MSCT follow-up in malignant lymphoma: comparison of manual linear measurements with semi-automated lymph node analysis for therapy response classification

Rofo. 2012 Sep;184(9):795-804. doi: 10.1055/s-0032-1312751. Epub 2012 May 22.

Abstract

Purpose: Assignment of semi-automated lymph node analysis compared to manual measurements for therapy response classification of malignant lymphoma in MSCT.

Materials and methods: MSCT scans of 63 malignant lymphoma patients before and after 2 cycles of chemotherapy (307 target lymph nodes) were evaluated. The long axis diameter (LAD), short axis diameter (SAD) and bi-dimensional WHO were determined manually and semi-automatically. The time for manual and semi-automatic segmentation was evaluated. The ref. standard response was defined as the mean relative change across all manual and semi-automatic measurements (mean manual/semi-automatic LAD, SAD, semi-automatic volume). Statistical analysis encompassed t-test and McNemar's test for clustered data.

Results: Response classification per lymph node revealed semi-automated volumetry and bi-dimensional WHO to be significantly more accurate than manual linear metric measurements. Response classification per patient based on RECIST revealed more patients to be correctly classified by semi-automatic measurements, e. g. 96.0 %/92.9 % (WHO bi-dimensional/volume) compared to 85.7/84.1 % for manual LAD and SAD, respectively (mean reduction in misclassified patients of 9.95 %). Considering the use of correction tools, the time expenditure for lymph node segmentation (29.7 ± 17.4 sec) was the same as with the manual approach (29.1 ± 14.5 sec).

Conclusion: Semi-automatically derived "lymph node volume" and "bi-dimensional WHO" significantly reduce the number of misclassified patients in the CT follow-up of malignant lymphoma by at least 10 %. However, lymph node volumetry does not outperform bi-dimensional WHO.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms*
  • Female
  • Humans
  • Lymph Nodes / diagnostic imaging*
  • Lymphoma / diagnostic imaging*
  • Male
  • Middle Aged
  • Observer Variation
  • Pattern Recognition, Automated / methods*
  • Radiographic Image Enhancement / methods
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed / methods*
  • Young Adult