Intravoxel incoherent motion and diffusion kurtosis imaging for discriminating soft tissue sarcoma from vascular anomalies

Wu, Gang; Liu, Xuanlin; Xiong, Yan; Ran, Jun; Li, Xiaoming

doi:10.1097/md.0000000000013641

Cited by 18 publications

(27 citation statements)

References 20 publications

(14 reference statements)

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“…The diffusion coefficient of continuous distribution of micro motion in voxel is assumed to be two parts, namely D (diffusion coefficient) and D * (pseudo-diffusion coefficient), which represent slow and fast diffusion, respectively. f is the perfusion fraction representing the volume ratio of perfusion effect produced by local microcirculation to the total volume [ 11 , 12 ]. At present, IVIM-DWI has been widely used in differential diagnosis, grading, and prediction of survival time and prognosis of brain tumors [ 13 – 15 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI

Yang

Huang

et al. 2021

Aging

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Glioma characterized by high morbidity and mortality, is one of the most common brain tumors. The application of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in differentiating glioma grading and IDH1 mutation status were poorly investigated. 78 glioma patients confirmed by pathological and imaging methods were enrolled. Glioma patients were measured using IVIM-DWI, then related parameters such as cerebral blood flow (CBF), perfusion fraction (f), pseudo diffusivity (D*), and true diffusivity (D), were derived. Receiver operating characteristic (ROC) curves were made to calculate specificity and sensitivity. The values of CBF1, CBF3, D*1, rCBF1-2, rCBF3-2, and age in group high-grade gliomas (HGG) were significantly higher than that of in group low-grade gliomas (LGG). The values of CBF1, CBF3, rCBF1-2, rCBF3-2, D*1, and age in group IDH1 mut were significantly lower than that of in group IDH1 wt . The levels of D1 and f1 were remarkably higher in the group IDH1 mut than group IDH1 wt . rCBF1-2 had a remarkably positive correlation with CBF1 (r=0.852, p<0.001). f1 showed a markedly negative correlation with CBF1 (r= -0.306, p=0.007). IVIM-DWI presented efficacy in differentiating glioma grading and IDH1 mutation status.

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Section: Introductionmentioning

confidence: 99%

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI

Yang

Huang

et al. 2021

Aging

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“…We performed a comparison in DTI parameter between the two tumors, and found ADC was lower in soft tissue sarcoma versus vascular anomalies, in consist with previous publications. 31 Interestingly, we found FA was also lower in soft tissue sarcoma. A possible explanation is that tissue structure of soft tissue sarcoma is extremely disordered, 32 resulting in similar diffusion in all directions.…”

Section: Discussionmentioning

confidence: 56%

Readout-segmented diffusion tensor imaging for assessing sciatic nerve invasion by soft tissue tumor

Wan¹,

Wang²,

Chu³

et al. 2020

Preprint

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There are few publications regarding feasibility of readout-segmented diffusion tensor imaging (rsDTI) in assessing nerve invasion by soft tissue tumor. 64 patients with soft tissue mass in upper leg suspected of sciatic nerve invasion underwent rsDTI. Nerve invasion was confirmed in 28 cases by operation or electromyogram. The sciatic nerve was better depicted with diffusion weighted map versus b = 0 map of rsDTI. Inter-reader agreement in using rsDTI to rate nerve invasion was excellent. Sensitivity and specificity of rsDTI in identifying nerve invasion were 93% (26/28) and 92% (33/36) respectively. Apparent diffusion coefficient (ADC) was significantly higher in invaded nerves versus normal nerves (1.45 ± 0.67 × 10− 3mm2/s vs. 1.39 ± 0.46 × 10− 3mm2/s, P༜0.05). DTI derived FA was significantly lower in invaded nerves versus normal nerves (0.22 ± 0.11 vs. 0.37 ± 0.13, P༜0.05). Readout-segmented DTI was feasible in assessing sciatic nerve invasion by soft tissue tumor in selected patients.

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“…However, due to the complexity of complex biological tissues, the diffusion of water molecules tends to deviate from a Gaussian distribution, thereby limiting the effectiveness of conventional DWI. Diffusion kurtosis imaging (DKI) is an advanced non-Gaussian diffusion imaging technique that has been used to account for this deficiency and is more suitable for assessments of the tumor microenvironment [20][21][22]. Previous studies have introduced the feasibility of DKI in brain, rectal, prostate, and breast tumors.…”

Section: Ivyspringmentioning

confidence: 99%

Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis

Wang¹,

Xiao²,

Liang³

et al. 2021

J. Cancer

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Objective: To evaluate the diagnostic performance of standard diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for differentiating benign and malignant soft tissue tumors (STTs). Materials and methods: A thorough search was carried out to identify suitable studies published up to September 2020. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were calculated using bivariate mixed effects models. A subgroup analysis was also performed to explore the heterogeneity. Results: Eighteen studies investigating 1319 patients with musculoskeletal STTs (malignant, n =623; benign, n =696) were enrolled. Thirteen standard DWI studies using the apparent diffusion coefficient (ADC) showed that the pooled SEN and SPE of ADC were 0.80 (95% CI: 0.77-0.82) and 0.63 (95% CI: 0.60-0.67), respectively. The area under the curve (AUC) calculated from the SROC curve was 0.806. The subgroup analysis indicated that the percentage of myxoid malignant tumors, magnet strength, study design, and ROI placement were significant factors affecting heterogeneity. Four IVIM studies showed that the AUCs calculated from the SROC curves of the parameters ADC and D were 0.859 and 0.874, respectively. The AUCs for the IVIM parameters pseudo diffusion coefficient (D*) and perfusion fraction (f) calculated from the SROC curve were 0.736 and 0.573, respectively. Two DKI studies showed that the AUCs of the DKI parameter mean kurtosis (MK) were 0.97 and 0.89, respectively. Conclusion: The DWI-derived ADC value and the IVIM DWI-derived D value might be accurate tools for discriminating musculoskeletal STTs, especially for non-myxoid SSTs, using more than two b values, with maximal b value ranging from 600 to 800 s/mm 2 , additionally, a high-field strength (3.0 T) optimizes the diagnostic performance.

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Intravoxel incoherent motion and diffusion kurtosis imaging for discriminating soft tissue sarcoma from vascular anomalies

Cited by 18 publications

References 20 publications

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI

Readout-segmented diffusion tensor imaging for assessing sciatic nerve invasion by soft tissue tumor

Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis

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