Wiener filter improves diagnostic accuracy of CAD SPECT images-comparison to angiography and CT angiography.

Many discrepancy in selection of proper filter and its parameters for individual cases exists. The authors investigate the impact of the most common filters on patient NM images with coronary artery disease (CAD), and compare the results with the computerized tomography (CT)-Angio and angiography for accuracy.The investigation initiated by performing various single photon emission computerized tomography (SPECT)/CT scan of the national electrical manufacturers association chest phantoms having hot and cold inserts. Data acquired on GE 670 PRO SPECT/CT; 360Ø, 64 frames, 60 seconds, low energy high resolution (LEHR) 128, low energy general purpose (LEGP) with CT attenuation (120 kV and 170 mA). The images reconstructed with filtered back projection and ITERATIVE ordered-subset expectation maximization utilizing filters; Hann, Butterworth, Metz, Hamming, and Wiener. The Image contrast was calculated to assess absolute nearness of the inserts. Based on the preliminary results, then scans of 92 patients with CAD; 64 males and 28 females, age 41 to 77 years old, who had been reported earlier reprocessed with the nominated filter and were reported by 2 NM expert. The results compared to the earlier reports and to the CT-Angio and angiography.The optimization suggested 3 filters; Wiener (Wi), Metz and Butterworth (But) provide the highest contrast (99- 66.4%) and (81- 32%) for the cold and hot inserts respectively, with the (Wi) filter to be the better option. The reprocessed patients scan with the (Wi) presented an elevated diagnostic accuracy, correlated well with the CT-Angio and angiography results (P < .001 and r = 0.79 for [Wi] and P = .004 and r = 0.39 for [But]). The percentage of the false negative for moderate to severe CAD cases reported using Wi filter reduced from 27% to 7% and similarly for mild CAD cases from 7% to 1%.It appears the Wiener filter could produce results with the highest contrast for phantom imaging of various cold and hot spheres and for the patient data which is more consistent with angiography results, with much-elevated accuracy in intermediate cases (r = 0.79 for Wiener and r = 0.39 for Butterworth vs angiography). However, the optimum parameters obtained for the filters have no relation with the resolution of the imaging system, but the details of the objects could be improved.

Impact of PET - CT motion correction in minimizing the gross tumor volume in non-small cell lung cancer.

OBJECTIVES: To investigate the impact of respiratory motion on localization, and quantification of lung lesions for the Gross Tumor Volume utilizing a fully automated Auto3Dreg program and dynamic NURBS-based cardiac-torso digitized phantom (NCAT). METHODS: Respiratory motion may result in more than 30% underestimation of the SUV values of lung, liver and kidney tumor lesions. The motion correction technique adopted in this study was an image-based motion correction approach using, a voxel-intensity-based and a multi-resolution multi-optimization (MRMO) algorithm. The NCAT phantom was used to generate CT attenuation maps and activity distribution volumes for the lung regions. All the generated frames were co-registered to a reference frame using a time efficient scheme. Quantitative assessment including Region of Interest (ROI), image fidelity and image correlation techniques, as well as semi-quantitative line profile analysis and qualitatively overlaying non-motion and motion corrected image frames were performed. RESULTS: The largest motion was observed in the Z-direction. The greatest translation was for the frame 3, end inspiration, and the smallest for the frame 5 which was closet frame to the reference frame at 67% expiration. Visual assessment of the lesion sizes, 20-60mm at 3 different locations, apex, mid and base of lung showed noticeable improvement for all the foci and their locations. The maximum improvements for the image fidelity were from 0.395 to 0.930 within the lesion volume of interest. The greatest improvement in activity concentration underestimation was 7.7% below the true activity for the 20 mm lesion in comparison to 34.4% below, prior to correction. The discrepancies in activity underestimation were reduced with increasing the lesion sizes. Overlaying activity distribution on the attenuation map showed improved localization of the PET metabolic information to the anatomical CT images. CONCLUSION: The respiratory motion correction for the lung lesions has led to an improvement in the lesion size, localization and activity quantification with a potential application in reducing the size of the PET GTV for radiotherapy treatment planning applications and hence improving the accuracy of the regime in treatment of lung cancer.