Yazar "Urut, Devrim Ulas" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    Diffusion tensor imaging: survival analysis prediction in breast cancer patients
    (Springer Heidelberg, 2024) Urut, Devrim Ulas; Karabulut, Derya; Hereklioglu, Savas; Oezdemir, Gulsah; Cicin, Berkin Anil; Hacioglu, Bekir; Suet, Necet
    Purpose We aimed to explore the performance of diffusion-tensor imaging (DTI) and apparent diffusion coefficient (ADC) parameters in evaluating disease-free survival (DFS) and overall survival (OS) in patients with invasive breast cancer. Material and methods A total of 49 women with invasive breast cancer who were diagnosed between 2017 and 2022 were included. All patients underwent breast magnetic resonance imaging (MRI) with DTI and diffusion-weighted imaging (DWI) features, with examiners blinded to the clinical data. Volume anisotropy (VA), fractional anisotropy (FA), and ADC values were measured to assess intratumoral measured heterogeneity. Correlations and differences in diffusion metrics according to OS and DFS status of the cases were analyzed. The discriminative ability of the quantitative findings was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort. Results We evaluated patients with metastases (n = 13, 36.5%) and those without metastases (n = 36, 73.5%). Differences in the ADC, FA, and VA values were observed. The results of Cox regression survival analysis for all the patients included in the survival analysis revealed that DTI metrics contributed to the prediction of overall survival (OS) in the emerging models (p < 0.05). Both FA and VA were associated with OS (p = 0.037 and p = 0.038, respectively). However, ADC was not associated with OS (p = 0.177) or DFS (p = 0.252). Conclusion To the best of our knowledge, this is the first study to assess the prognostic value of DTI-MRI in breast cancer with statistical survival analysis techniques. We believe that DTI measurements can be used as a biomarker for OS analysis in breast cancer given the available data.
  • Küçük Resim Yok
    Öğe
    Magnetic resonance imaging predictors of surgical outcome in degenerative lumbar spinal stenosis
    (Springer, 2012) Alicioglu, Banu; Yilmaz, Baris; Bulakbasi, Nail; Copuroglu, Cem; Yalniz, Erol; Aykac, Bilal; Urut, Devrim Ulas
    To identify any MRI predictors for surgical outcomes of patients with degenerative lumbar spinal stenosis (DLSS) having instrumented posterior decompression (IPD) surgery. Seventy patients with DLSS who underwent IPD were reviewed retrospectively. The clinical score of each patient was assessed using the JOAS (Japanese Orthopedics Association Scoring) system, which is mainly based on the subjective symptoms and physical signs of the patients before (JOAS-I) and after (JOAS-II) surgery. Healing rate (HR) was calculated as: [(JOAS-II) - (JOAS-I)] x 100/[15 - (JOAS-I)]. HR > 50 % was considered clinical improvement. Radiological stenosis was assessed on MRI and was graded from 0 to 3 at the laminectomy level in terms of thecal sac-nerve root compression, foraminal stenosis, and facet degeneration. Mean HR of the improved patients (n = 39) was 81.94; HR of the unimproved patients (n = 31) was 34.75 (p < 0.05). There was no statistical difference in radiological stenosis parameters between the two groups (p > 0.05). HR was worse in patients with severe facet degeneration. Surgical outcomes of DLSS depend on multiple variables. It is not possible to predict the outcomes by assessing only one parameter. The possible outcomes should be analyzed by considering all the factors individually.