Effect of MRI-based semiautomatic size-assessment in cerebral metastases on the RANO-BM classification.

AIM: Evaluation of a semiautomatic software algorithm for magnetic resonance imaging (MRI)-based assessment of cerebral metastases in cancer patients. MATERIAL AND METHODS: Brain metastases (n = 131) in 38 patients, assessed by contrast-enhanced MRI, were retrospectively evaluated at two timepoints (baseline, follow-up) by two experienced neuroradiologists in a blinded manner. The response assessment in neuro-oncology (RANO) criteria for brain metastases (RANO-BM) were applied by means of a software (autoRANO-BM) as well as manually (manRANO-BM) at an interval of 3 weeks. RESULTS: The average diameter of metastases was 12.03 mm (SD ± 6.66 mm) for manRANO-BM and 13.97 mm (SD ± 7.76 mm) for autoRANO-BM. Diameter figures were higher when using semiautomatic measurements (median = 11.8 mm) as compared to the manual ones (median = 10.2 mm; p = 0.000). Correlation coefficients for intra-observer variability were 0.993 (autoRANO-BM) and 0.979 (manRANO-BM). The interobserver variability (R1/R2) was 0.936/0.965 for manRANO-BM and 0.989/0.998 for autoRANO-BM. A total of 19 lesions (15%) were classified differently when using semiautomatic measurements. In 14 cases with suspected disease progression by manRANO-BM a stable course was found according to autoRANO-BM. CONCLUSION: Computerized measuring techniques can aid in the assessment of cerebral metastases by reducing examiner-dependent effects and may consequently result in a different classification according to RANO-BM criteria.

Comparison of volumetric and linear serial CT assessments of lung metastases in renal cell carcinoma patients in a clinical phase IIB study.

RATIONALE AND OBJECTIVES: Accuracy of radiologic assessment may have a crucial impact on clinical studies and therapeutic decisions. We compared the variability of a central radiologic assessment (RECIST) and computer-aided volume-based assessment of lung lesions in patients with metastatic renal cell carcinoma (RCC). MATERIALS AND METHODS: The investigation was prospectively planned as a substudy of a clinical randomized phase IIB therapeutic trial in patients with RCC. Starting with the manual study diameter (SDM) of the central readers using RECIST in the clinical study, we performed computer-aided volume measurements. We compared SDM to an automated RECIST diameter (aRDM) and the diameter of a volume-equivalent sphere (effective diameter [EDM]), both for the individual size measurements and for the change rate (CR) between consecutive time points. One hundred thirty diameter pairs of 30 lung lesions from 14 patients were evaluable, forming 55 change pairs over two consecutive time points each. RESULTS: The SDMs of two different readers showed a correlation of 95.6%, whereas the EDMs exhibited an excellent correlation of 99.4%. Evaluation of CRs showed an SDM-CR correlation of 63.9%, which is substantially weaker than the EDM-CR correlation of 87.6%. The variability of SDM-CR is characterized by a median absolute difference of 11.4% points versus the significantly lower 1.8% points EDM-CRs variability (aRDM: 3.2% points). The limits of agreement between readers suggest that an EDM change of 10% or 1 mm can already be significant. CONCLUSIONS: Computer-aided volume-based assessments result in markedly reduced variability of parameters describing size and change, which may offer an advantage of earlier response evaluations and treatment decisions for patients.

Intra- and interobserver variability of linear and volumetric measurements of brain metastases using contrast-enhanced magnetic resonance imaging.

OBJECTIVES: To compare the intra- and interobserver variability of diameter and semiautomated volume measurements of brain metastases on contrast-enhanced magnetic resonance imaging (CE-MRI) data. MATERIALS AND METHODS: About 75 MRI staging examinations of patients with metastasized renal cell carcinoma, thyroid cancer, or malignant melanoma (mean age, 56 years; range, 40-75 years) were included. Patients had been examined with a routine MRI protocol, including a CE 3D T1-weighted MP-RAGE sequence (1-mm slice thickness). MRI data were retrospectively analyzed using the OncoTREAT segmentation system (MeVis, Bremen, Germany, version 1.6). Volume of 355 enhancing brain metastases included in the analysis as well as the largest diameter according to Response Evaluation Criteria for Solid Tumors were measured by 2 radiologists. Intra- and interobserver variability was calculated. RESULTS: Metastases (n = 355) had a mean diameter of 12.2 mm (range, 3.4-44.3 mm) and a mean volume of 1.4 cm(3) (range, 12-25.1 cm(3)). With respect to interobserver variability analysis revealed broader limits of agreement for response evaluation criteria for solid tumor measurements of all lesions (range, +/-27.8%-+/-33.0%; unsigned mean: 0.2%-2.5%) than for volume measurements (range, +/-21.4%-+/-23.3%; unsigned mean, 0.1%-0.3%) with statistically significant differences between diameter and volume measurements (P

Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT.

The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2-44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with -9.7% to 8.3% (mean difference -0.7%) for SD-CT and with -12.6% to 12.4% (mean difference -0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with -25.1% to -23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.

Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans.

Volumetric growth assessment of pulmonary lesions is crucial to both lung cancer screening and oncological therapy monitoring. While several methods for small pulmonary nodules have previously been presented, the segmentation of larger tumors that appear frequently in oncological patients and are more likely to be complexly interconnected with lung morphology has not yet received much attention. We present a fast, automated segmentation method that is based on morphological processing and is suitable for both small and large lesions. In addition, the proposed approach addresses clinical challenges to volume assessment such as variations in imaging protocol or inspiration state by introducing a method of segmentation-based partial volume analysis (SPVA) that follows on the segmentation procedure. Accuracy and reproducibility studies were performed to evaluate the new algorithms. In vivo interobserver and interscan studies on low-dose data from eight clinical metastasis patients revealed that clinically significant volume change can be detected reliably and with negligible computation time by the presented methods. In addition, phantom studies were conducted. Based on the segmentation performed with the proposed method, the performance of the SPVA volumetry method was compared with the conventional technique on a phantom that was scanned with different dosages and reconstructed with varying parameters. Both systematic and absolute errors were shown to be reduced substantially by the SPVA method. The method was especially successful in accounting for slice thickness and reconstruction kernel variations, where the median error was more than halved in comparison to the conventional approach.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT part 2. Therapy monitoring of pulmonary metastases.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a software application was developed to assist the radiologist in the analysis of thoracic CT data for the purpose of evaluating the response to tumor therapy. The application provides follow-up support for monitoring of tumor therapy by means of volumetric quantification of tumors and temporal registration. In addition, anatomically adequate three-dimensional visualization techniques for convenient examination of large data sets are included. With close cooperation between computer scientists and radiologists, the application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the application improves therapy monitoring with respect to accuracy and time required.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT. Part 1. Functional analysis of lungs, lung lobes, and bronchopulmonary segments.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a prototypical software application was developed to assist the radiologist in functional analysis of thoracic CT data. By identifying the anatomic compartments of the lungs, the software application enables assessment of established functional CT parameters for each individual lung, pulmonary lobe, and pulmonary segment. Such region-based assessment allows a more localized diagnosis of lung diseases such as emphysema and more accurate estimation of regional lung function from CT data. With close cooperation between computer scientists and radiologists, the software application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the software application improves quantification in diagnosis, therapy planning, and therapy monitoring with respect to accuracy and time required.