[Automatic detection of pulmonary nodules on computed tomography: a preliminary study]

Integrating CAD modules in a PACS environment using a wide computing infrastructure

PURPOSE

The aim of this paper is to describe a project designed to achieve a total integration of different CAD algorithms into the PACS environment by using a wide computing infrastructure.

METHODS

The aim is to build a system for the entire region of Galicia, Spain, to make CAD accessible to multiple hospitals by employing different PACSs and clinical workstations. The new CAD model seeks to connect different devices (CAD systems, acquisition modalities, workstations and PACS) by means of networking based on a platform that will offer different CAD services. This paper describes some aspects related to the health services of the region where the project was developed, CAD algorithms that were either employed or selected for inclusion in the project, and several technical aspects and results.

RESULTS

We have built a standard-based platform with which users can request a CAD service and receive the results in their local PACS. The process runs through a web interface that allows sending data to the different CAD services. A DICOM SR object is received with the results of the algorithms stored inside the original study in the proper folder with the original images.

CONCLUSIONS

As a result, a homogeneous service to the different hospitals of the region will be offered. End users will benefit from a homogeneous workflow and a standardised integration model to request and obtain results from CAD systems in any modality, not dependant on commercial integration models. This new solution will foster the deployment of these technologies in the entire region of Galicia.

Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival

PURPOSE

To establish the potential for tumour heterogeneity in non-small cell lung cancer (NSCLC) as assessed by CT texture analysis (CTTA) to provide an independent marker of survival for patients with NSCLC.

MATERIALS AND METHODS

Tumour heterogeneity was assessed by CTTA of unenhanced images of primary pulmonary lesions from 54 patients undergoing (18)F-fluorodeoxyglucose (FDG) PET-CT for staging of NSCLC. CTTA comprised image filtration to extract fine, medium and coarse features with quantification of the distribution of pixel values (uniformity) within the filtered images. Receiver operating characteristics identified thresholds for PET and CTTA parameters that were related to patient survival using Kaplan-Meier analysis.

RESULTS

The median (range) survival was 29.5 (1-38) months. 24, 10, 14 and 6 patients had tumour stages I, II, III and IV respectively. PET stage and tumour heterogeneity assessed by CTTA were significant independent predictors of survival (PET stage: Odds ratio 3.85, 95% confidence limits 0.9-8.09, P = 0.002; CTTA: Odds ratio 56.4, 95% confidence limits 4.79-666, p = 0.001). SUV was not a significantly associated with survival.

CONCLUSION

Assessment of tumour heterogeneity by CTTA of non-contrast enhanced images has the potential for to provide a novel, independent predictor of survival for patients with NSCLC.

KEY POINTS

Computed tomography is a routine staging procedure in non-small cell lung cancer. CT texture analysis (CTTA) can quantify heterogeneity within these lung tumours. CTTA seems to offer a novel independent predictor of survival for NSCLC. CTTA could contribute to disease risk-stratification for patients with NSCLC.

[Semiautomatic quantification of left and right ventricular function in cardiac magnetic resonance imaging: a preliminary study]

OBJECTIVES

The aim of this study was to compare a semiautomatic segmentation method to quantify the function of both ventricles in magnetic resonance imaging (MRI) with the manual tracing method.

MATERIAL AND METHODS

We examined 17 patients with diverse cardiovascular diseases on a 1.5 Tesla MRI unit (Magnetom Symphony Quantum; Siemens Medical Systems, Erlangen, Germany) using the following parameters: maximum gradient, 30 mT/m; and slew rate, 125 T/m/s. In all studies, we acquired images in cine mode in the short axis (SSFP, 6mm slice thickness, from the base to the ventricular apex) with breath holding. To reduce the user interaction, we used only one image per patient to initiate the semiautomatic method. The semiautomatic method was based on a specifically designed algorithm of regional growth and border detection. We quantified the end-diastolic volume (EDV), end-systolic volume (ESV), and the ejection fraction (EF) for both ventricles in all patients.

RESULTS

No significant differences between the two segmentation techniques were found in the quantification of either ventricle (p>0.05). The difference in the volumes, although nearly significant, are clinically irrelevant. The correlation for the estimation of left ventricular function was excellent (r>0.9), and the correlation for the estimation of right ventricular function was good (r>0.7).

CONCLUSIONS

Our semiautomatic segmentation method enables the function of both ventricles to be quantified as accurately as the conventional method.