Literature DB >> 12640556

Measuring [(18)F]FDG uptake in breast cancer during chemotherapy: comparison of analytical methods.

Nanda C Krak1, Jacobus J M van der Hoeven, Otto S Hoekstra, Jos W R Twisk, Elsken van der Wall, Adriaan A Lammertsma.   

Abstract

Over the years several analytical methods have been proposed for the measurement of glucose metabolism using fluorine-18 fluorodeoxyglucose ([(18)F]FDG) and positron emission tomography (PET). The purpose of this study was to evaluate which of these (often simplified) methods could potentially be used for clinical response monitoring studies in breast cancer. Prior to chemotherapy, dynamic [(18)F]FDG scans were performed in 20 women with locally advanced ( n=10) or metastasised ( n=10) breast cancer. Additional PET scans were acquired after 8 days ( n=8), and after one, three and six courses of chemotherapy ( n=18, 10 and 6, respectively). Non-linear regression (NLR) with the standard two tissue compartment model was used as the gold standard for measurement of [(18)F]FDG uptake and was compared with the following methods: Patlak graphical analysis, simplified kinetic method (SKM), SUV-based net influx constant ("Sadato" method), standard uptake value [normalised for weight, lean body mass (LBM) and body surface area (BSA), with and without corrections for glucose (g)], tumour to non-tumour ratio (TNT), 6P model and total lesion evaluation (TLE). Correlation coefficients between each analytical method and NLR were calculated using multilevel analysis. In addition, for the most promising methods (Patlak, SKM, SUV(LBMg) and SUV(BSAg)) it was explored whether correlation with NLR changed with different time points after the start of therapy. Three methods showed excellent correlation ( r>0.95) with NLR for the baseline scan: Patlak10-60 and Patlak10-45 ( r=0.98 and 0.97, respectively), SKM40-60 ( r=0.96) and SUV(LBMg) ( r=0.96). Good correlation was found between NLR and SUV-based net influx constant, TLE and SUV(BSAg) (0.90< r<0.95). The 6P model and TNT had the lowest correlation ( r<or=0.84). SUV was least accurate in predicting changes in [(18)F]FDG uptake over time during therapy. For all methods, correlation with NLR was significantly lower for bone metastases than for other (primary or metastatic) tumour lesions ( P<0.05). In conclusion, three methods with different degrees of complexity appear to be promising alternatives to NLR for measuring glucose metabolism in breast cancer: Patlak, SKM and SUV (normalised for LBM and with a correction for plasma glucose).

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Year:  2003        PMID: 12640556     DOI: 10.1007/s00259-003-1127-z

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  53 in total

1.  Experimental and clinical evaluation of iterative reconstruction (OSEM) in dynamic PET: quantitative characteristics and effects on kinetic modeling.

Authors:  R Boellaard; A van Lingen; A A Lammertsma
Journal:  J Nucl Med       Date:  2001-05       Impact factor: 10.057

2.  Anatomy of SUV. Standardized uptake value.

Authors:  S C Huang
Journal:  Nucl Med Biol       Date:  2000-10       Impact factor: 2.408

3.  On the use of image-derived input functions in oncological fluorine-18 fluorodeoxyglucose positron emission tomography studies.

Authors:  C J Hoekstra; O S Hoekstra; A A Lammertsma
Journal:  Eur J Nucl Med       Date:  1999-11

4.  Lesion-to-background ratio in nonattenuation-corrected whole-body FDG PET images.

Authors:  M B Imran; K Kubota; S Yamada; H Fukuda; K Yamada; T Fujiwara; M Itoh
Journal:  J Nucl Med       Date:  1998-07       Impact factor: 10.057

5.  Standardized uptake value and quantification of metabolism for breast cancer imaging with FDG and L-[1-11C]tyrosine PET.

Authors:  A C Kole; O E Nieweg; J Pruim; A M Paans; J T Plukker; H J Hoekstra; H Schraffordt Koops; W Vaalburg
Journal:  J Nucl Med       Date:  1997-05       Impact factor: 10.057

6.  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.

Authors:  H Young; R Baum; U Cremerius; K Herholz; O Hoekstra; A A Lammertsma; J Pruim; P Price
Journal:  Eur J Cancer       Date:  1999-12       Impact factor: 9.162

7.  Primary and metastatic breast carcinoma: initial clinical evaluation with PET with the radiolabeled glucose analogue 2-[F-18]-fluoro-2-deoxy-D-glucose.

Authors:  R L Wahl; R L Cody; G D Hutchins; E E Mudgett
Journal:  Radiology       Date:  1991-06       Impact factor: 11.105

8.  Enhanced FDG-PET tumor imaging with correlation-coefficient filtered influx-constant images.

Authors:  K R Zasadny; R L Wahl
Journal:  J Nucl Med       Date:  1996-02       Impact factor: 10.057

9.  Positron emission tomography using [(18)F]-fluorodeoxy-D-glucose to predict the pathologic response of breast cancer to primary chemotherapy.

Authors:  I C Smith; A E Welch; A W Hutcheon; I D Miller; S Payne; F Chilcott; S Waikar; T Whitaker; A K Ah-See; O Eremin; S D Heys; F J Gilbert; P F Sharp
Journal:  J Clin Oncol       Date:  2000-04       Impact factor: 44.544

10.  Standardized uptake values of FDG: body surface area correction is preferable to body weight correction.

Authors:  C K Kim; N C Gupta; B Chandramouli; A Alavi
Journal:  J Nucl Med       Date:  1994-01       Impact factor: 10.057

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  28 in total

Review 1.  FDG-PET in monitoring therapy of breast cancer.

Authors:  H-J Biersack; H Bender; H Palmedo
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-04-27       Impact factor: 9.236

Review 2.  Measuring response to chemotherapy in locally advanced breast cancer: methodological considerations.

Authors:  Nanda C Krak; Otto S Hoekstra; Adriaan A Lammertsma
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-04-22       Impact factor: 9.236

Review 3.  How should we analyse FDG PET studies for monitoring tumour response?

Authors:  Adriaan A Lammertsma; Corneline J Hoekstra; Giuseppe Giaccone; Otto S Hoekstra
Journal:  Eur J Nucl Med Mol Imaging       Date:  2006-07       Impact factor: 9.236

Review 4.  Importance of quantification for the analysis of PET data in oncology: review of current methods and trends for the future.

Authors:  Giampaolo Tomasi; Federico Turkheimer; Eric Aboagye
Journal:  Mol Imaging Biol       Date:  2012-04       Impact factor: 3.488

Review 5.  Dynamic whole-body PET imaging: principles, potentials and applications.

Authors:  Arman Rahmim; Martin A Lodge; Nicolas A Karakatsanis; Vladimir Y Panin; Yun Zhou; Alan McMillan; Steve Cho; Habib Zaidi; Michael E Casey; Richard L Wahl
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-09-29       Impact factor: 9.236

Review 6.  Advantages and limitations of FDG PET in the follow-up of breast cancer.

Authors:  Peter Lind; Isabel Igerc; Thomas Beyer; Peter Reinprecht; Klaus Hausegger
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-04-15       Impact factor: 9.236

7.  Comparison of different SUV-based methods for monitoring cytotoxic therapy with FDG PET.

Authors:  A Stahl; K Ott; M Schwaiger; W A Weber
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-07-15       Impact factor: 9.236

Review 8.  Methodological considerations in quantification of oncological FDG PET studies.

Authors:  Dennis Vriens; Eric P Visser; Lioe-Fee de Geus-Oei; Wim J G Oyen
Journal:  Eur J Nucl Med Mol Imaging       Date:  2009-11-20       Impact factor: 9.236

Review 9.  From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors.

Authors:  Richard L Wahl; Heather Jacene; Yvette Kasamon; Martin A Lodge
Journal:  J Nucl Med       Date:  2009-05       Impact factor: 10.057

10.  Blood flow and glucose metabolism in stage IV breast cancer: heterogeneity of response during chemotherapy.

Authors:  Nanda Krak; Jacobus van der Hoeven; Otto Hoekstra; Jos Twisk; Elsken van der Wall; Adriaan Lammertsma
Journal:  Mol Imaging Biol       Date:  2008-08-16       Impact factor: 3.488

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