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IVIM-DKI with parametric reconstruction method for lymph node evaluation and characterization in lymphoma: A preliminary study comparison with FDG-PET/CT by Archana Vadiraj Malagi; Devasenathipathy Kandasamy; Deepam Pushpam; Kedar Khare; Raju Sharma; Rakesh Kumar; Sameer Bakhshi; Amit Mehndiratta is a Engineering article available to read on EtoBox.

What is IVIM-DKI with parametric reconstruction method for lymph node evaluation and characterization in lymphoma: A preliminary study comparison with FDG-PET/CT about?

To investigate IVIM-DKI in diagnosing benign and malignant lymph nodes in lymphoma and its subtypes in comparison to FDG-PET/CT. A total of twenty-one (n = 21) patients diagnosed with biopsy-proven Hodgkin lymphoma(HL: n = 13) and non-Hodgkin lymphoma (NHL: n = 8) were prospectively evaluated. All patients underwent MRI(T1-weighted, Short-Tau-Inversion-Recovery (STIR)), and IVIM-DKI was acquired with 9b-values (0–2000s/mm2) at 1.5T and whole-body FDG-PET/CT. The maximum and average standard uptake values (SUVmax and SUVmean) were calculated using PET images. IVIM-DKI parameters (diffusion coefficient(D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and kurtosis (k)) were estimated using IVIM-DKI model with total variation (TV) method (IDTV model). Area-under-curve from receiver-operating-curve (ROC) analysis was used to examine diagnostic value of IVIM-DKI parameters in differentiation between benign and malignant lymph nodes and HL from NHL. Machine learning-based classification of histogram features were performed using linear classifier model. For malignant vs. benign lymph nodes, apparent diffusion coefficient (ADC), f, and k were significantly (p < 0.05) lower in

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Author

Archana Vadiraj Malagi; Devasenathipathy Kandasamy; Deepam Pushpam; Kedar Khare; Raju Sharma; Rakesh Kumar; Sameer Bakhshi; Amit Mehndiratta

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Engineering (Physical Sciences)