Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Huang, Yanxiong; Chen, Tianwu; Zhang, Xiaoming; Zeng, Nan-lin; Li, Rui; Tang, Y S; Fan, Chen; Chen, Yanli

doi:10.1259/bjr.20170421

Cited by 13 publications

(12 citation statements)

References 43 publications

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“…Nevertheless, perfusion fraction might add relevant information regarding tumor aggressiveness or treatment response. 31,32 Morphological imaging features demonstrated limited diagnostic accuracy for differentiation of malignant and benign PNSTs with sensitivities of 18-94% and specificities of 18-82%, similar to previous observations. 13 Malignant PNSTs were significantly associated with distinct morphological features, such as irregular shape, ill-defined margins, intratumoral heterogeneity, and peritumoral edema.…”

Section: Well Et Al Diffusion-weighted Imaging In Nf1supporting

confidence: 87%

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

et al. 2018

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Background. We sought to determine the value of diffusion-weighted (DW) magnetic resonance imaging (MRI) for characterization of benign and malignant peripheral nerve sheath tumors (PNSTs) in patients with neurofibromatosis type 1 (NF1). Methods. Twenty-six patients with NF1 and suspicion of malignant transformation of PNSTs were prospectively enrolled and underwent DW MRI at 3T. For a set of benign (n = 55) and malignant (n = 12) PNSTs, functional MRI parameters were derived from both biexponential intravoxel incoherent motion (diffusion coefficient D and perfusion fraction f) and monoexponential data analysis (apparent diffusion coefficients [ADCs]). A panel of morphological MRI features was evaluated using T1-and T2-weighted imaging. Mann-Whitney U-test, Fisher's exact test, and receiver operating characteristic (ROC) analyses were applied to assess the diagnostic accuracy of quantitative and qualitative MRI. Cohen's kappa was used to determine interrater reliability. Results. Malignant PNSTs demonstrated significantly lower diffusivity (P < 0.0001) compared with benign PNSTs. The perfusion fraction f was significantly higher in malignant PNSTs (P < 0.001). In ROC analysis, functional MRI parameters showed high diagnostic accuracy for differentiation of PNSTs (eg, ADC mean, 92% sensitivity with 98% specificity, AUC 0.98; D mean, 92% sensitivity with 98% specificity, AUC 0.98). By contrast, morphological imaging features had only limited sensitivity (18-94%) and specificity (18-82%) for identification of malignancy. Interrater reliability was higher for monoexponential data analysis. Conclusion. DW imaging shows better diagnostic performance than morphological features and allows accurate differentiation of benign and malignant peripheral nerve sheath tumors in NF1. Key Points 1. DWI allows sensitive and specific identification of malignancy in NF1. 2. Morphological features have limited accuracy for identifying malignant transformation. Well et al. Diffusion-weighted imaging in NF1 Neuro-Oncology Keywords diffusion-weighted imaging | intravoxel incoherent motion analysis | morphological features | neurofibromatosis type 1 | peripheral nerve sheath tumor

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Section: Well Et Al Diffusion-weighted Imaging In Nf1supporting

confidence: 87%

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

et al. 2018

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“…But the analysis of signal intensities averages over an ROI approach and segmented fitting method combined with the reasonable b value distributions could lead to considerable improvement in accuracy (17,45). Finally, esophageal peristalsis or glandular secretion can cause signal decay, which may be difficult to differentiate from perfusion effects (15). Though we ask the patient not to swallow during the examination and use the respiratory-triggered and saturation suppression technique, these issues need to be considered when interpreting our findings.…”

Section: Discussionmentioning

confidence: 99%

“…However, few studies (12)(13)(14) have been performed regarding the diagnosis and pathological grade of esophageal carcinoma with MRI, because conventional MRI is limited in its ability to resolve the early esophageal cancer. As the constant progress achieved in this field, IVIM-DWI demonstrated the potential value for the diagnosis and pathological grade of esophageal carcinoma (12,14,15).…”

Section: Introductionmentioning

confidence: 99%

Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model

et al. 2021

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PurposeTo compare the diagnostic efficiency of the mono-exponential model and bi-exponential model deriving from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating the pathological grade of esophageal squamous cell carcinoma (ESCC).MethodsFifty-four patients with ESCC were divided into three groups of poorly-differentiated (PD), moderately-differentiated (MD), and well-differentiated (WD), and underwent the IVIM-DWI scan. Mono-exponential (Dmono, D*mono, and fmono) and bi-exponential fit parameters (Dbi, D*bi, and fbi) were calculated using the IVIM data for the tumors. Mean parameter values of three groups were compared using a one-way ANOVA followed by post hoc tests. The receiver operating characteristic curve was drawn for differentiating pathological grade of ESCC. Correlations between pathological grades and IVIM parameters were analyzed.ResultsThere were significant differences in fmono and fbi among the PD, MD and WD ESCC groups (all p<0.05). The fmono were 0.32 ± 0.07, 0.23 ± 0.08, and 0.16 ± 0.05, respectively, and the fbi were 0.35 ± 0.08, 0.26 ± 0.10, and 0.18 ± 0.07, respectively. There was a significant difference in the Dmono between the WD and the PD group (1.48 ± 0.51* 10-3 mm2/s versus 1.05 ± 0.44*10-3 mm2/s, p<0.05), but there was no significant difference between the WD and MD groups, MD and PD groups (all p>0.05). The D*mono, Dbi, and D*bi showed no significant difference among the three groups (all p>0.05). The area under the curve (AUC) of Dmono, fmono and fbi in differentiating WD from PD ESCC were 0.764, 0.961 and 0.932, and the sensitivity and specificity were 92.9% and 60%, 92.9% and 90%, 85.7% and 100%, respectively. The AUC of fmono and fbi in differentiating MD from PD ESCC were 0.839 and 0.757, and the sensitivity and specificity were 78.6% and 80%, 85.7% and 70%, respectively. The AUC of fmono and fbi in differentiating MD from WD ESCC were 0.746 and 0.740, and the sensitivity and specificity were 65% and 85%, 80% and 60%, respectively. The pathologically differentiated grade was correlated with all IVIM parameters (all p<0.05).ConclusionsThe mono-exponential IVIM model is superior to the bi-exponential IVIM model in differentiating pathological grades of ESCC, which may be a promising imaging method to predict pathological grades of ESCC.

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“…Indeed, malignant tumors have a lower internal regulation. Previous studies related to the mean of diffusion have emphasized the higher restricted diffusion, more compact onto cells, and in some cases it is an indirect sign of malignancy (19,20). Little has been known about the role of the SD on tissue diffusion (21).…”

Section: Discussionmentioning

confidence: 99%

Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

et al. 2019

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Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.

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Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Abstract: IVIM derived parameters can be associated with T-stage of oesophageal SCC. Advances in knowledge (1) IVIM-derived parameters are negatively correlated with stage of oesophageal SCC. (2) Among IVIM-derived parameters, microvascular volume fraction helps detect and stage oesophageal SCC.

Cited by 13 publications

References 43 publications

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging

Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model

Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

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