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TÜRK, HACI MEHMET

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HACI MEHMET
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TÜRK
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Subject: apparent diffusion coefficient ×

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    PublicationOpen Access
    Diagnostic performance of apparent diffusion coefficient values for the differentiation of intrahepatic cholangiocarcinoma from gastrointestinal adenocarcinoma liver metastases
    (2021-12-22T00:00:00Z) Yilmaz, TEMEL FATİH; Gultekin, Mehmet Ali; Turk, Hacı Mehmet; Cesme, Dilek Hacer; Besiroglu, Mehmet; Simsek, Melih; Toprak, Huseyin; Alkan, ALPAY; YILMAZ, TEMEL FATİH; TÜRK, HACI MEHMET; ÇEŞME, DİLEK HACER; ŞİMŞEK, MELİH; ALKAN, ALPAY; TOPRAK, HÜSEYİN
    Background: We aimed to investigate whether there is a difference between intrahepatic cholangiocarcinoma (IHCC) and liver metastases of gastrointestinal system (GIS) adenocarcinoma in terms of apparent diffusion coefficient (ADC) values. Patients and methods: From January 2018 to January 2020, we retrospectively examined 64 consecutive patients with liver metastases due to gastrointestinal system adenocarcinomas and 13 consecutive IHCC in our hospital's medical records. After exclusions, fifty-three patients with 53 liver metastases and 10 IHCC were included in our study. We divided the patients into two groups as IHCC and liver metastases of GIS adenocarcinoma. For mean apparent diffusion coefficient (ADCmean) values, the region of interests (ROI) was placed in solid portions of the lesions. ADCmean values of groups were compared. Results: The mean age of IHCC group was 62.50 ± 13.49 and mean age of metastases group was 61.15 ± 9.18. ADCmean values were significantly higher in the IHCC group compared to the metastatic group (p < 0.001). ROC curves method showed high diagnostic accuracy (AUC = 0.879) with cut-off value of < 1178 x 10-6 mm2/s for ADCmean (Sensitivity = 90.57, Specificity = 70.0, positive predictive value [PPV] = 94.1, negative predictive value [NPV] = 58.3) in differentiating adenocarcinoma metastases from IHCC. Conclusions: The present study results suggest that ADC values have a potential role for differentiation between IHCC and GIS adenocarcinoma liver metastases which may be valuable for patient management.
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    PublicationOpen Access
    Diffusion Tensor Imaging Can Discriminate the Primary Cell Type of Intracranial Metastases for Patients with Lung Cancer.
    (2021-03-04T00:00:00Z) Bilgin, Sabriye Sennur; Gultekin, Mehmet Ali; Yurtsever, Ismail; Yilmaz, Temel Fatih; Cesme, Dilek Hacer; Bilgin, Melike; Topcu, Atakan; Besiroglu, Mehmet; Turk, Haci Mehmet; Alkan, ALPAY; Bilgin, Mehmet; GÜLTEKİN, MEHMET ALİ; YURTSEVER, İSMAİL; YILMAZ, TEMEL FATİH; ÇEŞME, DİLEK HACER; TÜRK, HACI MEHMET; ALKAN, ALPAY; BİLGİN, MEHMET
    Purpose: Histopathological differentiation of primary lung cancer is clinically important. We aimed to investigate whether diffusion tensor imaging (DTI) parameters of metastatic brain lesions could predict the histopathological types of the primary lung cancer. Methods: In total, 53 patients with 98 solid metastatic brain lesions of lung cancer were included. Lung tumors were subgrouped as non-small cell carcinoma (NSCLC) (n = 34) and small cell carcinoma (SCLC) (n = 19). Apparent diffusion coefficient (ADC) and Fractional anisotropy (FA) values were calculated from solid enhanced part of the brain metastases. The association between FA and ADC values and histopathological subtype of the primary tumor was investigated. Results: The mean ADC and FA values obtained from the solid part of the brain metastases of SCLC were significantly lower than the NSCLC metastases (P < 0.001 and P = 0.003, respectively). ROC curve analysis showed diagnostic performance for mean ADC values (AUC=0.889, P = < 0.001) and FA values (AUC = 0.677, P = 0.002). Cut-off value of > 0.909 × 10-3 mm2/s for mean ADC (Sensitivity = 80.3, Specificity = 83.8, PPV = 89.1, NPV = 72.1) and > 0.139 for FA values (Sensitivity = 80.3, Specificity = 54.1, PPV = 74.2, NPV= 62.5) revealed in differentiating NSCLC from NSCLC. Conclusion: DTI parameters of brain metastasis can discriminate SCLC and NSCLC. ADC and FA values of metastatic brain lesions due to the lung cancer may be an important tool to differentiate histopathological subgroups. DTI may guide clinicians for the management of intracranial metastatic lesions of lung cancer.