3D Assessment of Lymph Nodes vs. RECIST 1.1

Competence Center Medical Imaging, Fraunhofer IGD, Fraunhoferstrasse 5, 64283 Darmstadt, Germany.
Academic radiology (Impact Factor: 1.75). 03/2011; 18(3):391-4. DOI: 10.1016/j.acra.2010.11.010
Source: PubMed


In today's clinical practice, the size of lymph nodes is assessed by measuring the long and the short axis in the axial plane. This study compares this approach with three-dimensional (3D) assessment.
For a representative set of 49 lymph nodes, the axes in the axial plane have been measured and a 3D model has been created manually. Based on the 3D model, the real axial long and short axis as well as the three 3D axes and the volume have been computed and compared to the measured axial axes.
The inter-observer variability is around 10% for all measured lengths and almost 16% for the computed volume. The average relative error of the measured long (short) axial axis is 9.73% (24.57%) to the computed axial axis and 25.05% (19.97%) to the computed 3D axis, respectively. The product of the axial long axis and the square of the axial short axis provides best correlation to the volume.
This study confirms Response Evaluation Criteria In Solid Tumours 1.1 that measuring the short axis is more robust than measuring the long axis because of less impact of the node's spatial orientation. Nonetheless it is shown that considering both axes is a better prognostic factor for the volume than measuring the short axis only.

Download full-text


Available from: Ramon Colomer, Oct 01, 2015
114 Reads
  • Source
    • "Lymph node involvement determines cancer staging. Nodal stage also affects the patient survival rate and the time interval to development of distant metastasis (4, 7, 22, 23). Therefore, an evaluation of the lymph node stage is important to precisely assess the cancer burden and to correlate the tumor burden with the tumor stage. "
    [Show abstract] [Hide abstract]
    ABSTRACT: To compare the diagnostic performance in evaluating the response of neoadjuvant chemotherapy (NAC), between the response evaluation criteria in solid tumor (RECIST) 1.0 and RECIST 1.1, on magnetic resonance imaging (MRI) for advance breast cancer patients. Breast cancer patients, who underwent NAC between 2005 and 2010, were included. Both prechemotherapy and post-chemotherapy MRIs were performed within 1-4 weeks before and after NAC. Only the patients with subsequent surgery were included. The response to NAC was assessed by using RECIST 1.0 and RECIST 1.1. Patients with a complete or partial response on MRI were considered as responders, and those with stable or progressive disease were considered as non-responders. Tumor necrosis > 50% on pathology was defined as responders and necrosis < 50% was defined as non-responders. The diagnostic accuracy of both RECIST 1.0 and RECIST 1.1 was analyzed and compared by receiver operating characteristic curve analysis. Seventy-nine females (mean age 51.0 ± 9.3 years) were included. Pathology showed 45 responders and 34 non-responders. There were 49 responders and 30 non-responders on RECIST 1.0, and in 55 patients, RECIST 1.0 results agreed with pathologic results (69.6%). RECIST 1.1 showed 52 responders and 27 non-responders. In 60 patients, RECIST 1.1 results were in accordance with pathology results (75.9%). The area under the ROC curve was 0.809 for RECIST 1.0 and 0.853 for RECIST 1.1. RECIST 1.1 showed better diagnostic performance than RECIST 1.0, although there was no statistically significant difference between the two.
    Korean journal of radiology: official journal of the Korean Radiological Society 01/2013; 14(1):13-20. DOI:10.3348/kjr.2013.14.1.13 · 1.57 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Therapy response evaluation in oncological patient care requires reproducible and accurate image evaluation. Today, common standard in measurement of tumour growth or shrinkage is one-dimensional RECIST 1.1. A proposed alternative method for therapy monitoring is computer aided volumetric analysis. In lung metastases volumetry proved high reliability and accuracy in experimental studies. High reliability and accuracy of volumetry in lung metastases has been proven. However, other metastatic lesions such as enlarged lymph nodes are far more challenging. The aim of this study was to investigate the reproducibility of semi-automated volumetric analysis of lymph node metastases as a function of both slice thickness and reconstruction kernel. In addition, manual long axis diameters (LAD) as well as short axis diameters (SAD) were compared to automated RECIST measurements.
    European journal of radiology 03/2012; 81(11):3124-30. DOI:10.1016/j.ejrad.2012.03.008 · 2.37 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The authors wish to determine the extent to which the Response Evaluation Criteria in Solid Tumors (RECIST) and the criteria of the World Health Organization (WHO) can predict tumor volumes and changes in volume using clinical data. The data presented are a reanalysis of data acquired in other studies, including the public database from the Lung Image Database Consortium (LIDC) and from a study of liver tumors. The principal result is that a given RECIST diameter predicts volume to a factor of 16 or 10 for the two data sets, respectively, by examining 95% prediction bounds and that changes in volume are predicted only little better: to within a factor of 7 for the liver data. The WHO criteria reduce the prediction bounds by a factor of 1.3 in all cases. Also, the RECIST threshold of 10 mm to measure a nodule corresponds to a transition zone width of a factor of more than 2 in volume for the nodules in the LIDC database. While the RECIST diameter is certainly correlated with the volume, and similarly for changes in these quantities, the use of the diameter introduces additional variation assuming volume is the quantity of interest. Exactly how much this reduces the statistical power of clinical drug trials is a key open question for future research.
    Medical Physics 05/2012; 39(5):2628-37. DOI:10.1118/1.3701791 · 2.64 Impact Factor
Show more