Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
BMC Cancer
Published in: BMC Cancer 1/2016

Open Access 01-12-2016 | Research article

Reproducibility and uptake time dependency of volume-based parameters on FDG-PET for lung cancer

Authors: Tomoka Kitao, Kenji Hirata, Katsumi Shima, Takashi Hayashi, Mitsunori Sekizawa, Toshiki Takei, Wataru Ichimura, Masao Harada, Keishi Kondo, Nagara Tamaki

Published in: BMC Cancer | Issue 1/2016

Login to get access

Abstract

Background

Volume-based parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), on F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) are useful for predicting treatment response in nonsmall cell lung cancer (NSCLC). We aimed to examine intra- and inter-operator reproducibility to measure the MTV and TLG, and to estimate their dependency on the uptake time.

Methods

Fifty NSCLC patients underwent preoperative FDG-PET. After an injection of FDG, the whole body was scanned twice: at the early phase (61.4 ± 2.8 min) and delayed phase (117.7 ± 1.6 min). Two operators independently defined the tumor boundary using three different delineation methods: (1) the absolute SUV threshold method (MTVp and TLGp; p = 2.0, 2.5, 3.0, 3.5), (2) the fixed% SUVmax threshold method (MTVq% and TLGq%; q = 35, 40, 45), and (3) the adaptive region-growing method (MTVARG and TLGARG). Parameters were compared between operators and between phases.

Results

Both the intra- and inter-operator reproducibility were high for all parameters using any method (intra-class correlation > 0.99 each). MTV3.0 and MTV3.5 resulted in a significant increase from the early to delayed phase (P < 0.05 for both), whereas MTV2.0 and MTV2.5 neither increased nor decreased (P = n.s.). All of the MTVq% values significantly decreased over time (P < 0.01), whereas MTVARG and TLG with any delineation method increased significantly (P < 0.05).

Conclusions

High reproducibility of MTV and TLG was obtained by all of the methods used. MTV2.0 and MTV2.5 were the least sensitive to uptake time, and may be good alternatives when we compare images acquired with different uptake times, although applying constant uptake time is important for volume measurement.
Literature
1.
Ben-Haim S, Ell P. 18F-FDG PET and PET/CT in the evaluation of cancer treatment response. J Nucl Med. 2009;50(1):88–99.CrossRefPubMed
2.
Jhanwar YS, Straus DJ. The role of PET in lymphoma. J Nucl Med. 2006;47(8):1326–34.PubMed
3.
Israel O, Kuten A. Early detection of cancer recurrence: 18 F-FDG PET/CT can make a difference in diagnosis and patient care. J Nucl Med. 2007;48 Suppl 1:28S–35.PubMed
4.
Inoue T, Kim EE, Komaki R, Wong FC, Bassa P, Wong WH, et al. Detecting recurrent or residual lung cancer with FDG-PET. J Nucl Med. 1995;36(5):788–93.PubMed
5.
Wu H, Dimitrakopoulou-Strauss A, Heichel TO, Lehner B, Bernd L, Ewerbeck V, et al. Quantitative evaluation of skeletal tumours with dynamic FDG PET: SUV in comparison to Patlak analysis. Eur J Nucl Med. 2001;28(6):704–10.CrossRefPubMed
6.
Adams S, Baum RP, Stuckensen T, Bitter K, Hor G. Prospective comparison of 18 F-FDG PET with conventional imaging modalities (CT, MRI, US) in lymph node staging of head and neck cancer. Eur J Nucl Med. 1998;25(9):1255–60.CrossRefPubMed
7.
Thie JA. Understanding the standardized uptake value, its methods, and implications for usage. J Nucl Med. 2004;45(9):1431–4.PubMed
8.
Higashi K, Ueda Y, Arisaka Y, Sakuma T, Nambu Y, Oguchi M, et al. 18 F-FDG uptake as a biologic prognostic factor for recurrence in patients with surgically resected non-small cell lung cancer. J Nucl Med. 2002;43(1):39–45.PubMed
9.
Higashi K, Matsunari I, Ueda Y, Ikeda R, Guo J, Oguchi M, et al. Value of whole-body FDG PET in management of lung cancer. Ann Nucl Med. 2003;17(1):1–14.CrossRefPubMed
10.
Hicks RJ, Kalff V, MacManus MP, Ware RE, Hogg A, McKenzie AF, et al. (18)F-FDG PET provides high-impact and powerful prognostic stratification in staging newly diagnosed non-small cell lung cancer. J Nucl Med. 2001;42(11):1596–604.PubMed
11.
Gebhart G, Gamez C, Holmes E, Robles J, Garcia C, Cortes M, de Azambuja E, et al. 18 F-FDG PET/CT for early prediction of response to neoadjuvant lapatinib, trastuzumab, and their combination in HER2-positive breast cancer: results from Neo-ALTTO. J Nucl Med. 2013;54(11):1862–8.CrossRefPubMed
12.
Hanin FX, Lonneux M, Cornet J, Noirhomme P, Coulon C, Distexhe J, et al. Prognostic value of FDG uptake in early stage non-small cell lung cancer. Eur J Cardiothorac Surg. 2008;33(5):819–23.CrossRefPubMed
13.
Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors. J Nucl Med. 2009;50 Suppl 1:122S–50.CrossRefPubMedPubMedCentral
14.
Lodge MA, Chaudhry MA, Wahl RL. Noise considerations for PET quantification using maximum and peak standardized uptake value. J Nucl Med. 2012;53(7):1041–7.CrossRefPubMedPubMedCentral
15.
Vanderhoek M, Perlman SB, Jeraj R. Impact of different standardized uptake value measures on PET-based quantification of treatment response. J Nucl Med. 2013;54(8):1188–94.CrossRefPubMed
16.
Liao S, Penney BC, Zhang H, Suzuki K, Pu Y. Prognostic value of the quantitative metabolic volumetric measurement on 18 F-FDG PET/CT in Stage IV nonsurgical small-cell lung cancer. Acad Radiol. 2012;19(1):69–77.CrossRefPubMed
17.
Chen HH, Chiu NT, Su WC, Guo HR, Lee BF. Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer. Radiology. 2012;264(2):559–66.CrossRefPubMed
18.
Ryu IS, Kim JS, Roh JL, Lee JH, Cho KJ, Choi SH, et al. Prognostic value of preoperative metabolic tumor volume and total lesion glycolysis measured by 18 F-FDG PET/CT in salivary gland carcinomas. J Nucl Med. 2013;54(7):1032–8.CrossRefPubMed
19.
Chu KP, Murphy JD, La TH, Krakow TE, Iagaru A, Graves EE, et al. Prognostic value of metabolic tumor volume and velocity in predicting head-and-neck cancer outcomes. Int J Radiat Oncol Biol Phys. 2012;83(5):1521–7.CrossRefPubMedPubMedCentral
20.
Abgral R, Keromnes N, Robin P, Le Roux PY, Bourhis D, Palard X, et al. Prognostic value of volumetric parameters measured by 18 F-FDG PET/CT in patients with head and neck squamous cell carcinoma. Eur J Nucl Med Mol Imaging. 2014;41(4):659–67.CrossRefPubMed
21.
Kidd EA, Thomas M, Siegel BA, Dehdashti F, Grigsby PW. Changes in cervical cancer FDG uptake during chemoradiation and association with response. Int J Radiat Oncol Biol Phys. 2013;85(1):116–22.CrossRefPubMed
22.
Liao S, Lan X, Cao G, Yuan H, Zhang Y. Prognostic predictive value of total lesion glycolysis from 18 F-FDG PET/CT in post-surgical patients with epithelial ovarian cancer. Clin Nucl Med. 2013;38(9):715–20.CrossRefPubMed
23.
Roedl JB, Colen RR, Holalkere NS, Fischman AJ, Choi NC, Blake MA. Adenocarcinomas of the esophagus: response to chemoradiotherapy is associated with decrease of metabolic tumor volume as measured on PET-CT. Comparison to histopathologic and clinical response evaluation. Radiother Oncol. 2008;89(3):278–86.CrossRefPubMed
24.
Cook GJ, Yip C, Siddique M, Goh V, Chicklore S, Roy A, et al. Are pretreatment 18 F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? J Nucl Med. 2013;54(1):19–26.CrossRefPubMed
25.
Uto F, Shiba E, Onoue S, Yoshimura H, Takada M, Tsuji Y, et al. Phantom Study on Radiotherapy Planning Using PET/CT. J Radiat Res. 2010;51(2):157–64.CrossRefPubMed
26.
Li H, Thorstad WL, Biehl KJ, Laforest R, Su Y, Shoghi KI, et al. A novel PET tumor delineation method based on adaptive region-growing and dual-front active contours. Med Phys. 2008;35(8):3711–21.CrossRefPubMedPubMedCentral
27.
Van de Wiele C, Kruse V, Smeets P, Sathekge M, Maes A. Predictive and prognostic value of metabolic tumour volume and total lesion glycolysis in solid tumours. Eur J Nucl Med Mol Imaging. 2013;40(2):290–301.CrossRefPubMed
28.
Kao CH, Lin SC, Hsieh TC, Yen KY, Yang SN, Wang YC, et al. Use of pretreatment metabolic tumour volumes to predict the outcome of pharyngeal cancer treated by definitive radiotherapy. Eur J Nucl Med Mol Imaging. 2012;39(8):1297–305.CrossRefPubMed
29.
Soussan M, Chouahnia K, Maisonobe JA, Boubaya M, Eder V, Morere JF, et al. Prognostic implications of volume-based measurements on FDG PET/CT in stage III non-small-cell lung cancer after induction chemotherapy. Eur J Nucl Med Mol Imaging. 2013;40(5):668–76.CrossRefPubMed
30.
Tahari AK, Alluri KC, Quon H, Koch W, Wahl RL, Subramaniam RM. FDG PET/CT Imaging of Oropharyngeal Squamous Cell Carcinoma Characteristics of Human Papillomavirus-Positive and -Negative Tumors. Clin Nucl Med. 2014;39(3):225–31.CrossRefPubMedPubMedCentral
31.
Chen SW, Chen WTL, Wu YC, Yen KY, Hsieh TC, Lin TY, et al. Which FDG/PET parameters of the primary tumors in colon or sigmoid cancer provide the best correlation with the pathological findings? Eur J Radiol. 2013;82(9):E405–10.CrossRefPubMed
32.
Tanaka E, Kudo H. Subset-dependent relaxation in block-iterative algorithms for image reconstruction in emission tomography. Phys Med Biol. 2003;48(10):1405–22.CrossRefPubMed
33.
Shah B, Srivastava N, Hirsch AE, Mercier G, Subramaniam RM. Intra-reader reliability of FDG PET volumetric tumor parameters: effects of primary tumor size and segmentation methods. Ann Nucl Med. 2012;26(9):707–14.CrossRefPubMed
34.
Frings V, de Langen AJ, Smit EF, van Velden FH, Hoekstra OS, van Tinteren H, et al. Repeatability of metabolically active volume measurements with 18 F-FDG and 18 F-FLT PET in non-small cell lung cancer. J Nucl Med. 2010;51(12):1870–7.CrossRefPubMed
35.
Cheng G, Torigian DA, Zhuang H, Alavi A. When should we recommend use of dual time-point and delayed time-point imaging techniques in FDG PET? Eur J Nucl Med Mol Imaging. 2013;40(5):779–87.CrossRefPubMed
36.
Suga K, Kawakami Y, Hiyama A, Sugi K, Okabe K, Matsumoto T, Ueda K, Tanaka N, Matsunaga N. Dual-time point 18 F-FDG PET/CT scan for differentiation between 18 F-FDG-avid non-small cell lung cancer and benign lesions. Ann Nucl Med. 2009;23(5):427–35.CrossRefPubMed
37.
Byun BH, Kong CB, Park J, Seo Y, Lim I, Choi CW, et al. Initial metabolic tumor volume measured by 18 F-FDG PET/CT can predict the outcome of osteosarcoma of the extremities. J Nucl Med. 2013;54(10):1725–32.CrossRefPubMed
38.
Moon SH, Cho SH, Park LC, Ji JH, Sun JM, Ahn JS, et al. Metabolic response evaluated by 18 F-FDG PET/CT as a potential screening tool in identifying a subgroup of patients with advanced non-small cell lung cancer for immediate maintenance therapy after first-line chemotherapy. Eur J Nucl Med Mol Imaging. 2013;40(7):1005–13.CrossRefPubMed
39.
Usmanij EA, de Geus-Oei LF, Troost EG, Peters-Bax L, van der Heijden EH, Kaanders JH, et al. 18F-FDG PET early respons evaluation of locally advanced non-small cell lung cancer treated with concomitant chemoradiotherapy. J Nucl Med. 2013;54(9):1528–34.CrossRefPubMed
Metadata
Title
Reproducibility and uptake time dependency of volume-based parameters on FDG-PET for lung cancer
Authors
Tomoka Kitao
Kenji Hirata
Katsumi Shima
Takashi Hayashi
Mitsunori Sekizawa
Toshiki Takei
Wataru Ichimura
Masao Harada
Keishi Kondo
Nagara Tamaki
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2016
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-016-2624-3

Other articles of this Issue 1/2016

BMC Cancer 1/2016 Go to the issue

Study protocol

Protocol of a randomized controlled trial of the fear of recurrence therapy (FORT) intervention for women with breast or gynecological cancer

Research article

Associations of microbiota and toll-like receptor signaling pathway in esophageal adenocarcinoma

Case report

Dermatomyositis with anti-TIF-1γ antibodies as a presenting symptom of underlying triple-negative breast cancer: a case report

Case report

A HELLP syndrome complicates a gestational trophoblastic neoplasia in a perimenopausal woman: a case report

Research article

Chemotherapy for intracranial ependymoma in adults

Research article

The anti-tumor effect of the quinoline-3-carboxamide tasquinimod: blockade of recruitment of CD11b+ Ly6Chi cells to tumor tissue reduces tumor growth
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits