Measuring tumor burden: Comparison of automatic and manual techniques Conference Paper
| Authors: | Zhao, B.; Schwartz, L. H.; Lefkowitz, R. A.; Wang, L. |
| Editors: | Fitzpatrick, J. M.; Sonka, M. |
| Title: | Measuring tumor burden: Comparison of automatic and manual techniques |
| Conference Title: | Progress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing |
| Abstract: | The reproducible measurement of tumors is critical to assess therapy response in oncology patients. Our purpose was to develop an automated technique of measuring tumor burden and compare the results with radiologists. 15 patients with pulmonary metastases were evaluated by 3 independent, blinded radiologists. Each radiologist identified and measured the 5 largest pulmonary metastases for each patient. A computerized method for automated detection and measurement of pulmonary nodules was developed. This included detection of lung nodules using an automated local density maximum algorithm and segmentation of the nodules with an automated multi-criterion algorithm. Five largest nodules from each patient were determined using this method. The cross-product measurement was calculated as the product of the greatest diameter and greatest perpendicular for each of the nodules automatically and by each radiologist. The mean cross-product size of the pulmonary metastases was 3.6 cm 2 (range: 0.6-12.2 cm 2). All 3 Radiologists identified the identical 5 metastases as "largest" in only 5 (33%) of cases. They identified the same metastases 54/75 (72%) and at least 2 Radiologists identified the same metastases 66/75 (88%) of the time. Of the 54 metastases identified by all 3 Radiologists, the computer calculated 52 of these to be the largest. The difference in cross-product measurement was significant for 2 (p= .006, p = .003) of the 3 Radiologists. There was no significant difference in cross-product measurement for the automated measurement as compared to any of the Radiologists. Automated measurement of tumor burden may generate more reproducible measurements especially compared with the manual techniques used by one or more Radiologists. |
| Keywords: | oncology; algorithms; radiology; computerized tomography; tumors; tumor burden; patient treatment; segmentation; computed tomography (ct); image segmentation; pulmonary metastasis; computer aided diagnosis; pulmonary diseases; computer-aided detection (cad); computer aided detection (cad) |
| Journal Title | Proceedings of SPIE |
| Volume: | 5370 |
| Conference Dates: | 2004 Feb 14 |
| Conference Location: | San Diego, CA |
| ISBN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2004-05-12 |
| Start Page: | 1695 |
| End Page: | 1700 |
| Language: | English |
| DOI: | 10.1117/12.534342 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Proc SPIE Int Soc Opt Eng -- Conference code: 63695 -- Cited By (since 1996):2 -- Export Date: 16 June 2014 -- CODEN: PSISD -- 16 February 2004 through 19 February 2004 -- Source: Scopus |
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