Literature DB >> 20657226

Prediction of lymph node manifestations in malignant lymphoma: significant role of volumetric compared with established metric lymph node analysis in multislice computed tomography.

Michael Puesken1, Boris Buerke, Joachim Gerss, Barbara Frisch, Florian Beyer, Matthias Weckesser, Harald Seifarth, Walter Heindel, Johannes Wessling.   

Abstract

OBJECTIVE: Comparison of 2-dimensional and semiautomated 3-dimensional (3D) measurements to distinguish between benign and malignant lymph nodes in patients with malignant lymphoma.
METHODS: Whole-body positron emission tomography-computed tomography (PET-CT) was performed in 33 patients before therapy for malignant lymphoma. Two hundred fifty-seven peripheral lymph nodes (mean size, 13.4 +/- 5.4 mm) were evaluated independently by 2 radiologists, both manually and with the use of semiautomated segmentation software. Long-axis diameter (LAD), short-axis diameter (SAD), maximal 3D diameter, volume, and elongation were measured. Positron emission tomography-CT and PET-CT follow-up and/or histology served as the reference standard. Statistical analysis encompassed intraclass correlation coefficients and receiver operating characteristic curves.
RESULTS: The standard of reference revealed involvement in 116 (45%) of 257 lymph nodes. Manual and semiautomated LAD and SAD showed good correlation with intraclass coefficients of 0.85 and 0.72, respectively. Semiautomated prediction of malignant lymph nodes revealed the highest areas under the receiver operating characteristic curves for volume (0.760; 95% confidence interval [CI], 0.639-0.887) followed by SAD (0.740; 95% CI, 0.616-0.862). The findings for LAD (0.722; 95% CI, 0.588-0.855), maximal 3D diameter (0.697; 95% CI, 0.565-0.830), and lymph node elongation (0.605; 95% CI, 0.466-0.745) were significantly lower (P < 0.05).
CONCLUSIONS: Volumetric lymph node analysis is significantly superior compared with established LAD in the prediction of lymph node involvement and therefore can add to the definition of peripheral lymphoma target lesions.

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Year:  2010        PMID: 20657226     DOI: 10.1097/RCT.0b013e3181db2901

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  6 in total

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6.  Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring.

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  6 in total

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