Digital image processing for clinicians, part II: filtering

Improving evaluation for TTR amyloidosis by interactive filtering of Tc-99 m PYP SPECT images. The role for "clean blood pool" imaging

BACKGROUND

Myocardial imaging with bone agents such as Tc-99 m PYP and HMDP has assumed a central role in the evaluation of patients with suspected transthyretin (TTR) amyloidosis. Visual scoring (VS) (0-3 +) and the heart to contralateral lung ratio (HCL) classify many patients as equivocal when mediastinal uptake is apparent but cannot be further differentiated into myocardial uptake versus blood pool. SPECT imaging has been recommended but current reconstruction protocols frequently produce amorphous mediastinal activity that also fails to discriminate between myocardial activity and blood pool. We hypothesized that interactive filtering interactively using a deconvolving filter would improve this.

METHODS

We identified 176 sequential patients referred for TTR amyloid imaging. All patients had planar imaging, 101 had planar imaging with a large field of view camera that allowed HCL measurements. SPECT imaging was performed on a 3-headed digital camera with lead fluorescence attenuation correction. One study was excluded for technical reasons. We created software to allow interactive filtering while reconstructing the images then overlay them on attenuation mu maps to assist localization of myocardial/mediastinal uptake. Conventional Butterworth and an interactive inverse Gaussian filters were employed to differentiate myocardial uptake from residual blood pool. We defined "clean blood pool" (CBP) as recognizable blood pool with no activity in the surrounding myocardium. A scan was determined diagnostic if it showed CBP, positive uptake or no identifiable mediastinal uptake.

RESULTS

76/175 (43%) were equivocal (1 +) by visual uptake. Of these 22 (29%) were diagnostic by Butterworth but 71 (93%) were by inverse gaussian (p < .0001). 71/101 (70%) were equivocal by HCL (1-1.5). Of these, 25 (35%) were diagnostic by Butterworth but 68 (96%) were diagnostic by inverse gaussian (p < .0001). This was driven by a greater than threefold increase in the identification of CBP by inverse gaussian filtering.

CONCLUSION

CBP can be identified in the vast majority of patients with equivocal PYP scans using optimized reconstruction and can greatly reduce the number of equivocal scans.

Lung-to-heart ratio analysis using virtual planar images obtained from myocardial perfusion SPECT data: A phantom and clinical studies

BACKGROUNDS

The lung-to-heart ratio (L/H ratio) in myocardial perfusion scintigraphy (MPS) is a useful marker that complements the sensitivity of ischemia detection. However, it requires planar imaging acquired following a separate protocol in addition to single-photon emission computed tomography (SPECT). We developed a novel method for constructing virtual planar image (VPI) from SPECT data.

METHODS

Myocardial phantoms using Tl-201 were built with different amounts of radioactivity in the lungs. SPECT data and conventional planar images of these phantoms were collected with an Anger-type gamma camera. VPIs were constructed by adding all coronal images reconstructed from SPECT data. The clinical utility of VPIs obtained from 52 patients who underwent MPS with Tc-99m sestamibi was evaluated.

RESULTS

The radioactivity linearity of VPIs was satisfactory, with a correlation coefficient of r ≥ .99 between the measured amounts of radioactivity and image counts. The L/H ratios obtained from VPI analysis were strongly correlated with those of conventional planar images with a correlation coefficient of r ≥ .99 in the phantom study and r = .929 in clinical application.

CONCLUSION

The accuracy of VPI-based L/H ratio analysis was comparable to that of conventional planar image-based analysis. VPIs could be used as an alternative method of obtaining planar images in clinical settings.

Myocardial Perfusion Single-Photon Emission Computed Tomography (SPECT) Image Denoising: A Comparative Study

The present study aimed to evaluate the effectiveness of different filters in improving the quality of myocardial perfusion single-photon emission computed tomography (SPECT) images. Data were collected using the Siemens Symbia T2 dual-head SPECT/Computed tomography (CT) scanner. Our dataset included more than 900 images from 30 patients. The quality of the SPECT was evaluated after applying filters such as the Butterworth, Hamming, Gaussian, Wiener, and median-modified Wiener filters with different kernel sizes, by calculating indicators such as the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and contrast-to-noise ratio (CNR). SNR and CNR were highest with the Wiener filter with a kernel size of 5 × 5. Additionally, the Gaussian filter achieved the highest PSNR. The results revealed that the Wiener filter, with a kernel size of 5 × 5, outperformed the other filters for denoising images of our dataset. The novelty of this study includes comparison of different filters to improve the quality of myocardial perfusion SPECT. As far as we know, this is the first study to compare the mentioned filters on myocardial perfusion SPECT images, using our datasets with specific noise structures and mentioning all the elements necessary for its presentation within one document.

Comparison of Low-Pass Filters for SPECT Imaging

In single photon emission computed tomography (SPECT) imaging, the choice of a suitable filter and its parameters for noise reduction purposes is a big challenge. Adverse effects on image quality arise if an improper filter is selected. Filtered back projection (FBP) is the most popular technique for image reconstruction in SPECT. With this technique, different types of reconstruction filters are used, such as the Butterworth and the Hamming. In this study, the effects on the quality of reconstructed images of the Butterworth filter were compared with the ones of the Hamming filter. A Philips ADAC forte gamma camera was used. A low-energy, high-resolution collimator was installed on the gamma camera. SPECT data were acquired by scanning a phantom with an insert composed of hot and cold regions. A Technetium-99m radioactive solution was homogenously mixed into the phantom. Furthermore, a symmetrical energy window (20%) centered at 140 keV was adjusted. Images were reconstructed by the FBP method. Various cutoff frequency values, namely, 0.35, 0.40, 0.45, and 0.50 cycles/cm, were selected for both filters, whereas for the Butterworth filter, the order was set at 7. Images of hot and cold regions were analyzed in terms of detectability, contrast, and signal-to-noise ratio (SNR). The findings of our study indicate that the Butterworth filter was able to expose more hot and cold regions in reconstructed images. In addition, higher contrast values were recorded, as compared to the Hamming filter. However, with the Butterworth filter, the decrease in SNR for both types of regions with the increase in cutoff frequency as compared to the Hamming filter was obtained. Overall, the Butterworth filter under investigation provided superior results than the Hamming filter. Effects of both filters on the quality of hot and cold region images varied with the change in cutoff frequency.

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.

K-space in the clinic

Magnetic resonance imaging (MRI) sequences are characterized by both radio frequency (RF) pulses and time-varying gradient magnetic fields. The RF pulses manipulate the alignment of the resonant nuclei and thereby generate a measurable signal. The gradient fields spatially encode the signals so that those arising from one location in an excited slice of tissue may be distinguished from those arising in another location. These signals are collected and mapped into an array called k-space that represents the spatial frequency content of the imaged object. Spatial frequencies indicate how rapidly an image feature changes over a given distance. It is the action of the gradient fields that determines where in the k-space array each data point is located, with the order in which k-space points are acquired being described by the k-space trajectory. How signals are mapped into k-space determines much of the spatial, temporal, and contrast resolution of the resulting images and scan duration. The objective of this article is to provide an understanding of k-space as is needed to better understand basic research in MRI and to make well-informed decisions about clinical protocols. Four major classes of trajectories-echo planar imaging (EPI), standard (non-EPI) rectilinear, radial, and spiral-are explained. Parallel imaging techniques SMASH (simultaneous acquisition of spatial harmonics) and SENSE (sensitivity encoding) are also described.