Simultaneous 99mTc-MDP/123I-MIBG tumor imaging using SPECT-CT: phantom and constructed patient studies

Dual-Tracer Parathyroid Imaging Using Joint SPECT Reconstruction

Purpose

We assessed the lesion detection performance of the dual-tracer parathyroid SPECT imaging using the joint reconstruction method.

Materials and Methods

Thirty-six noise realizations were created from SPECT projections collected from an in-house neck phantom to emulate 99mTc-pertechnetate/99mTc-sestamibi parathyroid SPECT datasets. Difference images representing parathyroid lesions were reconstructed using the subtraction and the joint methods whose corresponding optimal iteration was defined as the iteration which maximized the channelized Hotelling observer signal-to-noise ratio (CHO-SNR). The joint method whose initial estimate was derived from the subtraction method at optimal iteration (the joint-AltInt method) was also assessed. In a study of 36 patients, a human-observer lesion-detection study was performed using difference images from the three methods at optimal iteration and the subtraction method with four iterations. The area under the receiver operating characteristic curve (AUC) was calculated for each method.

Results

In the phantom study, both the joint-AltInt method and the joint method improved SNR compared to the subtraction method at their optimal iteration by 444% and 81%, respectively. In the patient study, the joint-AltInt method yielded the highest AUC of 0.73 as compared with 0.72, 0.71, and 0.64 from the joint method, the subtraction method at optimal iteration, and the subtraction method at four iterations. At a specificity of at least 0.70, the joint-AltInt method yielded significantly higher sensitivity than the other methods (0.60 vs 0.46, 042, and 0.42; p < 0.05).

Conclusions

The joint reconstruction method yielded higher lesion detectability than the conventional method and holds promise for dual-tracer parathyroid SPECT imaging.

Joint reconstruction of rest/stress myocardial perfusion SPECT

Myocardial perfusion imaging (MPI) using rest/stress single photon emission computed tomography (SPECT) allows non-invasive assessment of reversible cardiac perfusion defects. Conventionally, reversible defects are identified using a difference image, called reversible map, obtained by subtracting the stress image from the rest image after registration and normalization of the two images. The identification of reversible defects using the conventional subtraction method is however limited by noise. We propose to jointly reconstruct rest and stress projection data to directly obtain the reversible map in a single reconstruction framework to improve the detectability of reversible defects. To evaluate the performance of the proposed method, we performed phantom studies to mimic reversible defects with different levels of severity and doses. As compared to the conventional subtraction method, the joint method yielded reversible maps with much lower noise and improved defect detectability. At a normal clinical dose level, the joint method improved the signal to noise ratio (SNR) of defect contrast in reversible maps from 13.2 to 66.4, 9.7 to 35.0, 6.1 to 13.2, and 3.1 to 6.5, for defect to normal myocardium concentration ratios of 0%, 25%, 50%, and 75%, respectively. The SNRs obtained using the joint method were improved from 6.1 to 13.2, 3.9 to 9.4, 3.0 to 8.0, and 2.1 to 7.1, for 100%, 75%, 50%, and 25% of the normal clinical dose as compared to the conventional subtraction method. To access clinical feasibility, we applied the joint method to a rest/stress SPECT MPI patient study. The joint method yielded a reversible map with much lower noise, translating into a much higher defect detectability as compared to the conventional subtraction method. Our results indicate that the joint method has the potential to improve radiologists' performance for assessing defects in rest/stress SPECT MPI. In addition, the joint method can be used to reduce dose or imaging time.

Multiplexed imaging for diagnosis and therapy

Complex molecular and metabolic phenotypes depict cancers as a constellation of different diseases with common themes. Precision imaging of such phenotypes requires flexible and tunable modalities capable of identifying phenotypic fingerprints by using a restricted number of parameters while ensuring sensitivity to dynamic biological regulation. Common phenotypes can be detected by in vivo imaging technologies, and effectively define the emerging standards for disease classification and patient stratification in radiology. However, for the imaging data to accurately represent a complex fingerprint, the individual imaging parameters need to be measured and analysed in relation to their wider spatial and molecular context. In this respect, targeted palettes of molecular imaging probes facilitate the detection of heterogeneity in oncogene-driven alterations and their response to treatment, and lead to the expansion of rational-design elements for the combination of imaging experiments. In this Review, we evaluate criteria for conducting multiplexed imaging, and discuss its opportunities for improving patient diagnosis and the monitoring of therapy.

Joint reconstruction of Ictal/inter-ictal SPECT data for improved epileptic foci localization

PURPOSE

To improve the performance for localizing epileptic foci, we have developed a joint ictal/inter-ictal SPECT reconstruction method in which ictal and inter-ictal SPECT projections are simultaneously reconstructed to obtain the differential image.

METHODS

We have developed a SPECT reconstruction method that jointly reconstructs ictal and inter-ictal SPECT projection data. We performed both phantom and patient studies to evaluate the performance of our joint method for epileptic foci localization as compared with the conventional subtraction method in which the differential image is obtained by subtracting the inter-ictal image from the co-registered ictal image. Two low-noise SPECT projection datasets were acquired using ^99m Tc and a Hoffman head phantom at two different positions and orientations. At one of the two phantom locations, a low-noise dataset was also acquired using a ^99m Tc-filled 3.3-cm sphere with a cold attenuation background identical to the Hoffman phantom. These three datasets were combined and scaled to mimic low-noise clinical ictal (three different lesion-to-background contrast levels: 1.25, 1.55, and 1.70) and inter-ictal scans. For each low-noise dataset, 25 noise realizations were generated by adding Poisson noise to the projections. The mean and standard deviation (SD) of lesion contrast in the differential images were computed using both the conventional subtraction and our joint methods. We also applied both methods to the 35 epileptic patient datasets. Each differential image was presented to two nuclear medicine physicians to localize a lesion and specify a confidence level. The readers' data were analyzed to obtain the localized-response receiver operating characteristic (LROC) curves for both the subtraction and joint methods.

RESULTS

For the phantom study, the difference between the mean lesion contrast in the differential images obtained using the conventional subtraction versus our joint method decreases as the iteration number increases. Compared with the conventional subtraction approach, the SD reduction of lesion contrast at the 10^th iteration using our joint method ranges from 54.7% to 68.2% (P < 0.0005), and 33.8% to 47.9% (P < 0.05) for 2 and 4 million total inter-ictal counts, respectively. In the patient study, our joint method increases the area under LROC from 0.24 to 0.34 and from 0.15 to 0.20 for the first and second reader, respectively. We have demonstrated improved performance of our method as compared to the standard subtraction method currently used in clinical practice.

CONCLUSION

The proposed joint ictal/inter-ictal reconstruction method yields better performance for epileptic foci localization than the conventional subtraction method.