Arnaud Hocquelet1, Hervé Trillaud2, Nora Frulio2, Panteleimon Papadopoulos2, Pierre Balageas2, Cécile Salut2, Marie Meyer2, Jean-Frédéric Blanc3, Michel Montaudon4, Baudouin Denis de Senneville5. 1. Department of Diagnostic and Interventional Imaging, Hôpital Saint-André, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France. Electronic address: arnaud.hocquelet@gmail.com. 2. Department of Diagnostic and Interventional Imaging, Hôpital Saint-André, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France. 3. Department of HepatoGastroenterology and Digestive Oncology, Hôpital Saint-André, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France. 4. Department of Diagnostic and Interventional Imaging, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire de Bordeaux, Pessac, France. 5. Institut de Mathématiques de Bordeaux, Unité Mixte de Recherche 5251, Centre National de Recherche Scientifique/Universitaire de Bordeaux, Talence, France.
Abstract
PURPOSE: To propose a postprocessing technique that measures tumor surface with insufficient ablative margins (≤ 5 mm) on magnetic resonance (MR) imaging to predict local tumor progression (LTP) following radiofrequency (RF) ablation. MATERIALS AND METHODS: A diagnostic method is proposed based on measurement of tumor surface with a margin ≤ 5 mm on MR imaging. The postprocessing technique includes fully automatic registration of pre- and post-RF ablation MR imaging, a semiautomatic segmentation of pre-RF ablation tumor and post-RF ablation volume, and a subsequent calculation of the three-dimensional exposed tumor surface area. The ability to use this surface margin ≤ 5 mm to predict local recurrence at 2 years was then tested on 16 patients with cirrhosis who were treated by RF ablation with a margin ≤ 5 mm in 2012: eight with LTP matched according to tumor size and number and α-fetoprotein level versus eight without local recurrence. RESULTS: The error of estimated tumor surface with a margin ≤ 5 mm was less than 12%. Results of a log-rank test showed that patients with a tumor surface area > 425 mm(2) had a 2-year LTP rate of 77.5%, compared with 25% for patients with a tumor surface area ≤ 425 mm(2) (P = .018). CONCLUSIONS: This proof-of-concept study proposes an accurate and reliable postprocessing technique to estimate tumor surface with insufficient ablative margins, and underscores the potential usefulness of tumor surface with a margin ≤ 5 mm to stratify patients with HCC treated by RF ablation according to their risk of LTP.
PURPOSE: To propose a postprocessing technique that measures tumor surface with insufficient ablative margins (≤ 5 mm) on magnetic resonance (MR) imaging to predict local tumor progression (LTP) following radiofrequency (RF) ablation. MATERIALS AND METHODS: A diagnostic method is proposed based on measurement of tumor surface with a margin ≤ 5 mm on MR imaging. The postprocessing technique includes fully automatic registration of pre- and post-RF ablation MR imaging, a semiautomatic segmentation of pre-RF ablation tumor and post-RF ablation volume, and a subsequent calculation of the three-dimensional exposed tumor surface area. The ability to use this surface margin ≤ 5 mm to predict local recurrence at 2 years was then tested on 16 patients with cirrhosis who were treated by RF ablation with a margin ≤ 5 mm in 2012: eight with LTP matched according to tumor size and number and α-fetoprotein level versus eight without local recurrence. RESULTS: The error of estimated tumor surface with a margin ≤ 5 mm was less than 12%. Results of a log-rank test showed that patients with a tumor surface area > 425 mm(2) had a 2-year LTP rate of 77.5%, compared with 25% for patients with a tumor surface area ≤ 425 mm(2) (P = .018). CONCLUSIONS: This proof-of-concept study proposes an accurate and reliable postprocessing technique to estimate tumor surface with insufficient ablative margins, and underscores the potential usefulness of tumor surface with a margin ≤ 5 mm to stratify patients with HCC treated by RF ablation according to their risk of LTP.
Authors: Elena A Kaye; Francois H Cornelis; Elena N Petre; Neelam Tyagi; Waleed Shady; Weiji Shi; Zhigang Zhang; Stephen B Solomon; Constantinos T Sofocleous; Jeremy C Durack Journal: Eur Radiol Date: 2018-11-06 Impact factor: 5.315
Authors: Paul B Shyn; Alan J Cubre; Paul J Catalano; Leslie K Lee; Hyewon Hyun; Kemal Tuncali; Julia G Seol; Vincent M Levesque; Victor H Gerbaudo; Tina Kapur; Ryan T Chao; Stuart G Silverman Journal: Abdom Radiol (NY) Date: 2021-02-19
Authors: D Putzer; P Schullian; E Braunwarth; M Fodor; F Primavesi; B Cardini; T Resch; R Oberhuber; M Maglione; C Margreiter; S Schneeberger; S Stättner; D Öfner-Velano; W Jaschke; R J Bale Journal: Eur Surg Date: 2018-04-13 Impact factor: 0.953