Semi-automatic analysis of standard uptake values in serial PET/CT studies in patients with lung cancer and lymphoma

BMC Medical Imaging

Per Wollmer²  Lars Edenbrandt⁴  Sven Valind¹  Eskil Jönsson¹  Peter Höglund³  Sabine Garpered¹  John Ly¹ 

[1] Department of Clinical Sciences, Skåne University, Malmö, Sweden;Clinical Physiology and Nuclear Medicine, Diagnostic Centre, Skåne University Hospital Malmö, SE-20502 Malmö, Sweden;Competence Centre for Clin Research, Lund University, Lund, Sweden;Department of Molecular and Clinical Medicine, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden

关键词: Quantification;    Radionuclide imaging;    Image analysis;   

Others  :  1092386
DOI  :  10.1186/1471-2342-12-6

 received in 2011-08-10, accepted in 2012-04-02,  发布年份 2012

【 摘 要 】

Background

Changes in maximum standardised uptake values (SUV_max) between serial PET/CT studies are used to determine disease progression or regression in oncologic patients. To measure these changes manually can be time consuming in a clinical routine. A semi-automatic method for calculation of SUV_max in serial PET/CT studies was developed and compared to a conventional manual method. The semi-automatic method first aligns the serial PET/CT studies based on the CT images. Thereafter, the reader selects an abnormal lesion in one of the PET studies. After this manual step, the program automatically detects the corresponding lesion in the other PET study, segments the two lesions and calculates the SUV_max in both studies as well as the difference between the SUV_max values. The results of the semi-automatic analysis were compared to that of a manual SUV_max analysis using a Philips PET/CT workstation. Three readers did the SUV_max readings in both methods. Sixteen patients with lung cancer or lymphoma who had undergone two PET/CT studies were included. There were a total of 26 lesions.

Results

Linear regression analysis of changes in SUV_max show that intercepts and slopes are close to the line of identity for all readers (reader 1: intercept = 1.02, R² = 0.96; reader 2: intercept = 0.97, R² = 0.98; reader 3: intercept = 0.99, R² = 0.98). Manual and semi-automatic method agreed in all cases whether SUV_max had increased or decreased between the serial studies. The average time to measure SUV_max changes in two serial PET/CT examinations was four to five times longer for the manual method compared to the semi-automatic method for all readers (reader 1: 53.7 vs. 10.5 s; reader 2: 27.3 vs. 6.9 s; reader 3: 47.5 vs. 9.5 s; p < 0.001 for all).

Conclusions

Good agreement was shown in assessment of SUV_max changes between manual and semi-automatic method. The semi-automatic analysis was four to five times faster to perform than the manual analysis. These findings show the feasibility of using semi-automatic methods for calculation of SUV_max in clinical routine and encourage further development of programs using this type of methods.

【 授权许可】

   
2012 Ly et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

• [1]Eisenhauer EA, et al.: New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009, 45(2):228-247.
• [2]Ben-Haim S, et al.: 18F-FDG PET and PET/CT in the evaluation of cancer treatment response. J Nucl Med 2009, 50(1):88-99. Review
• [3]Hicks RJ: Role of 18F-FDG PET in assessment of response in non-small cell lung cancer. J Nucl Med 2009, 50(Suppl 1):31S-42S.
• [4]Blodgett TM, et al.: PET/CT: Form and Function. Radiology 2007, 242(2):360-385. Review
• [5]Jacene HA, et al.: Assessment of interobserver reproducibility in quantitative 18-F-FDG PET and CT measurements of tumor response to therapy. J Nucl Med 2009, 50:1760-1769.
• [6]Gao X, et al.: Computer-assisted quantitative evaluation of therapeutic responses for lymphoma using serial PET/CT imaging. Acad Radiol 2010, 17:479-488.
• [7]Tylski , et al.: Comparative assessment of methods for estimating tumor volume and standardized uptake value in 18F-FDG PET. J Nucl Med February 2010, 51(2):268-276.
• [8]Wang , et al.: Computer-assisted quantification of lung tumors in respiratory gated PET/CT images: phantom study. Med Biol Eng Comput 2010, 48:49-58.
• [9]Yan J, et al.: Marker-controlled watershed for lymphoma segmentation in sequential CT images. Med Phys 2006, 33(7):2452-2460.
• [10]Yan J, et al.: Automated matching and segmentation of lymphoma on serial CT examinations. Med Phys 2007, 34(1):55-62.
• [11]Fox , et al.: Practical approach for comparative analysis of multilesion molecular imaging using a semiautomated program for PET/CT. J Nucl Med 2011, 52:1727-1732.
• [12]Hatt , et al.: PET functional volume delineation: a robustness and repeatability study. Eur J Nucl Med Mol Imaging 2011, 38:663-672.
• [13]Cheebsumon , et al.: Impact of [18F]FDG PET imaging parameters on automatic tumour delineation: need for improved tumour delineation methodology. Eur J Nucl Med Mol Imaging 2011, 38(12):2136-2144. ISSN 1619-7070, 12/2011
• [14]Cheebsumon NO, et al.: Effects of image characteristics on performance of tumor delineation methods: a test-retest assessment. J Nucl Med 2011, 52(10):1550-1558.
• [15]Boykov Yuri, et al.: Interactive graph cuts for optimal boundary & region segmentation of objects in N- D images. Computer Vision 2001, 1:105-112.