Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models

Comparison of models of diffusion in Wilms' tumours and normal contralateral renal tissue

Objective

ADC (Apparent Diffusion Coefficient) derived from Diffusion-Weighted Imaging (DWI) has shown promise as a non-invasive quantitative imaging biomarker in Wilms’ tumours. However, many non-Gaussian models could be applied to DWI. This study aimed to compare the suitability of four diffusion models (mono exponential, IVIM [Intravoxel Incoherent Motion], stretched exponential, and kurtosis) in Wilms’ tumours and the unaffected contralateral kidneys.

Materials and methods

DWI data were retrospectively reviewed (110 Wilms’ tumours and 75 normal kidney datasets). The goodness of fit for each model was measured voxel-wise using Akaike Information Criteria (AIC). Mean AIC was calculated for each tumour volume (or contralateral normal kidney tissue). One-way ANOVAs with Greenhouse–Geisser correction and post hoc tests using the Bonferroni correction evaluated significant differences between AIC values; the lowest AIC indicating the optimum model.

Results

IVIM and stretched exponential provided the best fits to the Wilms’ tumour DWI data. IVIM provided the best fit for the normal kidney data. Mono exponential was the least appropriate fitting method for both Wilms’ tumour and normal kidney data.

Discussion

The diffusion weighted signal in Wilms’ tumours and normal kidney tissue does not exhibit a mono-exponential decay and is better described by non-Gaussian models of diffusion.

Clinical Study of Diffusion-Weighted Imaging in the Diagnosis of Liver Focal Lesion

Apparent diffusion coefficient (ADC), derived from diffusion-weighted magnetic resonance images (DW-MRI), measures the motion of water molecules in vivo and can be used to quantify tumor response so as to determine the best therapy approach. In this paper, our goal was to determine whether the DW-MRI can be used for qualitative and quantitative liver cancer analysis, where an automated method will be proposed for improving the accuracy of liver segmentation in DW-MRI to increase the ability of diagnosis of disease. We firstly analyzed the research status of liver cancer diagnosis, especially on the issues of liver image segmentation technology in MRI. Then, the imaging mechanism and image features of the DW-MRI were analyzed, and the initial DW-MRI slice was segmented by graph-cut algorithm. Finally, our obtained result from the liver DW-MRI image is quantitatively and qualitatively analyzed. Experimental results show that DW-MRI has a great advantage in the diagnosis, the DWI images of benign lesion group was lower than that of malignant lesion, thus DW-MRI is segmented by graph-cut algorithm can provide important additional information regarding differential diagnosis of specific liver cancer to some extend.

Correction: Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models

[This corrects the article DOI: 10.1371/journal.pone.0184197.].

Value of high resolution magnetic resonance imaging in preoperative staging of rectal cancer

AIM

To assess the value of conventional magnetic resonance imaging (MRI) combined with high resolution MRI (HR-MRI) in preoperative T and N staging of rectal cancer by comparing with pathological staging.

METHODS

The clinical data of 84 patients with primary rectal cancer who were admitted to Tianjin Haibin People's Hospital from January 2017 to October 2017 and underwent conventional MRI and HR-MRI preoperatively and pathological examination postoperatively were collected. The consistency and correlation were analyzed between preoperative T and N staging by conventional MRI and HR-MRI and pathological T and N staging. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of conventional MRI combined with HR-MRI in diagnosing T and N stages were calculated.

RESULTS

There was a strong consistency between preoperative T and N staging by conventional MRI and HR-MRI and pathological T and N staging (κ = 0.691, P = 0.000), and the correlation rate was 84.52% (71/84). The accuracy, sensitivity, and specificity of conventional MRI and HR-MRI were 93.15%, 87.44%, and 92.36% for preoperative T1 staging, 91.23%, 86.19%, and 95.42% for preoperative T2 staging, 93.15%, 87.44%, and 92.36% for preoperative T3 staging, and 95.24%, 100.00%, and 77.78% for preoperative T4 staging. The accuracy, sensitivity, and specificity of conventional MRI combined with HR-MRI for preoperative N staging were 93.15%, 87.44%, and 92.36%, respectively. Using postoperative pathological results as the "gold standard", the accuracy, specificity, and sensitivity of conventional MRI combined with HR-MRI in predicting mesorectal invasion before surgery were 93.15%, 87.44%, and 92.36%, respectively.

CONCLUSION

Conventional MRI combined with HR-MRI has high diagnostic value in preoperative evaluation of T and N stages and mesangial invasion in patients with rectal cancer, which can provide a reliable reference for the clinical planning of surgical procedures.