4.6 Article

Tumor Size Measurements for Predicting Hodgkin's and Non-Hodgkin's Lymphoma Response to Treatment

期刊

METABOLITES
卷 12, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/metabo12040285

关键词

metabolic tumor size; metabolic volume; PET/CT; lymphoma; image segmentation

资金

  1. European Union (European Social Fund -ESF)
  2. Greek national funds through the Operational Program Education and Lifelong Learning of the National Strategic Reference Framework (NSRF) -Research Funding Program: ARCHIMEDES III. Investing in Knowledge Society through the European Social Fund

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This study investigated the value of tumor measurements in predicting treatment outcomes for Hodgkin's and Non-Hodgkin's lymphomas. Results showed that while SUVmax was the strongest prognostic indicator, automated metabolic tumor volume measurements and expert's metabolic maximum diameter measurements also provided valuable insights. Anatomic tumor measurements had poor prognostic value. The study suggests a paradigm shift towards identifying robust prognostic markers in PET/CT with the use of radiomics.
The purpose of this study was to investigate the value of tumor size measurements as prognostic indicators of treatment outcome of Hodgkin's and Non-Hodgkin's lymphomas. F-18-FDG PET/CT exams before and after treatment were analyzed and metabolic and anatomic parameters- tumor maximum diameter, tumor maximum area, tumor volume, and maximum standardized uptake value (SUVmax)-were determined manually by an expert and automatically by a computer algorithm on PET and CT images. Results showed that the computer algorithm measurements did not correlate well with the expert's standard maximum tumor diameter measurements but yielded better three dimensional metrics that could have clinical value. SUVmax was the strongest prognostic indicator of the clinical outcome after treatment, followed by the automated metabolic tumor volume measurements and the expert's metabolic maximum diameter measurements. Anatomic tumor measurements had poor prognostic value. Metabolic volume measurements, although promising, did not significantly surpass current standard of practice, but automated measurements offered a significant advantage in terms of time and effort and minimized biases and variances in the PET measurements. Overall, considering the limited value of tumor size in predicting response to treatment, a paradigm shift seems necessary in order to identify robust prognostic markers in PET/CT; radiomics, namely combinations of anatomy, metabolism, and imaging, may be an option.

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