Quantitative imaging (QI) in computed tomography (CT) encompasses a range of methods, modalities, and techniques including but not limited to voxelwise CT volumetry, histogram analysis, texture analysis, and dual-energy or spectral CT material decomposition. In subspecialties such as neuroradiology, breast imaging, thoracic radiology, and cancer imaging, quantitative methods have experienced a Cambrian explosion over the past two decades. Initial painstaking clinical validation using manual approaches ultimately serves as the bedrock for rapid computer vision-based methods that can be applied at the point of care for personalized, objective, and granular prognostication and decision support with high accuracy and decreased turn-around times. We are fast approaching a hockey-stick inflection point in the availability of automated deployable commercial computer-aided detection tools that provide high-trust quantitative analysis of stroke, tumors, lung nodules, and lung infiltrates among other examples.
Trauma represents a radiology vertical that has remained in a kind of research torpor or splendid isolation. It is not an exaggeration to say that with respect to advanced image processing, this -subspeciality within ER radiology is empirically decades behind progress in other imaging domains with respect to QI research. Additionally, trauma is skewed toward underserved populations and new equipment such as dual or multi-energy scanners tend to be latecomers to the trauma bay. Practitioners explicitly focused on trauma imaging are few, scattered across a small and spread-out archipelago of trauma centers with sufficient yearly patient admissions to justify trauma imaging faculty. Peak trauma volumes occur in the evenings and nights and the burden has been shifted toward attendings due to the exigencies of the current medicolegal climate. The challenges of 24/7 schedules are hardly conducive to meaningful scientific progress in QI, given the time commitment, personnel, and resources required to generate data and secure funding. Consequently, the research infrastructure and technical expertise in QI have not kept up with the times. However, in the long term, we hope to help jumpstart an active, prolific, impactful, and supportive research community in quantitative trauma imaging.
With a large number of computer-aided detection tools in the development and regulatory pipeline, the radiology value proposition will be upended toward quality over volume. This creates both new challenges and new opportunities to refine our collective role as the doctor’s doctor who is able to synthesize injury patterns and anticipate the surgeon’s management decisions. In this way, the radiologist moves into a more central and collaborative role as a valued member in the multidisciplinary care of trauma patients.
This Research Topic welcomes submissions in the field of trauma radiology. Themes solicited include but are not limited to:
• CT volumetry
• Quantitative dual and multi-energy CT
• Texture analysis and radiomics
• Computer-aided detection tools
• Surgical management principles with emphasis on CT
This will empower readers to add value to the multidisciplinary trauma team and contribute to improved outcomes for our patients.
Quantitative imaging (QI) in computed tomography (CT) encompasses a range of methods, modalities, and techniques including but not limited to voxelwise CT volumetry, histogram analysis, texture analysis, and dual-energy or spectral CT material decomposition. In subspecialties such as neuroradiology, breast imaging, thoracic radiology, and cancer imaging, quantitative methods have experienced a Cambrian explosion over the past two decades. Initial painstaking clinical validation using manual approaches ultimately serves as the bedrock for rapid computer vision-based methods that can be applied at the point of care for personalized, objective, and granular prognostication and decision support with high accuracy and decreased turn-around times. We are fast approaching a hockey-stick inflection point in the availability of automated deployable commercial computer-aided detection tools that provide high-trust quantitative analysis of stroke, tumors, lung nodules, and lung infiltrates among other examples.
Trauma represents a radiology vertical that has remained in a kind of research torpor or splendid isolation. It is not an exaggeration to say that with respect to advanced image processing, this -subspeciality within ER radiology is empirically decades behind progress in other imaging domains with respect to QI research. Additionally, trauma is skewed toward underserved populations and new equipment such as dual or multi-energy scanners tend to be latecomers to the trauma bay. Practitioners explicitly focused on trauma imaging are few, scattered across a small and spread-out archipelago of trauma centers with sufficient yearly patient admissions to justify trauma imaging faculty. Peak trauma volumes occur in the evenings and nights and the burden has been shifted toward attendings due to the exigencies of the current medicolegal climate. The challenges of 24/7 schedules are hardly conducive to meaningful scientific progress in QI, given the time commitment, personnel, and resources required to generate data and secure funding. Consequently, the research infrastructure and technical expertise in QI have not kept up with the times. However, in the long term, we hope to help jumpstart an active, prolific, impactful, and supportive research community in quantitative trauma imaging.
With a large number of computer-aided detection tools in the development and regulatory pipeline, the radiology value proposition will be upended toward quality over volume. This creates both new challenges and new opportunities to refine our collective role as the doctor’s doctor who is able to synthesize injury patterns and anticipate the surgeon’s management decisions. In this way, the radiologist moves into a more central and collaborative role as a valued member in the multidisciplinary care of trauma patients.
This Research Topic welcomes submissions in the field of trauma radiology. Themes solicited include but are not limited to:
• CT volumetry
• Quantitative dual and multi-energy CT
• Texture analysis and radiomics
• Computer-aided detection tools
• Surgical management principles with emphasis on CT
This will empower readers to add value to the multidisciplinary trauma team and contribute to improved outcomes for our patients.
