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Purpose: 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. Materials and Methods: Multislice-CT of the chest, abdomen and pelvis of 15 patients with lymph node metastases of malignant melanoma were included. Raw data were reconstructed using different slice thicknesses (1-5 mm) and varying reconstruction kernels (B20f, B40f, B60f). Volume and RECIST measurements were performed for 85 lymph nodes between 10 and 60 mm using Oncology Prototype Software (Fraunhofer MEVIS, Siemens, Germany) and were compared to a defined reference volume and diameter by calculating absolute percentage errors (APE). Variability of the lymph node sizes was computed as relative measurement differences, precision of measurements was computed as relative measurement deviation. Results: Mean absolute percentage error (APE) for volumetric analysis varied between 3.95% and 13.8% and increased significantly with slice thickness. Differences between reconstruction kernels were not significant, however, a trend towards middle soft tissue kernel could be observed.. Between automated and manual short axis diameter (SAD, RECIST 1.1) and long axis diameter (LAD, RECIST 1.0) no significant differences were found. The most unsatisfactory segmentation results occurred in higher slice thickness (3 and 5 mm) and sharp tissue kernel. Conclusion: Volumetric analysis of lymph nodes works satisfying in a clinical setting. Thin slice reconstructions (≤3 mm) and a middle soft tissue reconstruction kernel are recommended. LAD and SAD did not show significant differences regarding APE. Automated RECIST measurement showed lower APE than manual measurement in trend. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To examine technical parameters of measurement accuracy and differences in tumor response classification using RECIST 1.1 and volumetric assessment in three common metastasis types (lung nodules, liver lesions, lymph node metastasis) simultaneously. Materials and methods: 56 consecutive patients (32 female) aged 41–82 years with a wide range of metastatic solid tumors were examined with MSCT for baseline and follow up. Images were evaluated by three experienced radiologists using manual measurements and semi-automatic lesion segmentation. Institutional ethics review was obtained and all patients gave written informed consent. Data analysis comprised interobserver variability operationalized as coefficient of variation and categorical response classification according to RECIST 1.1 for both manual and volumetric measures. Continuous data were assessed for statistical significance with Wilcoxon signed-rank test and categorical data with Fleiss kappa. Results: Interobserver variability was 6.3% (IQR 4.6%) for manual and 4.1% (IQR 4.4%) for volumetrically obtained sum of relevant diameters (p <0.05, corrected). 4–8 patients’ response to therapy was classified differently across observers by using volumetry compared to standard manual measurements. Fleiss kappa revealed no significant difference in categorical agreement of response classification between manual (0.7558) and volumetric (0.7623) measurements. Conclusion: Under standard RECIST thresholds there was no advantage of volumetric compared to manual response evaluation. However volumetric assessment yielded significantly lower interobserver variability. This may allow narrower thresholds for volumetric response classification in the future. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: Therapy monitoring in oncologic patient requires precise measurement methods. In order to improve the precision of measurements, we used a semi-automated generic segmentation algorithm to measure the size of large lung cancer tumors. The reproducibility of computer-assisted measurements were assessed and compared with manual measurements. Methods: CT scans of 24 consecutive lung cancer patients who were referred to our hospital over a period of 6 months were analyzed. The tumor sizes were measured manually by 3 independent radiologists, according to World Health Organization (WHO) and the Revised Response Evaluation Criteria in Solid Tumors (RECIST) guidelines. At least 10 months later, measurements were repeated semi-automatically on the same scans by the same radiologists. The inter-observer reproducibility of all measurements was assessed and compared between manual and semi-automated measurements. Results: Manual measurements of the tumor longest diameter were significantly (p <0.05) smaller compared with the semi-automated measurements. The intra-rater correlations coefficients were significantly higher for measurements of longest diameter (intra-class correlation coefficients: 0.998 vs. 0.986; p <0.001) and area (0.995 vs. 0.988; p =0.032) using semi-automated compared with manual method. The variation coefficient for manual measurement of the tumor area (WHO guideline, 15.7% vs. 7.3%) and the longest diameter (RECIST guideline, 7.7% vs. 2.7%) was 2–3 times that of semi-automated measurement. Conclusions: By using computer-assisted size assessment in primary lung tumor, interobserver-variability can be reduced to about half to one-third compared to standard manual measurements. This indicates a high potential value for therapy monitoring in lung cancer patients. [Copyright &y& Elsevier]