Diffusion Weighted Imaging for Differentiating Benign from Malignant Orbital Tumors: Diagnostic Performance of the Apparent Diffusion Coefficient Based on Region of Interest Selection Method

Abstract

ObjectiveTo evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors.Materials and MethodsDiffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC).ResultsMalignant group showed significantly lower ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS as differentiating index, respectively (all p > 0.05). The ROISS and ROIRDSS required comparable measurement time (p > 0.05), while significantly shorter than ROIWT (p < 0.05). The ROISS showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080–0.123] × 10-3 mm2/s; ICC, 0.997) among three ROI methods.ConclusionApparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROISS method are potentially useful for clinical practice.

Assessment of lacrimal glands in thyroid eye disease with diffusion-weighted magnetic resonance imaging

“…Diffusion-weighted magnetic resonance (MR) imaging provides characterisation of soft tissues and their physiological processes because it reflects the random motion of water protons, which is disturbed by intracellular organelles and macromolecules located in the tissues [10,11]. Diffusion-weighted MR imaging is used for characterisation of orbital [12][13][14] and thyroid lesions [15,16]. Few studies discuss diffusion-weighted and diffusion tensor imaging of the extra-ocular muscles [17][18][19][20] and the optic nerves [21,22] in patients with thyroid eye disease.…”

Dynamic contrast‐enhanced MRI in orbital lymphoproliferative disorders: Effects of region of interest selection methods on time efficiency, measurement reproducibility, and diagnostic ability

“…[9][10][11][12][13] Previous imaging-related studies mainly used three kinds of ROI selection methods to obtain quantitative parameters, including ROI covering the whole tumor (ROI WT ), ROI covering the single slice in which the tumor showed largest diameter (ROI SS ), and ROI covering the "hot spot" within the tumor (ROI HS ). 14,15 ROI HS may lead to significant interobserver variability. 14 ROI WT can overcome this problem; however, a long postprocessing time limits its wide application.…”

“…14,15 ROI HS may lead to significant interobserver variability. 14 ROI WT can overcome this problem; however, a long postprocessing time limits its wide application. 14 The influence of ROI selection methods on the measurement of the apparent diffusion coefficient value has been widely studied, [14][15][16][17] and its influence on DCE-MRI-derived parameters has been only studied in patients with renal cell carcinoma and head and neck cancer.…”

“…14 ROI WT can overcome this problem; however, a long postprocessing time limits its wide application. 14 The influence of ROI selection methods on the measurement of the apparent diffusion coefficient value has been widely studied, [14][15][16][17] and its influence on DCE-MRI-derived parameters has been only studied in patients with renal cell carcinoma and head and neck cancer. 12,13 Therefore, the purpose of this study was to assess the effects of different ROI selection methods on the measurement of DCE-MRI-derived quantitative parameters, and their diagnostic ability in discriminating malignant from benign OLPDs.…”

Evaluation of Effects of TGF‐β1 Inhibition on Gastric Cancer in Nude Mice by Diffusion Kurtosis Imaging and In‐Line X‐ray Phase Contrast Imaging With Sequential Histology

“…The final each parameter value was determined as the mean value in the delineated ROI results by integrating all tumor voxels from all delineated slices into the total signal intensity. 22,26 To evaluate the therapeutic response based on RECIST guidelines, tumor size defined by the longest dimension on axial T 2 W images was measured and recorded. 27,28 A set of source DKI diffusion images and the ROI-based fitted curves was drawn by using the manufacturer-supplied software (PRIDE DWI Tool, v. 1.5, Philips Healthcare) ( Supplementary Figs.…”