The aim of this study was to determine apelin levels in dialysis, and control groups and to investigate the relationship between apelin and carotid intima media thickness (CIMT). MATERIALS AND METHODS Thirty three HD patients, 35 PD patients, and 15 healthy individuals were included in the study. All laboratory data, N-terminal pro-B-type natriuretic peptide (NT-proBNP), IL-6, and apelin-13 levels were analyzed. To prevent interobserver errors in CIMT measurement, the analyses were performed by a single radiologist. RESULT CIMT, presence of plaque, apelin, NT-proBNP, IL-6, and C-reactive protein (CRP) levels were higher in dialysis patients. There was a relationship between apelin and CIMT, and between apelin and high-density lipoprotein (HDL) in PD patients. Age, apelin, HDL, parathormone (PTH), glucose, and smoking were found to affect the presence of plaque in dialysis patients. CONCLUSION Apelin levels were high in dialysis patients. Especially in PD patients, there was a negative correlation between apelin and CIMT, and between apelin and HDL. Therefore, apelin may play a role in the pathogenesis of cardiovascular diseases in PD patients.
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Affiliation(s)
| | | | - Murat Duranay
- Nephrology Department, Ankara Training and Research Hospital, Ankara, Turkey
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Tek C, Öztekin PS, Celepli P, Uçar F, Koşar PN. Using the Superb Microvascular Imaging Method in the Distinction of Intraductal Papilloma and Duct Ectasia With Secretion. J Ultrasound Med 2021; 40:269-277. [PMID: 32681668 DOI: 10.1002/jum.15396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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: 04/29/2020] [Revised: 05/26/2020] [Accepted: 06/01/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES To investigate the diagnostic value of a Superb Microvascular Imaging (SMI; Toshiba Medical Systems, Tokyo, Japan) Doppler examination for distinguishing intraductal papilloma (IDP) from duct ectasia with secretion in lesions smaller than 1 cm compared to color Doppler imaging (CDI) and power Doppler imaging (PDI). METHODS Fifty-nine lesions were evaluated by grayscale ultrasound, CDI, PDI, and SMI. Biopsied tissue samples were analyzed. Ultrasound evaluations and Doppler examinations were performed with a Toshiba Aplio 500 device. The lesions were divided into 2 groups, secretion and IDP, according to the pathologic results. Color Doppler imaging, PDI, and SMI data were compared statistically to investigate their diagnostic values. RESULTS Of the 59 lesions, 22 were secretion, and 37 were IDP. The mean diameters ± SDs were 4.7 ± 0.6 mm in the secretion group and 4.9 ± 0.8 mm in the IDP group (P = .315). There was no significant difference in grayscale ultrasound features such as shape or margin between the groups (P > .05). No significant difference was found between the groups in CDI or PDI characteristics (P > .999; P = .702, respectively). The color SMI evaluation results showed no vascularity in 18 (81.8%) lesions in the secretion group. Vascularity was detected in 32 patients (86.5%) in the IDP group. In the receiver operating characteristic analysis, the areas under the curve were calculated as 0.842 (95% confidence interval [CI], 0.728-0.925) for SMI, 0.522 (95% CI, 0.388-0.654) for PDI, and 0.518 (95% CI, 0.384-0.650) for CDI. CONCLUSIONS Superb Microvascular Imaging is more accurate and has more diagnostic ability than CDI or PDI in distinguishing small IDPs from duct ectasia with secretion because of its ability to visualize slow flow speeds of vascular structures.
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Affiliation(s)
- Cihat Tek
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Turkey
| | - Pelin Seher Öztekin
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Turkey
| | - Pınar Celepli
- Department of Pathology, Ankara Training and Research Hospital, Ankara, Turkey
| | - Funda Uçar
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Turkey
| | - Pınar Nercis Koşar
- Department of Radiology, Ankara Training and Research Hospital, Ankara, Turkey
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Durhan G, Öztekin PS, Ünverdi H, Değirmenci T, Durhan A, Karakaya J, Nercis Koşar P, Necip Köseoğlu E, Hücümenoğlu S. Do Histopathological Features and Microcalcification Affect the Elasticity of Breast Cancer? J Ultrasound Med 2017; 36:1101-1108. [PMID: 28240797 DOI: 10.7863/ultra.16.06064] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [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: 06/25/2016] [Accepted: 08/22/2016] [Indexed: 06/06/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate any association between histological grade, molecular subtypes of breast cancer, and strain elastography, and to investigate whether microcalcification affects the stiffness of tumor in breast cancers with the same histological grade. METHODS Between April 2015 and March 2016, 94 lesions of 94 patients with the diagnosis of invasive ductal carcinoma were included in the study. Strain elastography was performed on all patients before biopsy. Histological grades (Grades 1, 2, and 3), molecular subtypes (luminal A, luminal B, Her-2, and basal-like), and strain ratio (SR) were compared. In the same histological grades, patients were divided into two groups according to the presence of microcalcifications, and the groups were compared with each other. RESULTS Compared with Grades 1 (20.5) and 2 (23.7), Grade 3 (11.7) showed lower SR values (Grade 3-2, P = .01; Grade 3-1, P = .2). The groups with microcalcification had slightly higher SR in all histological grades, but not of statistical significance. In molecular subtypes, luminal A and B demonstrated higher SR, whereas HER2 and basal-like had lower SR (P > .05 for all group comparisons). CONCLUSIONS Grade 3 invasive ductal carcinomas are different from other grades with lower SR values. The presence of microcalcifications and molecular subtypes do not affect elasticity like a high histological grade does.
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Affiliation(s)
- Gamze Durhan
- Department of Radiology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Pelin Seher Öztekin
- Department of Radiology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Hatice Ünverdi
- Department of Pathology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Tülin Değirmenci
- Department of Radiology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Abdullah Durhan
- Department of General Surgery, Surgical Oncology Unit, Ankara University Medical School, Ankara, Turkey
| | - Jale Karakaya
- Department of Biostatistics, Hacettepe University Medical School, Ankara, Turkey
| | - Pınar Nercis Koşar
- Department of Radiology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Enver Necip Köseoğlu
- Department of Radiology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
| | - Sema Hücümenoğlu
- Department of Pathology, Ministry of Health Ankara Training and Research Hospital, Ankara, Turkey
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