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Computer-aided detection (CAD) and assessment of malignant lesions in the liver and lung using a novel PET/CT software tool: initial results.
Rofo. 2010 Mar; 182(3):243-7.ROFO

Abstract

PURPOSE

To determine the feasibility of a PET/CT software tool (PET computer-aided detection: PET-CAD) for automated detection and assessment of pulmonary and hepatic lesions.

MATERIALS AND METHODS

20 consecutive patients with colorectal liver metastases and 20 consecutive patients suffering from non-small cell lung cancer (NSCLC) were examined with FDG-PET/CT. In a first step the maximum standardized uptake values (SUV (max)) of non-tumorous liver and lung tissues were determined manually. This value was used as a threshold value for software-based lesion detection. The number of lesions detected, their SUV (max), and their sizes in the x, y, and z-planes, as automatically provided by PET-CAD, were compared to visual lesion detection and manual measurements on CT.

RESULTS

The sensitivity for automated detection was 96 % (86 - 99 %) for colorectal liver metastases and 90 % (70 - 99 %) for lung lesions. The positive predictive value was 80 % for liver and 68 % for lung lesions. The mean SUV (max) of all lung lesions was 9.3 and 8.8 for the liver lesions. When assessed by PET-CAD, the mean lesion sizes for liver lesions in the x, y, and z-planes were 4.3 cm, 4.6 cm, and 4.2 cm compared to 3.5 cm, 3.8 cm, and 3.6 cm for manual measurements. The mean lesion sizes of lung lesions were 7.4 cm, 7.7 cm, and 8.4 cm in the x, y, and z-planes when assessed by PET-CAD compared to 5.8 cm, 6.1 cm, and 7.1 cm when measured manually. Using manual assessment, the lesion sizes were significantly smaller in all planes (p < 0.005).

CONCLUSION

Software tools for automated lesion detection and assessment are expected to improve the clinical PET/CT workflow. Before implementation in the clinical routine, further improvements to the measurement accuracy are required.

Authors+Show Affiliations

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Germany. steffen.hahn@uk-essen.deNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

19859858

Citation

Hahn, S, et al. "Computer-aided Detection (CAD) and Assessment of Malignant Lesions in the Liver and Lung Using a Novel PET/CT Software Tool: Initial Results." RoFo : Fortschritte Auf Dem Gebiete Der Rontgenstrahlen Und Der Nuklearmedizin, vol. 182, no. 3, 2010, pp. 243-7.
Hahn S, Heusner T, Zhou X, et al. Computer-aided detection (CAD) and assessment of malignant lesions in the liver and lung using a novel PET/CT software tool: initial results. Rofo. 2010;182(3):243-7.
Hahn, S., Heusner, T., Zhou, X., Zhan, Y., Peng, Z., Hamami, M., Forsting, M., Bockisch, A., & Antoch, G. (2010). Computer-aided detection (CAD) and assessment of malignant lesions in the liver and lung using a novel PET/CT software tool: initial results. RoFo : Fortschritte Auf Dem Gebiete Der Rontgenstrahlen Und Der Nuklearmedizin, 182(3), 243-7. https://doi.org/10.1055/s-0028-1109833
Hahn S, et al. Computer-aided Detection (CAD) and Assessment of Malignant Lesions in the Liver and Lung Using a Novel PET/CT Software Tool: Initial Results. Rofo. 2010;182(3):243-7. PubMed PMID: 19859858.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Computer-aided detection (CAD) and assessment of malignant lesions in the liver and lung using a novel PET/CT software tool: initial results. AU - Hahn,S, AU - Heusner,T, AU - Zhou,X, AU - Zhan,Y, AU - Peng,Z, AU - Hamami,M, AU - Forsting,M, AU - Bockisch,A, AU - Antoch,G, Y1 - 2009/10/26/ PY - 2009/10/28/entrez PY - 2009/10/28/pubmed PY - 2010/3/23/medline SP - 243 EP - 7 JF - RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin JO - Rofo VL - 182 IS - 3 N2 - PURPOSE: To determine the feasibility of a PET/CT software tool (PET computer-aided detection: PET-CAD) for automated detection and assessment of pulmonary and hepatic lesions. MATERIALS AND METHODS: 20 consecutive patients with colorectal liver metastases and 20 consecutive patients suffering from non-small cell lung cancer (NSCLC) were examined with FDG-PET/CT. In a first step the maximum standardized uptake values (SUV (max)) of non-tumorous liver and lung tissues were determined manually. This value was used as a threshold value for software-based lesion detection. The number of lesions detected, their SUV (max), and their sizes in the x, y, and z-planes, as automatically provided by PET-CAD, were compared to visual lesion detection and manual measurements on CT. RESULTS: The sensitivity for automated detection was 96 % (86 - 99 %) for colorectal liver metastases and 90 % (70 - 99 %) for lung lesions. The positive predictive value was 80 % for liver and 68 % for lung lesions. The mean SUV (max) of all lung lesions was 9.3 and 8.8 for the liver lesions. When assessed by PET-CAD, the mean lesion sizes for liver lesions in the x, y, and z-planes were 4.3 cm, 4.6 cm, and 4.2 cm compared to 3.5 cm, 3.8 cm, and 3.6 cm for manual measurements. The mean lesion sizes of lung lesions were 7.4 cm, 7.7 cm, and 8.4 cm in the x, y, and z-planes when assessed by PET-CAD compared to 5.8 cm, 6.1 cm, and 7.1 cm when measured manually. Using manual assessment, the lesion sizes were significantly smaller in all planes (p < 0.005). CONCLUSION: Software tools for automated lesion detection and assessment are expected to improve the clinical PET/CT workflow. Before implementation in the clinical routine, further improvements to the measurement accuracy are required. SN - 1438-9010 UR - https://www.unboundmedicine.com/medline/citation/19859858/Computer_aided_detection__CAD__and_assessment_of_malignant_lesions_in_the_liver_and_lung_using_a_novel_PET/CT_software_tool:_initial_results_ L2 - http://www.thieme-connect.com/DOI/DOI?10.1055/s-0028-1109833 DB - PRIME DP - Unbound Medicine ER -