Prognostic role of radiomics-based body composition analysis for the 1-year survival for hepatocellular carcinoma patients

BACKGROUND

Parameters of body composition have prognostic potential in patients with oncologic diseases. The aim of the present study was to analyse the prognostic potential of radiomics-based parameters of the skeletal musculature and adipose tissues in patients with advanced hepatocellular carcinoma (HCC).

METHODS

Radiomics features were extracted from a cohort of 297 HCC patients as post hoc sub-study of the SORAMIC randomized controlled trial. Patients were treated with selective internal radiation therapy (SIRT) in combination with sorafenib or with sorafenib alone yielding two groups: (1) sorafenib monotherapy (n = 147) and (2) sorafenib and SIRT (n = 150). The main outcome was 1-year survival. Segmentation of muscle tissue and adipose tissue was used to retrieve 881 features. Correlation analysis and feature cleansing yielded 292 features for each patient group and each tissue type. We combined 9 feature selection methods with 10 feature set compositions to build 90 feature sets. We used 11 classifiers to build 990 models. We subdivided the patient groups into a train and validation cohort and a test cohort, that is, one third of the patient groups.

RESULTS

We used the train and validation set to identify the best feature selection and classification model and applied it to the test set for each patient group. Classification yields for patients who underwent sorafenib monotherapy an accuracy of 75.51% and area under the curve (AUC) of 0.7576 (95% confidence interval [CI]: 0.6376-0.8776). For patients who underwent treatment with SIRT and sorafenib, results are accuracy = 78.00% and AUC = 0.8032 (95% CI: 0.6930-0.9134).

CONCLUSIONS

Parameters of radiomics-based analysis of the skeletal musculature and adipose tissue predict 1-year survival in patients with advanced HCC. The prognostic value of radiomics-based parameters was higher in patients who were treated with SIRT and sorafenib.

A novel calibration phantom for combining echocardiography with electromagnetic tracking

Ultrasound compounding techniques offer the possibility to enlarge the otherwise limited field of view of ultrasound. However, existing works mainly rely on larger ultrasound sensors. In this work, we attach electromagnetic (EM) tracking sensors to small tubular echo probes, namely an intracardiac echocardiographic (ICE) probe and a transesophageal echocardiographic (TEE) transducer. The EM tracking allows, when synchronized to the ultrasound, localization of the probes in either 5 DOF (Degrees of Freedom) or 6 DOF without line-of-sight requirement. For computation of the references between the two systems, we developed a novel customized 3D-printable phantom, which is especially convenient for tubular probes that acquire images laterally. Calibration with the phantom and 3D volume reconstruction was conducted in the Plus Toolkit. The volume reconstructor uses the captured position and orientation information to fuse 2D ultrasound slices into a compounded volume. Mean calibration error is below 2.5 mm for ICE and TEE. An accuracy evaluation of the 3D reconstruction using an object of known geometry revealed that tracking with 5 DOF provides unsatisfactory results, while the combination of 6 DOF and TEE achieved a mean absolute difference of 3.08 mm. Our calibration phantom fCal-Echo1.0 is openly available at http://perk-software.cs.queensu.ca/plus/doc/nightly/modelcatalog/.