Literature DB >> 21940590

Next generation radiologic-pathologic correlation in oncology: Rad-Path 2.0.

Michael D Kuo1, Shota Yamamoto.   

Abstract

OBJECTIVE: The bedrock of radiology has been radiologic-pathologic (Rad-Path) correlation: the correlation of imaging to ex vivo gross and histopathologic findings of disease. This classical view is being challenged by our increasing understanding of the molecular basis of disease, particularly in oncology. The traditional lines in diagnostic sciences have blurred with the development of new in vitro diagnostic molecular assays and molecular imaging methods as well as the growing evidence that conventional diagnostic imaging has potential use in understanding genomic properties of disease. The purpose of this article is to make the case for a fundamental shift to the next generation of Rad-Path correlation (Rad-Path 2.0).
CONCLUSION: The future success of radiology will require not only continued technologic advances in physical and life sciences but also the convergence of previously distinct diagnostic disciplines.

Entities:  

Mesh:

Year:  2011        PMID: 21940590     DOI: 10.2214/AJR.11.7163

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  14 in total

1.  Image-Guided Biopsy in the Era of Personalized Cancer Care: Proceedings from the Society of Interventional Radiology Research Consensus Panel.

Authors:  Alda L Tam; Howard J Lim; Ignacio I Wistuba; Anobel Tamrazi; Michael D Kuo; Etay Ziv; Stephen Wong; Albert J Shih; Robert J Webster; Gregory S Fischer; Sunitha Nagrath; Suzanne E Davis; Sarah B White; Kamran Ahrar
Journal:  J Vasc Interv Radiol       Date:  2015-11-25       Impact factor: 3.464

2.  Radiogenomics of clear cell renal cell carcinoma: associations between CT imaging features and mutations.

Authors:  Christoph A Karlo; Pier Luigi Di Paolo; Joshua Chaim; A Ari Hakimi; Irina Ostrovnaya; Paul Russo; Hedvig Hricak; Robert Motzer; James J Hsieh; Oguz Akin
Journal:  Radiology       Date:  2013-10-28       Impact factor: 11.105

Review 3.  The Importance of Biopsy in the Era of Molecular Medicine.

Authors:  Etay Ziv; Jeremy C Durack; Stephen B Solomon
Journal:  Cancer J       Date:  2016 Nov/Dec       Impact factor: 3.360

4.  MRI Features of Histologically Diagnosed Supratentorial Primitive Neuroectodermal Tumors and Pineoblastomas in Correlation with Molecular Diagnoses and Outcomes: A Report from the Children's Oncology Group ACNS0332 Trial.

Authors:  A Jaju; E I Hwang; M Kool; D Capper; L Chavez; S Brabetz; C Billups; Y Li; M Fouladi; R J Packer; S M Pfister; J M Olson; L A Heier
Journal:  AJNR Am J Neuroradiol       Date:  2019-10-10       Impact factor: 3.825

5.  Germline VHL gene variant in patients with von Hippel-Lindau disease does not predict renal tumor growth.

Authors:  Faraz Farhadi; Moozhan Nikpanah; Xiaobai Li; Rolf Symons; Amir Pourmorteza; Maria J Merino; W Marston Linehan; Ashkan A Malayeri
Journal:  Abdom Radiol (NY)       Date:  2018-10

6.  Intrahepatic cholangiocarcinoma: can imaging phenotypes predict survival and tumor genetics?

Authors:  Emily A Aherne; Linda M Pak; Debra A Goldman; Mithat Gonen; William R Jarnagin; Amber L Simpson; Richard K Do
Journal:  Abdom Radiol (NY)       Date:  2018-10

7.  Multiregional Radiogenomic Assessment of Prostate Microenvironments with Multiparametric MR Imaging and DNA Whole-Exome Sequencing of Prostate Glands with Adenocarcinoma.

Authors:  Neema Jamshidi; Daniel J Margolis; Steven Raman; Jiaoti Huang; Robert E Reiter; Michael D Kuo
Journal:  Radiology       Date:  2017-04-28       Impact factor: 11.105

Review 8.  Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?

Authors:  Amani Arthur; Edward W Johnston; Jessica M Winfield; Matthew D Blackledge; Robin L Jones; Paul H Huang; Christina Messiou
Journal:  Front Oncol       Date:  2022-07-01       Impact factor: 5.738

9.  Reliable gene mutation prediction in clear cell renal cell carcinoma through multi-classifier multi-objective radiogenomics model.

Authors:  Xi Chen; Zhiguo Zhou; Raquibul Hannan; Kimberly Thomas; Ivan Pedrosa; Payal Kapur; James Brugarolas; Xuanqin Mou; Jing Wang
Journal:  Phys Med Biol       Date:  2018-10-24       Impact factor: 3.609

10.  CT-Based Radiomics Signature With Machine Learning Predicts MYCN Amplification in Pediatric Abdominal Neuroblastoma.

Authors:  Xin Chen; Haoru Wang; Kaiping Huang; Huan Liu; Hao Ding; Li Zhang; Ting Zhang; Wenqing Yu; Ling He
Journal:  Front Oncol       Date:  2021-05-24       Impact factor: 6.244

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