Biomedical subjects

Yan Rolland

Publications and source records attributed to Yan Rolland.

4 recordsLinked to original sources

PubMed2003

Hepatic tumor enhancement in computed tomography: combined models of liver perfusion and dynamic imaging.

The objective of this study is to show how computational modeling can be used to increase our understanding of liver enhancement in dynamic computer tomography. It relies on two models: (1). a vascular model, based on physiological rules, is used to generate the 3D hepatic vascular network; (2). the physical process of CT acquisition allows to synthesize timed-stamped series of images, aimed at tracking the propagation of a contrast material through the vessel network and the parenchyma. The coupled models are used to simulate the enhancement of a hyper-vascular tumor at different acquisition times, showing a maximum conspicuity during the arterial phase.

Algorithms↗

PubMed2003

Fast algorithm for 3-D vascular tree modeling.

In this short paper, accelerated three-dimensional computer simulations of vascular trees development, preserving physiological and haemodynamic features, are reported. The new computation schemes deal: (i). with the geometrical optimization of each newly created bifurcation; and (ii). with the recalculation of blood pressures and radii of vessels in the whole tree. A significant decrease of the computation time is obtained by replacing the global optimization by the fast updating algorithm allowing more complex structure to be simulated. A comparison between the new algorithms and the previous one is illustrated through the hepatic arterial tree.

Algorithms↗

PubMed2003

Adjuvant intra-arterial injection of iodine-131-labeled lipiodol after resection of hepatocellular carcinoma.

The high rate of recurrence after surgical resection of hepatocellular carcinoma (HCC) is a major therapeutic challenge. Postoperative injection of 131-iodine-labeled lipiodol (131I-Lip) into the hepatic artery has been proposed as adjuvant treatment (Lau et al.). We analyzed 2 retrospective series of matched patients treated in our unit before and after addition of 131I-Lip adjuvant therapy to our standard surgical strategy. Thirty-eight patients who had undergone surgical resection of HCC after January 1999 were given adjuvant intra-arterial injection of 131I-Lip after surgery. These patients were matched with 38 other patients who had undergone surgical resection only between January 1997 and January 1999. The frequency of recurrences, disease-free rates, and overall survival rates were compared. The 2 groups were similar for clinical, biologic, or histologic parameters studied and Cancer Liver Italian Program scores. There were 15 recurrences in the group without adjuvant treatment and 9 in the group with 131I-Lip adjuvant treatment. The 1-, 2-, and 3-year disease-free survival rates (+/-95% confidence interval) were different (P <.02): 94.7% +/- 3.6%, 83.7% +/- 6.1%, and 68.4% +/- 9.7%, respectively, in the 131I-Lip group versus 73.7% +/- 7.1%, 54.3% +/- 8.2%, and 41.5% +/- 10.5% in the surgery group. The 1-, 2-, and 3-year survival rates (+/-95% confidence interval) also were different (P <.02): 94.7% +/- 3.6%, 91.7% +/- 4.6%, and 91.7% +/- 4.6%, respectively, in the 131I-Lip group versus 94.7% +/- 3.6%, 71.3% +/- 7.8%, and 49.9% +/- 10% in the surgery group. In conclusion, this retrospective analysis supports the promising contribution of postoperative injection of 131I-Lip after resection of HCC. A randomized study including more patients would be necessary to confirm its contribution to therapeutic management.

Aged↗

PubMed2003

Physiologically based modeling of 3-D vascular networks and CT scan angiography.

In this paper, a model-based approach to medical image analysis is presented. It is aimed at understanding the influence of the physiological (related to tissue) and physical (related to image modality) processes underlying the image content. This methodology is exemplified by modeling first, the liver and its vascular network, and second, the standard computed tomography (CT) scan acquisition. After a brief survey on vascular modeling literature, a new method, aimed at the generation of growing three-dimensional vascular structures perfusing the tissue, is described. A solution is proposed in order to avoid intersections among vessels belonging to arterial and/or venous trees, which are physiologically connected. Then it is shown how the propagation of contrast material leads to simulate time-dependent sequences of enhanced liver CT slices.

Algorithms↗