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Open Access 01-12-2021 | Computed Tomography | Research

Predicting pathological complete response (pCR) after stereotactic ablative radiation therapy (SABR) of lung cancer using quantitative dynamic [¹⁸F]FDG PET and CT perfusion: a prospective exploratory clinical study

Published in: Radiation Oncology | Issue 1/2021

Abstract

Background

Stereotactic ablative radiation therapy (SABR) is effective in treating inoperable stage I non-small cell lung cancer (NSCLC), but imaging assessment of response after SABR is difficult. This prospective study aimed to develop a predictive model for true pathologic complete response (pCR) to SABR using imaging-based biomarkers from dynamic [¹⁸F]FDG-PET and CT Perfusion (CTP).

Methods

Twenty-six patients with early-stage NSCLC treated with SABR followed by surgical resection were included, as a pre-specified secondary analysis of a larger study. Dynamic [¹⁸F]FDG-PET and CTP were performed pre-SABR and 8-week post. Dynamic [¹⁸F]FDG-PET provided maximum and mean standardized uptake value (SUV) and kinetic parameters estimated using a previously developed flow-modified two-tissue compartment model while CTP measured blood flow, blood volume and vessel permeability surface product. Recursive partitioning analysis (RPA) was used to establish a predictive model with the measured PET and CTP imaging biomarkers for predicting pCR. The model was compared to current RECIST (Response Evaluation Criteria in Solid Tumours version 1.1) and PERCIST (PET Response Criteria in Solid Tumours version 1.0) criteria.

Results

RPA identified three response groups based on tumour blood volume before SABR (BV_pre-SABR) and change in SUV_max (ΔSUV_max), the thresholds being BV_pre-SABR = 9.3 mL/100 g and ΔSUV_max = − 48.9%. The highest true pCR rate of 92% was observed in the group with BV_pre-SABR < 9.3 mL/100 g and ΔSUV_max < − 48.9% after SABR while the worst was observed in the group with BV_pre-SABR ≥ 9.3 mL/100 g (0%). RPA model achieved excellent pCR prediction (Concordance: 0.92; P = 0.03). RECIST and PERCIST showed poor pCR prediction (Concordance: 0.54 and 0.58, respectively).

Conclusions

In this study, we developed a predictive model based on dynamic [¹⁸F]FDG-PET and CT Perfusion imaging that was significantly better than RECIST and PERCIST criteria to predict pCR of NSCLC to SABR. The model used BV_pre-SABR and ΔSUV_max which correlates to tumour microvessel density and cell proliferation, respectively and warrants validation with larger sample size studies.

Trial registration

MISSILE-NSCLC, NCT02136355 (ClinicalTrials.gov). Registered May 8, 2014, https://clinicaltrials.gov/ct2/show/NCT02136355

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Title: Predicting pathological complete response (pCR) after stereotactic ablative radiation therapy (SABR) of lung cancer using quantitative dynamic [18F]FDG PET and CT perfusion: a prospective exploratory clinical study
Publication date: 01-12-2021
Keywords: Computed Tomography
NSCLC
Computed Tomography
NSCLC
Positron Emission Tomography
Published in: Radiation Oncology / Issue 1/2021
Electronic ISSN: 1748-717X
DOI: https://doi.org/10.1186/s13014-021-01747-z

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Predicting pathological complete response (pCR) after stereotactic ablative radiation therapy (SABR) of lung cancer using quantitative dynamic [¹⁸F]FDG PET and CT perfusion: a prospective exploratory clinical study

Abstract

Background

Methods

Results

Conclusions

Trial registration

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Trial registration

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