Quantitative PET/CT in clinical practice: Assessing the agreement of PET tumor indices using different clinical reading platforms

Joyce Mhlanga, Alin Chirindel, Martin A. Lodge, Richard L. Wahl, Rathan M. Subramaniam

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Objective The aim of this study was to determine whether various fluorine-18-fluorodeoxyglucose PET/CT-derived parameters used in oncology vary significantly depending on the interpretation software systems used in clinical practice for multiple human solid tumors. Patients and methods A total of 120 fluorine-18-fluorodeoxyglucose PET/CT studies carried out in patients with pancreatic, lung, colorectal, and head and neck cancers were evaluated retrospectively on two different vendor software platforms including Mirada and MIMVista. Regions of interest were placed on the liver to determine the liver mean standardized uptake value at lean body mass (SUL) and on each tumor to determine the SUL max, SUL peak. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined using fixed thresholds of 50% of SUL max and SUL peak. Inter-reader, intersystem intraclass correlations, systematic bias, and variability reflected by the 95% limits of agreement, and precision were determined. Results There was excellent inter-reader reliability between the readers and the two software systems, with intraclass correlations more than 0.9 for all PET metrics, with P values less than 0.0001. The bias and SD on Bland-Altman analysis between the two software platforms for tumor SUL max, SUL peak, Max 50 MTV, and Peak 50 MTV, respectively, for Reader 1 were -1.52±2.24, 0.80±3.67, -0.80±13.01, and -4.49±20.6. For Reader 2, the biases were -1.62±1.95, 0.18±3.60, -0.27±4.64, and -3.13±8.30. The precision between the two systems was better for SUL max and SUL peak, with less variance observed, than for volume-based metrics such as Max 50 MTV and Peak 50 MTV or TLG. Conclusion Excellent correlation has been found between two tested software reading platforms for all PET-derived metrics in a dual-reader analysis. Overall, the SUL max and SUL peak values had less bias and better precision compared with the MTV and TLG.

Original languageEnglish (US)
Pages (from-to)154-160
Number of pages7
JournalNuclear Medicine Communications
Volume39
Issue number2
DOIs
StatePublished - Jan 1 2018
Externally publishedYes

Fingerprint

Tumor Burden
Reading
Software
Glycolysis
Neoplasms
Fluorodeoxyglucose F18
Liver
Head and Neck Neoplasms
Colorectal Neoplasms
Lung

Keywords

  • 18 F-FDG PET-CT
  • metabolic tumor volume
  • quantitative analysis
  • quantitative software
  • SUL max
  • SUL peak
  • total lesion glycolysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Quantitative PET/CT in clinical practice : Assessing the agreement of PET tumor indices using different clinical reading platforms. / Mhlanga, Joyce; Chirindel, Alin; Lodge, Martin A.; Wahl, Richard L.; Subramaniam, Rathan M.

In: Nuclear Medicine Communications, Vol. 39, No. 2, 01.01.2018, p. 154-160.

Research output: Contribution to journalArticle

Mhlanga, Joyce ; Chirindel, Alin ; Lodge, Martin A. ; Wahl, Richard L. ; Subramaniam, Rathan M. / Quantitative PET/CT in clinical practice : Assessing the agreement of PET tumor indices using different clinical reading platforms. In: Nuclear Medicine Communications. 2018 ; Vol. 39, No. 2. pp. 154-160.
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AU - Chirindel, Alin

AU - Lodge, Martin A.

AU - Wahl, Richard L.

AU - Subramaniam, Rathan M.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Objective The aim of this study was to determine whether various fluorine-18-fluorodeoxyglucose PET/CT-derived parameters used in oncology vary significantly depending on the interpretation software systems used in clinical practice for multiple human solid tumors. Patients and methods A total of 120 fluorine-18-fluorodeoxyglucose PET/CT studies carried out in patients with pancreatic, lung, colorectal, and head and neck cancers were evaluated retrospectively on two different vendor software platforms including Mirada and MIMVista. Regions of interest were placed on the liver to determine the liver mean standardized uptake value at lean body mass (SUL) and on each tumor to determine the SUL max, SUL peak. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined using fixed thresholds of 50% of SUL max and SUL peak. Inter-reader, intersystem intraclass correlations, systematic bias, and variability reflected by the 95% limits of agreement, and precision were determined. Results There was excellent inter-reader reliability between the readers and the two software systems, with intraclass correlations more than 0.9 for all PET metrics, with P values less than 0.0001. The bias and SD on Bland-Altman analysis between the two software platforms for tumor SUL max, SUL peak, Max 50 MTV, and Peak 50 MTV, respectively, for Reader 1 were -1.52±2.24, 0.80±3.67, -0.80±13.01, and -4.49±20.6. For Reader 2, the biases were -1.62±1.95, 0.18±3.60, -0.27±4.64, and -3.13±8.30. The precision between the two systems was better for SUL max and SUL peak, with less variance observed, than for volume-based metrics such as Max 50 MTV and Peak 50 MTV or TLG. Conclusion Excellent correlation has been found between two tested software reading platforms for all PET-derived metrics in a dual-reader analysis. Overall, the SUL max and SUL peak values had less bias and better precision compared with the MTV and TLG.

AB - Objective The aim of this study was to determine whether various fluorine-18-fluorodeoxyglucose PET/CT-derived parameters used in oncology vary significantly depending on the interpretation software systems used in clinical practice for multiple human solid tumors. Patients and methods A total of 120 fluorine-18-fluorodeoxyglucose PET/CT studies carried out in patients with pancreatic, lung, colorectal, and head and neck cancers were evaluated retrospectively on two different vendor software platforms including Mirada and MIMVista. Regions of interest were placed on the liver to determine the liver mean standardized uptake value at lean body mass (SUL) and on each tumor to determine the SUL max, SUL peak. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined using fixed thresholds of 50% of SUL max and SUL peak. Inter-reader, intersystem intraclass correlations, systematic bias, and variability reflected by the 95% limits of agreement, and precision were determined. Results There was excellent inter-reader reliability between the readers and the two software systems, with intraclass correlations more than 0.9 for all PET metrics, with P values less than 0.0001. The bias and SD on Bland-Altman analysis between the two software platforms for tumor SUL max, SUL peak, Max 50 MTV, and Peak 50 MTV, respectively, for Reader 1 were -1.52±2.24, 0.80±3.67, -0.80±13.01, and -4.49±20.6. For Reader 2, the biases were -1.62±1.95, 0.18±3.60, -0.27±4.64, and -3.13±8.30. The precision between the two systems was better for SUL max and SUL peak, with less variance observed, than for volume-based metrics such as Max 50 MTV and Peak 50 MTV or TLG. Conclusion Excellent correlation has been found between two tested software reading platforms for all PET-derived metrics in a dual-reader analysis. Overall, the SUL max and SUL peak values had less bias and better precision compared with the MTV and TLG.

KW - 18 F-FDG PET-CT

KW - metabolic tumor volume

KW - quantitative analysis

KW - quantitative software

KW - SUL max

KW - SUL peak

KW - total lesion glycolysis

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