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Quantification of hematoma and perihematomal edema volumes in intracerebral hemorrhage study: Design considerations in an artificial intelligence validation (QUANTUM) study.
Ironside, Natasha; Patrie, James; Ng, Sherman; Ding, Dale; Rizvi, Tanvir; Kumar, Jeyan S; Mastorakos, Panagiotis; Hussein, Mohamed Z; Naamani, Kareem El; Abbas, Rawad; Harrison Snyder, M; Zhuang, Yan; Kearns, Kathryn N; Doan, Kevin T; Shabo, Leah M; Marfatiah, Saurabh; Roh, David; Lignelli-Dipple, Angela; Claassen, Jan; Worrall, Bradford B; Johnston, Karen C; Jabbour, Pascal; Park, Min S; Sander Connolly, E; Mukherjee, Sugoto; Southerland, Andrew M; Chen, Ching-Jen.
Afiliação
  • Ironside N; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Patrie J; Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Ng S; Department of Software Engineering, Microsoft Corporation, Redmond, WA, USA.
  • Ding D; Department of Neurosurgery, University of Louisville School of Medicine, Louisville, KY, USA.
  • Rizvi T; Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Kumar JS; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Mastorakos P; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Hussein MZ; Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Naamani KE; Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
  • Abbas R; Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
  • Harrison Snyder M; Department of Neurosurgery, Tufts Medical Center, Boston, MA, USA.
  • Zhuang Y; Department of Biomedical Engineering and Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA.
  • Kearns KN; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Doan KT; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Shabo LM; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Marfatiah S; Department of Radiology, Columbia University School of Medicine, New York, NY, USA.
  • Roh D; Department of Neurology, Columbia University School of Medicine, New York, NY, USA.
  • Lignelli-Dipple A; Department of Radiology, Columbia University School of Medicine, New York, NY, USA.
  • Claassen J; Department of Neurology, Columbia University School of Medicine, New York, NY, USA.
  • Worrall BB; Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Johnston KC; Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Jabbour P; Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Park MS; Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Sander Connolly E; Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
  • Mukherjee S; Department of Neurological Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Southerland AM; Department of Neurosurgery, Columbia University School of Medicine, New York, NY, USA.
  • Chen CJ; Department of Radiology and Medical Imaging, University of Virginia School of Medicine, Charlottesville, VA, USA.
Clin Trials ; 19(5): 534-544, 2022 10.
Article em En | MEDLINE | ID: mdl-35786006
ABSTRACT

BACKGROUND:

Hematoma and perihematomal edema volumes are important radiographic markers in spontaneous intracerebral hemorrhage. Accurate, reliable, and efficient quantification of these volumes will be paramount to their utility as measures of treatment effect in future clinical studies. Both manual and semi-automated quantification methods of hematoma and perihematomal edema volumetry are time-consuming and susceptible to inter-rater variability. Efforts are now underway to develop a fully automated algorithm that can replace them. A (QUANTUM) study to establish inter-quantification method measurement equivalency, which deviates from the traditional use of measures of agreement and a comparison hypothesis testing paradigm to indirectly infer quantification method measurement equivalence, is described in this article. The Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study aims to determine whether a fully automated quantification method and a semi-automated quantification method for quantification of hematoma and perihematomal edema volumes are equivalent to the hematoma and perihematomal edema volumes of the manual quantification method. METHODS/

DESIGN:

Hematoma and perihematomal edema volumes of supratentorial intracerebral hemorrhage on 252 computed tomography scans will be prospectively quantified in random order by six raters using the fully automated, semi-automated, and manual quantification methods. Primary outcome measures for hematoma and perihematomal edema volumes will be quantified via computed tomography scan on admission (<24 h from symptom onset) and on day 3 (72 ± 12 h from symptom onset), respectively. Equivalence hypothesis testing will be conducted to determine if the hematoma and perihematomal edema volume measurements of the fully automated and semi-automated quantification methods are within 7.5% of the hematoma and perihematomal edema volume measurements of the manual quantification reference method.

DISCUSSION:

By allowing direct equivalence hypothesis testing, the Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study offers advantages over radiology validation studies which utilize measures of agreement to indirectly infer measurement equivalence and studies which mistakenly try to infer measurement equivalence based on the failure of a comparison two-sided null hypothesis test to reach the significance level for rejection. The equivalence hypothesis testing paradigm applied to artificial intelligence application validation is relatively uncharted and warrants further investigation. The challenges encountered in the design of this study may influence future studies seeking to translate artificial intelligence medical technology into clinical practice.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Edema Encefálico Tipo de estudo: Etiology_studies / Guideline Limite: Humans Idioma: En Revista: Clin Trials Assunto da revista: MEDICINA / TERAPEUTICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Edema Encefálico Tipo de estudo: Etiology_studies / Guideline Limite: Humans Idioma: En Revista: Clin Trials Assunto da revista: MEDICINA / TERAPEUTICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos