Usefulness of a breath-holding acquisition method in PET/CT for pulmonary lesions

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Abstract

Objective

To evaluate the usefulness of a breath-holding (BH) 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG-PET) technique for PET/computed tomography (CT) scanning of pulmonary lesions near the diaphragm, where image quality is influenced by respiratory motion.

Methods

In a basic study, simulated breath-holding PET (sBH-PET) data were acquired by repeating image acquisition eight times with fixation of a phantom at 15 s/bed. Free-breathing PET (FB-PET) was simulated by acquiring data even as moving the phantom at 120 s/bed (sFB-PET). Images with total acquisition times of 15 s, 30 s, 45 s, 60 s, and 120 s were generated for sBHPET. Receiver-operating characteristic (ROC) analyses and determination of the statistical significance of differences between sFB-PET images and sBH-PET images were performed. A total of 22 pulmonary lesions in 21 patients (12 men and 9 women, mean age 61.3 ± 10.6 years, 10 benign lesions in 9 patients and 12 malignant lesions in 12 patients) were examined by FB-PET and BH-PET). For evaluation of these two acquisition methods, displacement of the lesion between CT and PET was considered to be a translation, and the statistical significance of differences in maximum standardized uptake value (SUVmax) of the lesion was assessed using the paired t test.

Results

In the basic study, sBH-PET images with acquisition times of 45 s, 60 s, and 120 s had significantly higher diagnostic accuracy than 120-s sFB-PET images (P < 0.05). In clinical cases, translation of the BH-PET images was significantly lower than that of the FB-PET images (benign: 5.29 ± 4.02 mm vs. 11.79 ± 8.27 mm, P = 0.005; malignant: 4.29 ± 3.36 mm vs. 18.26 ± 12.31 mm, P = 0.003). The SUVmax of the lesions in the BH-PET images was significantly higher than that in the FB-PET images (benign: 2.40 ± 0.86 vs. 2.20 ± 0.85, P = 0.005; malignant: 4.84 ± 2.16 vs. 3.75 ± 2.11, P = 0.001).

Conclusions

BH-PET provides images with better diagnostic accuracy, avoids image degradation owing to respiratory motion, and yields more accurate attenuation correction. This method is very useful for overcoming the problem of respiratory motion.

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