Comparison of MRI-based response criteria and radiomics for the prediction of early response to transarterial radioembolization in patients with hepatocellular carcinoma - 02/07/22
, Christèle Etchegaray b, Jean-Frederic Blanc c, Bruno Lapuyade a, Panteleimon Papadopoulos a, Marie-Anaïg Pey a, Laurence Bordenave d, Hervé Trillaud a, Olivier Saut b, Jean-Baptiste Pinaquy d
Bienvenue sur EM-consulte, la référence des professionnels de santé.
Article gratuit.
Connectez-vous pour en bénéficier!
Highlight |
• | Radiomics using magnetic resonance imaging data has high capabilities in the assessment of treatment response to 90yttrium transarterial radioembolization (TARE) in patients with locally advanced hepatocellular carcinoma (HCC). |
• | Four radiomics parameters (long run emphasis, minor axis length, surface area, and gray level non-uniformity on arterial phase images) were identified as predictors of early response of HCC to TARE. |
• | Long run emphasis is the best radiomics parameter for predicting early response of HCC to TARE with 100% sensitivity and 100% specificity. |
Abstract |
Purpose |
The purpose of this study was to evaluate the capabilities of radiomics using magnetic resonance imaging (MRI) data in the assessment of treatment response to 90yttrium transarterial radioembolization (TARE) in patients with locally advanced hepatocellular carcinoma (HCC) by comparison with predictions based on European Association for the Study of the Liver (EASL) criteria.
Patients and methods |
Twenty-two patients with HCC (19 men, 3 women; mean age: 66.7 ± 9.8 [SD]; age range: 37–82 years) who underwent contrast-enhanced MRI 4 ± 1 weeks before and 4 ± 4 weeks after TARE, were enrolled in this retrospective study. Regions of interest were placed manually along the contours of the treated tumor on each axial slice of arterial and portal phase images using the ITK-SNAP post-processing software. For each MRI, the Pyradiomics Python package was used to extract 107 radiomics features on both arterial and portal phases, and resulting delta-features were computed. The Mann-Whitney U test with Bonferroni correction was used to select statistically different features between responders and non-responders (i.e., those with progressive or stable disease) at 6-month follow-up, according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST). Finally, for each selected feature, univariable logistic regression with leave-one-out cross validation procedure was used to perform receiver operating characteristic (ROC) curve analysis and compare radiomics parameters with MRI variables.
Results |
According to mRECIST, 14 patients (14/22; 64%) were non-responders and 8 (8/22; 36%) were responders. Four radiomics parameters (long run emphasis, minor axis length, surface area, and gray level non-uniformity on arterial phase images) were the only predictors of early response. ROC curve analysis showed that long run emphasis was the best parameter for predicting early response, with 100% sensitivity (95% CI: 68–100) and 100% specificity (95% CI: 78–100). EASL morphologic criteria yielded 75% sensitivity (95% CI: 41–96%) and 93% specificity (95% CI: 69–100%).
Conclusion |
Radiomics allows identify marked differences between responders and non-responders, and could aid in the prediction of early treatment response following TARE in patients with HCC.
Le texte complet de cet article est disponible en PDF.Keywords : Hepatocellular carcinoma, Selective internal radiation therapy (SIRT), Treatment response, Magnetic resonance imaging, Radiomics
List of abbreviation : 99Y, 99mTC-MAA, AUC, CT, EASL, HCC, LI-RADS, LR-TR, mRECIST, MRI, RECIST, ROC, TARE
Plan
Vol 103 - N° 7-8
P. 360-366 - juillet 2022 Retour au numéro
Article précédent
- A deep learning tool without muscle-by-muscle grading to differentiate myositis from facio-scapulo-humeral dystrophy using MRI
- Vincent Fabry, Franck Mamalet, Anne Laforet, Mikael Capelle, Blandine Acket, Coralie Sengenes, Pascal Cintas, Marie Faruch-Bilfeld
- Percutaneous screw fixation of pelvic bone metastases using cone-beam computed tomography navigation
- Francois H. Cornelis, Leo Razakamanantsoa, Mohamed Ben Ammar, Milan Najdawi, Sanaa El-Mouhadi, Francois Gardavaud, Matthias Barral
Bienvenue sur EM-consulte, la référence des professionnels de santé.