POSTER SECTIONS Coverpage Aims and objectives Methods and materials Results Conclusion Personal information References

ECR 2016 / C-2178

Diffusion imaging of rectal cancer: comparison between four different models

This poster is published under an open license. Please read the disclaimer for further details.

Congress:

ECR 2016

Poster Number:

C-2178

Type:

Scientific Exhibit

Keywords:

Abdomen, Colon, Gastrointestinal tract, MR-Diffusion/Perfusion, Technical aspects, Cancer

Authors:

G. C. Manikis¹, K. Marias¹, K. Nikiforaki¹, D. M. J. Lambregts², M. V. Heeswijk², R. G. H. Beets-Tan², N. Papanikolaou³; ¹Heraklion/GR, ²Maastricht/NL, ³Stockholm/SE

DOI:

10.1594/ecr2016/C-2178

DOI-Link:

https://dx.doi.org/10.1594/ecr2016/C-2178

Fig. 1: Adjusted R2 maps for mono exponential Gaussian (upper left), bi-exponential...

Fig. 2: Boxplots of adjusted R-square for each model and patient separately

Fig. 3: Overall boxplot of adjusted R-square for each model

Fig. 4: Overall boxplot of Root Mean Square Error (RMSE) for each model

Fig. 5: Overall boxplot of Error Sum of Squares (SSE) for each model

Fig. 6: Overall boxplot of corrected Akaike Information Criterion (AICc) for each model

Table 1: Mean, standard deviation (sd) and square error (se) of adjusted R-square for...

Table 2: Mean, standard deviation (sd) and square error (se) of Root Mean Square Error...

Table 3: Mean, standard deviation (sd) and square error (se) of Error Sum of Squares...

Table 4: Mean, standard deviation (sd) and square error (se) of corrected Akaike...

Table 5: Mean, standard deviation (sd) and square error (se) of the diffusion...

Table 6: Mean, standard deviation (sd) and square error (se) of the micro-perfusion...

$Table 7: Mean, standard deviation (sd) and square error (se) of the perfusion fraction (f) for each bi-exponential model References: Computational Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Greece$

Table 7: Mean, standard deviation (sd) and square error (se) of the perfusion fraction...

Aims and objectives

The aim of the current poster was to compare four diffusion models including mono-exponential and bi-exponential both Gaussian and non-Gaussian in patients with rectal adenocarcinoma. Gaussian mono-exponential model associated to the Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM) model [1], non-Gaussian mono-exponential Kurtosis model [2], and extended non-Gaussian bi-exponential model [3] were used for comparison.

Methods and materials

Sixteen consecutive patients with rectal adenocarcinoma underwent MRI examination before chemoradiation therapy or surgery. Diffusion weighted imaging (DWI) using a Spin-Echo Echo Planar Imaging sequence was acquired on a Philips Ingenia 1.5T system utilizing 6 b-values (0, 25, 50, 100, 500, 1000) assymetrically sampled to acquire more data on the low b-value area were microperfusion effects are more evident. Mono-exponential and bi-exponential diffusion models were used both in Gaussian and non-Gaussian form to fit the data and extract the relevant diffusion imaging biomarkers. ADC was...

Results

Diffusion data were post processed by an in house software (ICS, FORTH) which is able to produce pixel based parametric maps of a number of model related parameters. All pixel values belonging to the tumor, as marked by an expert radiologist, were used as input for signal intensity curves as a function of b-value. Model specific curves were grafically overlaid on the data in order to gain insight into each model performance qualitatively. For visual and quantitative evaluation of each approach, statisticalmetrics permitted direct comparison...

Conclusion

Non-Gaussian diffusion models proved to be more accurate to Gaussian models in fitting rectal cancer multi b-value diffusion data, possiblydue to their sensitivity to depict not only microperfusion effects but also increased tumor heterogeneity.

Personal information

References

[1] D. Le Bihan, E. Breton, D. Lallemand, M.-L. Aubin, J. Vignaud, and M. Laval-Jeantet, “Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging,” Radiology, vol. 168, no. 2, pp. 497–505, 1988. [2] J. H. Jensen and J. a. Helpern, “MRI quantification of non-Gaussian water diffusion by kurtosis analysis,” NMR Biomed., vol. 23, no. 7, pp. 698–710, 2010. [3] Y. Lu, J. F. a Jansen, Y. Mazaheri, H. E. Stambuk, J. a. Koutcher, and A. Shukla-Dave, “Extension of the intravoxel incoherent motion model...