Diagnostic and staging impact of radiotherapy planning FDG-PET-CT in non-small-cell lung cancer

doi:10.1016/j.radonc.2011.06.030

Radiotherapy and Oncology

Volume 101, Issue 2, November 2011, Pages 284-290

https://doi.org/10.1016/j.radonc.2011.06.030 Get rights and content

Abstract

Background and purpose

To evaluate whether FDG-PET performed for radiotherapy (RT) planning can detect disease progression, compared with staging PET.

Materials and methods

Twenty-six patients with newly-diagnosed non-small-cell lung cancer underwent planning PET-CT for curative RT within 8 weeks (mean: 33 ± 14 days) of staging PET-CT. Progressive disease (PD) was defined as >25% increase in tumour size (transaxial) or volume, as delineated by SUV threshold of 2.5, or new sites (SUV > 2.5).

Results

The planning PET detected PD in 16 patients (61%), compared to four patients (15%) by CT component of PET-CT. The mean scan interval was longer in patients with progression: 40 ± 12 days, compared to 22 ± 11 days without progression. Planning PET detected PD in 13/17 (76%), 12/14 (86%) and 7/7 patients if the interval was ⩾4, 5 and 6 weeks, respectively, compared with 3/9 patients if interval <4 weeks. Planning PET detected PD in primary metabolic volume in seven patients, 20 new nodal sites in 12 new nodal stations and nine patients, five extra-nodal sites in five patients. This resulted in upstaging in nine patients (35%): stage IIIA in three, IIIB in three and IV in three.

Conclusions

RT-planning FDG-PET can provide incremental diagnostic information and may impact on staging in a significant number of patients.

Section snippets

Study population

Patients with biopsy-proven newly diagnosed NSCLC undergoing both staging and planning FDG-PET-CT and planned for curative thoracic radiotherapy were retrospectively recruited from Liverpool Hospital. Only patients with planning PET-CT performed within 8 weeks of the staging PET-CT were included for analysis, as this was thought to be a pragmatic and clinically relevant timeframe. Patients who received chemotherapy during this time were excluded from the study. Patients who underwent staging

Results

Twenty-six consecutive patients (eight female, 18 male; median age = 69 years, range 54–80 years) from October 2007 to February 2010 met the inclusion criteria and were included for analysis. Histological subgroups comprised of squamous cell carcinoma (n = 9 patients), adenocarcinoma (n = 7) and large cell carcinoma (n = 10). TNM 6 staging classification [14] comprised of four patients in stage IA, one in IB, three in IIA, two in IIB, 15 in IIIA and one in IIIB. The mean scan interval between the staging

Discussion

This study demonstrates that a dedicated FDG-PET scan performed for RT planning purpose can be a potentially powerful imaging tool to detect interval disease progression at the functional level compared to CT alone. Overall, the planning PET detected progressive disease in 16 patients (61%), compared to 4 patients (15%) by CT component of the planning PET-CT. The planning PET detected PD in primary tumour in seven patients, 20 new nodal sites in 12 new nodal stations and nine patients, three

Conflict of interest

None.

Role of funding source

The scans, collection and analysis of the data were funded internally by the Department of Nuclear Medicine and PET with no external sponsors.

Acknowledgements

We thank Andrew Chicco from the Department of Nuclear Medicine and PET for preparing the table and figures. We thank the doctors from Liverpool and Macarthur Cancer Therapy Centres, Cardiothoracic Surgery and Respiratory Departments participating at the weekly Lung Multidisciplinary Clinic for their patient referrals and advice regarding this study.

References (30)

J.T. Annema et al.
Towards a minimally invasive staging strategy in NSCLC: analysis of PET positive mediastinal lesions by EUS-FNA
Lung Cancer
(2004)
C. Greco et al.
Current status of PET/CT for tumour volume definition in radiotherapy treatment planning for non-small cell lung cancer (NSCLC)
Lung Cancer
(2007)
D. De Ruysscher et al.
PET scans in radiotherapy planning of lung cancer
Radiother Oncol
(2010)
D. De Ruysscher et al.
Selective mediastinal node irradiation based on FDG-PET scan data in patients with non-small-cell lung cancer: a prospective clinical study
Int J Radiat Oncol Biol Phys
(2005)
J.S. Belderbos et al.
Final results of a phase I/II dose escalation trial in non-small-cell lung cancer using three-dimensional conformal radiotherapy
Int J Radiat Oncol Biol Phys
(2006)
M. MacManus et al.
Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006–2007
Radiother Oncol
(2009)
I.S. Grills et al.
Clinical implications of defining the gross tumor volume with combination of CT and (18)FDG-positron emission tomography in non-small-cell lung cancer
Int J Radiat Oncol Biol Phys
(2007)
A. Grgic et al.
FDG-PET based radiotherapy planning in lung cancer: optimum breathing protocol and patient positioning–an intraindividual comparison
Int J Radiat Oncol Biol Phys
(2009)
C.F. Mountain et al.
Regional lymph node classification for lung cancer staging
Chest
(1997)
E.A. Eisenhauer et al.
New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
Eur J Cancer
(2009)

P. Giraud et al.

Evaluation on microscopic tumour extension in non-small cell lung cancer for three-dimensional conformal radiotherapy planning

Int J Radiat Oncol Biol Phys

(2000)

M. Baumann et al.

Radiotherapy of lung cancer: Technology meets biology meets multidisciplinarity

Radiother Oncol

(2009)

A. Abramyuk et al.

Is pre-therapeutical FDG-PET/CT capable to detect high risk tumor subvolumes responsible for local failure in non-small cell lung cancer?

Radiother Oncol

(2009)

A.T. Fernandes et al.

Elective nodal irradiation (ENI) vs. involved field radiotherapy (IFRT) for locally advanced non-small cell lung cancer (NSCLC): A comparative analysis of toxicities and clinical outcomes

Radiother Oncol

(2010)

H. Young et al.

Measurement of clinical and subclinical tumour response using [¹⁸F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group

Eur J Cancer

(1999)

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PET-CT planning in lung cancerDiagnostic and staging impact of radiotherapy planning FDG-PET-CT in non-small-cell lung cancer

Abstract

Background and purpose

Materials and methods

Results

Conclusions

Section snippets

Study population

Results

Discussion

Conflict of interest

Role of funding source

Acknowledgements

Lung Cancer

Lung Cancer

Radiother Oncol

Int J Radiat Oncol Biol Phys

Int J Radiat Oncol Biol Phys

Radiother Oncol

Int J Radiat Oncol Biol Phys

Int J Radiat Oncol Biol Phys

Chest

Eur J Cancer

Int J Radiat Oncol Biol Phys

Radiother Oncol

Radiother Oncol

Radiother Oncol

Eur J Cancer

PET-CT planning in lung cancer
Diagnostic and staging impact of radiotherapy planning FDG-PET-CT in non-small-cell lung cancer