DTI histogram parameters correlate with the extent of myoinvasion and tumor type in endometrial carcinoma: a preliminary analysis

2019 ◽  
Vol 61 (5) ◽  
pp. 675-684
Author(s):  
Adarsh Ghosh ◽  
Tulika Singh ◽  
Veenu Singla ◽  
Rashmi Bagga ◽  
Radhika Srinivasan ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Endometrial Carcinoma ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Characteristic Curve ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
Myometrial Invasion ◽  
Tumor Type ◽  
Planar Imaging

Background Myoinvasion and tumor-type determines surgical planning in endometrial carcinoma. Purpose To evaluate whole tumor diffusion tensor imaging histogram texture parameters in evaluating myoinvasion and tumor type in endometrial carcinoma. Material and Methods Twenty-seven patients with endometrial carcinoma underwent diffusion tensor imaging on a 1.5-T MRI system using echo-planar imaging sequence with 0 and 700 s/mm2 b values. Whole tumor histogram parameters were obtained from fractional anisotropy, mean diffusivity maps. Mann–Whitney U test and receiver operating characteristic curve analyses were used Results The mean fractional anisotropy of tumors with no myoinvasion was significantly higher than tumors which underwent myoinvasion, suggesting higher anisotropy in tumors which did not invade the myometrium. Voxel-wise heterogeneity in distribution of fractional anisotropy and mean diffusivity was seen in the form of higher uniformity and lower entropy of tumors with superficial <50% myoinvasion versus >50% myoinvasion. Uniformity, entropy, and energy of voxel-wise fractional anisotropy distribution gave an area under the curve of 0.827, 0.821, and 0.796, respectively, in predicting the presence of deep myometrial invasion while energy, entropy, and uniformity of mean diffusivity distribution in tumor gave an area under the curve of 0.84, 0.815, and 0.809 respectively. Tumor type was predicted with an area under the curve of 0.747, 0.759, and 0.765 for the uniformity, energy, and entropy of voxel-wise fractional anisotropy distribution. A logistic regression combining all the important histogram parameters obtained 94% and 88% sensitivity and 88% and 80% specificity in predicting deep myoinvasion and tumor type, respectively. Conclusion Diffusion tensor histogram analysis can better characterize endometrial carcinomas and can be used as a quantitative marker of tumor behavior.

scholarly journals Use of diffusion-weighted imaging and diffusion tensor imaging in assessment of myometrial invasion in patients of endometrial carcinoma and its correlation with histopathological grading (Prospective study)

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Mahmoud Abdel-Latif ◽  
Hebatullah Safwat Mosaad
Keyword(s):  
Diffusion Tensor Imaging ◽  
Endometrial Carcinoma ◽  
Diffusion Tensor ◽  
Histological Grade ◽  
Mean Diffusivity ◽  
Myometrial Invasion ◽  
Endometrioid Adenocarcinoma ◽  
Diffusion Weighted ◽  
The Mean ◽  
And Diffusion

Abstract Background Endometrial cancer (EMC) is considered one of the most common gynecological cancers worldwide. In particular, the depth of myometrial invasion and histological grade of endometrial cancers (EMCs) are strong prognostic factors. Diffusion tensor measurements as mean diffusivity (MD) and fractional anisotropy (FA) values could be useful for assessing the depth of tumor invasion and its histological grade. The study aimed to evaluate the role of diffusion-weighted imaging (DWI) and diffusion tensor imaging in the detection of myometrial invasion in cases of endometrial carcinoma and prediction of its grade in vivo. Results This study included 50 female patients with pathologically proved endometrial carcinoma, and their ages ranged from 38 to 67 years; the mean age was 56.15 years (± 8.229 standard deviation “SD”). There was a significant statistical difference regarding the mean values of diffusion tensor fractional anisotropy (DT-FA), diffusion tensor mean diffusivity (DT-MD) and diffusion-weighted apparent diffusion coefficient(DW-ADC) values in differentiating between intact and infiltrated myometrium with (P value ≤ 0.001). The accuracy of DT-MD, DT-FA and DWI-ADC was 98%, 90% and 86%, respectively, in the detection of myometrial invasion. There was a statistically significant difference in the mean values of DT-FA, DT-MD and DW-ADC for differentiating endometrioid adenocarcinoma grades with the overall P values (˂0.001). The accuracy of DT-FA, DT- MD and DWI-ADC for differentiating grade 3 from grade 1 or 2 endometrioid adenocarcinoma was 94.9%, 84.6% and 74.4%, respectively. For differentiating grade 1 from grade 2 or 3 endometrioid adenocarcinoma, the accuracy of DT-FA, DT-MD and DWI-ADC was 90%, 89.7% and 84.6%, respectively. Mean DT-FA, DT-MD and DW-ADC values were inversely proportional to the degree of pathological grading with r =  − 0.867, − 0.762 and − 0.706, respectively. Conclusion Diffusion tensor imaging and DWI are helpful in the assessment of myometrial invasion and have a high negative correlation with histopathological grading in patients with endometrial cancer.

scholarly journals Discrimination of epileptogenic lesions and perilesional white matter using diffusion tensor magnetic resonance imaging

2018 ◽  
Vol 32 (1) ◽  
pp. 10-16
Author(s):  
Alexander Rau ◽  
Elias Kellner ◽  
Niels A Foit ◽  
Niklas Lützen ◽  
Dieter H Heiland ◽  
...  
Keyword(s):  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Focal Cortical Dysplasia ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
P Value ◽  
Radial Diffusivity ◽  
Normal Appearing White Matter ◽  
Diffusion Parameters

The aim of this study was to evaluate whether ganglioglioma (GGL), dysembryoplastic neuroepithelial tumour (DNET) and FCD (focal cortical dysplasia) are distinguishable through diffusion tensor imaging. Additionally, it was investigated whether the diffusion measures differed in the perilesional (pNAWM) and in the contralateral normal appearing white matter (cNAWM). Six GGLs, eight DNETs and seven FCDs were included in this study. Quantitative diffusion measures, that is, axial, radial and mean diffusivity and fractional anisotropy, were determined in the lesion identified on isotropic T2 or FLAIR-weighted images and in pNAWM and cNAWM, respectively. DNET differed from FCD in mean diffusivity, and GGL from FCD in radial diffusivity. Both types of glioneuronal tumours were different from pNAWM in fractional anisotropy and radial diffusivity. For identifying the tumour edges, threshold values for tumour-free tissue were investigated with receiver operating characteristic analyses: tumour could be separated from pNAWM at a threshold ≤ 0.32 (fractional anisotropy) or ≥ 0.56 (radial diffusivity) *10–3 mm2/s (area under the curve 0.995 and 0.990 respectively). While diffusion parameters of FCDs differed from cNAWM (radial diffusivity (*10–3 mm/s2): 0.74 ± 0.19 vs. 0.43 ± 0.05; corrected p-value < 0.001), the pNAWM could not be differentiated from the FCD.

scholarly journals Diffusion Tensor Imaging of the Kidneys: Influence of b-Value and Number of Encoding Directions on Image Quality and Diffusion Tensor Parameters

2013 ◽  
Vol 3 ◽  
pp. 53 ◽  
Author(s):  
Natalie C. Chuck ◽  
Günther Steidle ◽  
Iris Blume ◽  
Michael A. Fischer ◽  
Daniel Nanz ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Image Quality ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Renal Medulla ◽  
Whole Body ◽  
Acquisition Time ◽  
Data Sets ◽  
B Values

Objectives: The purpose of this study was to evaluate to which degree investment of acquisition time in more encoding directions leads to better image quality (IQ) and what influence the number of encoding directions and the choice of b-values have on renal diffusion tensor imaging (DTI) parameters. Material and Methods: Eight healthy volunteers (32.3 y ± 5.1 y) consented to an examination in a 1.5T whole-body MR scanner. Coronal DTI data sets of the kidneys were acquired with systematic variation of b-values (50, 150, 300, 500, and 700 s/mm2) and number of diffusion-encoding directions (6, 15, and 32) using a respiratory-triggered echo-planar sequence (TR/TE 1500 ms/67 ms, matrix size 128 × 128). Additionally, two data sets with more than two b-values were acquired (0, 150, and 300 s/mm2 and all six b-values). Parametrical maps were calculated on a pixel-by-pixel basis. Image quality was determined with a reader score. Results: Best IQ was visually assessed for images acquired with 15 and 32 encoding directions, whereas images acquired with six directions had significantly lower IQ ratings. Image quality, fractional anisotropy, and mean diffusivity only varied insignificantly for b-values between 300 and 500 s/mm2. In the renal medulla fractional anisotropy (FA) values between 0.43 and 0.46 and mean diffusivity (MD) values between 1.8-2.1 × 10-3 mm2/s were observed. In the renal cortex, the corresponding ranges were 0.24-0.25 (FA) and 2.2-2.8 × 10-3 mm2/s (MD). Including b-values below 300 s/mm2, notably higher MD values were observed, while FA remained constant. Susceptibility artifacts were more prominent in FA maps than in MD maps. Conclusion: In DTI of the kidneys at 1.5T, the best compromise between acquisition time and resulting image quality seems the application of 15 encoding directions with b-values between 300 and 500 s/mm2. Including lower b-values allows for assessment of fast diffusing spin components.

scholarly journals Heterogeneity of Fractional Anisotropy and Mean Diffusivity Measurements by In Vivo Diffusion Tensor Imaging in Normal Human Hearts

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0132360 ◽  
Author(s):  
Laura-Ann McGill ◽  
Andrew D. Scott ◽  
Pedro F. Ferreira ◽  
Sonia Nielles-Vallespin ◽  
Tevfik Ismail ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Diffusivity Measurements ◽  
Normal Human

scholarly journals Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

2018 ◽  
Author(s):  
Farshid Sepehrband ◽  
Ryan P Cabeen ◽  
Jeiran Choupan ◽  
Giuseppe Barisano ◽  
Meng Law ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Mean Diffusivity ◽  
Brain Parenchyma ◽  
Perivascular Space ◽  
List Type

AbstractDiffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.HighlightsPerivascular space (PVS) fluid significantly contributes to diffusion tensor imaging metricsIncreased PVS fluid results in increased mean diffusivity and decreased fractional anisotropyPVS contribution to diffusion signal is overlooked and demands further investigation

Segmental Diffusion Properties of the Corticospinal Tract and Motor Outcome in Hemiparetic Children With Perinatal Stroke

2017 ◽  
Vol 32 (6) ◽  
pp. 550-559 ◽  
Author(s):  
Jacquie Hodge ◽  
Bradley Goodyear ◽  
Helen Carlson ◽  
Xing-Chang Wei ◽  
Adam Kirton
Keyword(s):  
Diffusion Tensor Imaging ◽  
Fractional Anisotropy ◽  
Corticospinal Tract ◽  
Diffusion Tensor ◽  
Model Development ◽  
Structural Connectivity ◽  
Mean Diffusivity ◽  
Radial Diffusivity ◽  
Perinatal Stroke ◽  
Motor Outcomes

Perinatal stroke injures developing motor systems, resulting in hemiparetic cerebral palsy. Diffusion tensor imaging can explore structural connectivity. We used diffusion tensor imaging to assess corticospinal tract diffusion in hemiparetic children with perinatal stroke. Twenty-eight children (6-18 years) with unilateral stroke underwent diffusion tensor imaging. Four corticospinal tract assessments included full tract, partial tract, minitract and region of interest. Diffusion characteristics (fractional anisotropy, mean, axial, and radial diffusivity) were calculated. Ratios (lesioned/nonlesioned) were compared across segments and to validated long-term motor outcomes (Pediatric Stroke Outcome Measure, Assisting Hand Assessment, Melbourne Assessment). Fractional anisotropy and radial diffusivity ratios decreased as tract size decreased, while mean diffusivity showed consistent symmetry. Poor motor outcomes were associated with lower fractional anisotropy in all segments and radial diffusivity correlated with both Assisting Hand Assessment and Melbourne Assessment. Diffusion imaging of segmented corticospinal tracts is feasible in hemiparetic children with perinatal stroke. Correlations with disability support clinical relevance and utility in model development for personalized rehabilitation.

scholarly journals Reduction of bias in the evaluation of fractional anisotropy and mean diffusivity in magnetic resonance diffusion tensor imaging using region-of-interest methodology

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Youngseob Seo ◽  
Nancy K. Rollins ◽  
Zhiyue J. Wang
Keyword(s):  
Diffusion Tensor Imaging ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Mean Diffusivity ◽  
Region Of Interest ◽  
Superior Temporal Gyrus ◽  
Brain Structures ◽  
Equivalence Test ◽  
Mr Diffusion

Abstract Accurate quantification of fractional anisotropy (FA) and mean diffusivity (MD) in MR diffusion tensor imaging (DTI) requires adequate signal-to-noise ratio (SNR) especially in low FA areas of the brain, which necessitates clinically impractical long image acquisition times. We explored a SNR enhancement strategy using region-of-interest (ROI)-based diffusion tensor for quantification. DTI scans from a healthy male were acquired 15 times and combined into sets with different number of signal averages (NSA = 1–4, 15) at one 1.5-T Philips and three 3-T (Philips, Siemens and GE) scanners. Equivalence test was performed to determine NSA thresholds for bias-free FA and MD quantifications by comparison with reference values derived from images with NSA = 15. We examined brain areas with low FA values including caudate nucleus, globus pallidus, putamen, superior temporal gyrus, and substructures within thalamus (lateral dorsal, ventral anterior and posterior nuclei), where bias-free FA is difficult to obtain using a conventional approach. Our results showed that bias-free FA can be obtained with NSA = 2 or 3 in some cases using ROI-based analysis. ROI-based analysis allows reliable FA and MD quantifications in various brain structures previously difficult to study with clinically feasible data acquisition schemes.

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