Literature DB >> 26907916

Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment.

Sarah A Mattonen1, David A Palma2, Carol Johnson3, Alexander V Louie4, Mark Landis5, George Rodrigues4, Ian Chan5, Roya Etemad-Rezai5, Timothy P C Yeung1, Suresh Senan6, Aaron D Ward7.   

Abstract

PURPOSE: Stereotactic ablative radiation therapy (SABR) is a guideline-specified treatment option for early-stage lung cancer. However, significant posttreatment fibrosis can occur and obfuscate the detection of local recurrence. The goal of this study was to assess physician ability to detect timely local recurrence and to compare physician performance with a radiomics tool. METHODS AND MATERIALS: Posttreatment computed tomography (CT) scans (n=182) from 45 patients treated with SABR (15 with local recurrence matched to 30 with no local recurrence) were used to measure physician and radiomic performance in assessing response. Scans were individually scored by 3 thoracic radiation oncologists and 3 thoracic radiologists, all of whom were blinded to clinical outcomes. Radiomic features were extracted from the same images. Performances of the physician assessors and the radiomics signature were compared.
RESULTS: When taking into account all CT scans during the whole follow-up period, median sensitivity for physician assessment of local recurrence was 83% (range, 67%-100%), and specificity was 75% (range, 67%-87%), with only moderate interobserver agreement (κ = 0.54) and a median time to detection of recurrence of 15.5 months. When determining the early prediction of recurrence within <6 months after SABR, physicians assessed the majority of images as benign injury/no recurrence, with a mean error of 35%, false positive rate (FPR) of 1%, and false negative rate (FNR) of 99%. At the same time point, a radiomic signature consisting of 5 image-appearance features demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.85, classification error of 24%, FPR of 24%, and FNR of 23%.
CONCLUSIONS: These results suggest that radiomics can detect early changes associated with local recurrence that are not typically considered by physicians. This decision support system could potentially allow for early salvage therapy of patients with local recurrence after SABR.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26907916     DOI: 10.1016/j.ijrobp.2015.12.369

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  45 in total

Review 1.  Towards precision medicine: from quantitative imaging to radiomics.

Authors:  U Rajendra Acharya; Yuki Hagiwara; Vidya K Sudarshan; Wai Yee Chan; Kwan Hoong Ng
Journal:  J Zhejiang Univ Sci B       Date:  2018 Jan.       Impact factor: 3.066

Review 2.  "Radio-oncomics" : The potential of radiomics in radiation oncology.

Authors:  Jan Caspar Peeken; Fridtjof Nüsslin; Stephanie E Combs
Journal:  Strahlenther Onkol       Date:  2017-07-07       Impact factor: 3.621

Review 3.  Texture analysis of medical images for radiotherapy applications.

Authors:  Elisa Scalco; Giovanna Rizzo
Journal:  Br J Radiol       Date:  2016-11-25       Impact factor: 3.039

Review 4.  Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications.

Authors:  Kaustav Bera; Vamsidhar Velcheti; Anant Madabhushi
Journal:  Am Soc Clin Oncol Educ Book       Date:  2018-05-23

Review 5.  Pulmonary imaging after stereotactic radiotherapy-does RECIST still apply?

Authors:  Sarah A Mattonen; Aaron D Ward; David A Palma
Journal:  Br J Radiol       Date:  2016-06-20       Impact factor: 3.039

Review 6.  Emerging role of MRI in radiation therapy.

Authors:  Hersh Chandarana; Hesheng Wang; R H N Tijssen; Indra J Das
Journal:  J Magn Reson Imaging       Date:  2018-09-08       Impact factor: 4.813

Review 7.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

Review 8.  Radiomics of pulmonary nodules and lung cancer.

Authors:  Ryan Wilson; Anand Devaraj
Journal:  Transl Lung Cancer Res       Date:  2017-02

9.  Treatment outcomes and patterns of radiologic appearance after hypofractionated image-guided radiotherapy delivered with helical tomotherapy (HHT) for lung tumours.

Authors:  Stefano Arcangeli; Lorenzo Falcinelli; Stefano Bracci; Alessandro Greco; Alessia Monaco; Jessica Dognini; Cinzia Chiostrini; Rita Bellavita; Cynthia Aristei; Vittorio Donato
Journal:  Br J Radiol       Date:  2017-03       Impact factor: 3.039

Review 10.  Clinical applications of textural analysis in non-small cell lung cancer.

Authors:  Iain Phillips; Mazhar Ajaz; Veni Ezhil; Vineet Prakash; Sheaka Alobaidli; Sarah J McQuaid; Christopher South; James Scuffham; Andrew Nisbet; Philip Evans
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

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