Enhancing RAPNO: the need for standardized imaging heuristics and volumetric assessment

Finally, while volumetric analysis remains optional in RAPNO, there is a growing consensus on its added value for irregular, infiltrative, or multifocal tumors.For such tumors, tools that offer reliable subregion tracking, change detection, and spatial mapping of new lesions over time are essential for consistent reporting and trial readiness, [4].A natural progression from descriptive frameworks to quantitative, validated tools that are widely accessible grounded in robust imaging standards [5], is urgently needed.We commend the authors for providing a valuable resource and believe that the next phase of RAPNO development should be driven by practical, implementationready strategies.These approaches can enhance consistency across centers, improve reproducibility of imaging assessments, and ultimately support patient-level decision making in both clinical trials and routine care.

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Publication Details

Journal
Neuroradiology
Published
2025-05-15
DOI
https://doi.org/10.1007/s00234-025-03641-x
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Enhancing RAPNO: the need for standardized imaging heuristics and volumetric assessment

Ariana Familiar, Ali Nabavizadeh
Neuroradiology
Radiomics and Machine Learning in Medical Imaging
article

Enhancing RAPNO: the need for standardized imaging heuristics and volumetric assessment

Ariana Familiar, Ali Nabavizadeh
article en

Abstract

Finally, while volumetric analysis remains optional in RAPNO, there is a growing consensus on its added value for irregular, infiltrative, or multifocal tumors.For such tumors, tools that offer reliable subregion tracking, change detection, and spatial mapping of new lesions over time are essential for consistent reporting and trial readiness, [4].A natural progression from descriptive frameworks to quantitative, validated tools that are widely accessible grounded in robust imaging standards [5], is urgently needed.We commend the authors for providing a valuable resource and believe that the next phase of RAPNO development should be driven by practical, implementationready strategies.These approaches can enhance consistency across centers, improve reproducibility of imaging assessments, and ultimately support patient-level decision making in both clinical trials and routine care.

NeuroradiologyVol. 67(6)
Children's Hospital of Philadelphia (US), Penn Center for AIDS Research (US)
Openalex Percentile: Top 84%
Radiomics and Machine Learning in Medical Imaging
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Enhancing RAPNO: the need for standardized imaging heuristics and volumetric assessment — Ariana Familiar, Ali Nabavizadeh · Neuroradiology (2025) | TGRS Research Map | TGRS