Background: Functional liver reserve is an important determinant of survival in cirrhosis. The traditional indocyanine green test (ICG) is cumbersome. Hence, we developed and validated a novel liver imaging, a hybrid of SPECT and CT (Q-SPECT/CT), for evaluating disease severity, outcomes, and response to treatment in decompensated cirrhosis (DC).
Methods: We recruited a cohort of DC patients at a tertiary institute between 2016–2019. First, we standardized the Q-SPECT/CT across a predefined range of volumes through phantom experiments. Then we performed clinical and laboratory evaluations, ICG test (retention at 15 min), and Q-SPECT/CT at baseline and 12 months of granulocyte colony-stimulating factor (G-CSF) and standard medical treatment (SMT).
Results: In 109 DC patients, 87.1% males, aged 51 ± 10 years, MELD: 14 (7–21), the percent quantitative liver uptake (%QLU) on Q-SPECT/CT exhibited a strong correlation with CTP (r = −0.728, p < 0.001), MELD (r = −0.743; p < 0.001) and ICG-R-15 (r = −0.720, p < 0.001) at baseline. %QLU had the maximum discrimination (AUC: 0.890–0.920), sensitivity (88.9–90.3%), specificity (81.2–90.7%), and accuracy (85.8–89.4%) than liver volumes on Q-SPECT/CT or ICG test for classifying patients in CTP/MELD based prognostic categories. A significant increase in %QLU (26.09 ± 10.06 to 31.2 ± 12.19, p = 0.001) and improvement in CTP/MELD correlated with better survival of G-CSF treated DC patients (p < 0.05). SMT did not show any improvement in Q-SPECT/CT or clinical severity scores (p > 0.05). %QLU > 25 (adj.H.R.: 0.234, p = 0.003) and G-CSF treatment (adj.H.R.: 0.414, p = 0.009) were independent predictors of better 12-months survival in DC.
Conclusion: Q-SPECT/CT (%QLU) is a novel non-invasive, diagnostic, prognostic, and theragnostic marker of liver reserve and its functions in cirrhosis patients.
Clinical trial registration: Clinicaltrials.gov, NCT02451033 and NCT03415698.
Purpose: Deep learning-based denoising is promising for myocardial perfusion (MP) SPECT. However, conventional convolutional neural network (CNN)-based methods use fixed-sized convolutional kernels to convolute one region within the receptive field at a time, which would be ineffective for learning the feature dependencies across large regions. The attention mechanism (Att) is able to learn the relationships between the local receptive field and other voxels in the image. In this study, we propose a 3D attention-guided generative adversarial network (AttGAN) for denoising fast MP-SPECT images.
Methods: Fifty patients who underwent 1184 MBq 99mTc-sestamibi stress SPECT/CT scan were retrospectively recruited. Sixty projections were acquired over 180° and the acquisition time was 10 s/view for the full time (FT) mode. Fast MP-SPECT projection images (1 s to 7 s) were generated from the FT list mode data. We further incorporated binary patient defect information (0 = without defect, 1 = with defect) into AttGAN (AttGAN-def). AttGAN, AttGAN-def, cGAN, and Unet were implemented using Tensorflow with the Adam optimizer running up to 400 epochs. FT and fast MP-SPECT projection pairs of 35 patients were used for training the networks for each acquisition time, while 5 and 10 patients were applied for validation and testing. Five-fold cross-validation was performed and data for all 50 patients were tested. Voxel-based error indices, joint histogram, linear regression, and perfusion defect size (PDS) were analyzed.
Results: All quantitative indices of AttGAN-based networks are superior to cGAN and Unet on all acquisition time images. AttGAN-def further improves AttGAN performance. The mean absolute error of PDS by AttcGAN-def was 1.60 on acquisition time of 1 s/prj, as compared to 2.36, 2.76, and 3.02 by AttGAN, cGAN, and Unet.
Conclusion: Denoising based on AttGAN is superior to conventional CNN-based networks for MP-SPECT.
Purpose: To assess the utility of skeletal standardized uptake values (SUVs) obtained using quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) in differentiating bone metastases from benign lesions, particularly in patients with lung adenocarcinoma.
Methods: Patients with lung adenocarcinoma who had undergone whole-body Tc-99m methyl-diphosphonate (99mTc-MDP) bone scans and received late phase SPECT/CT were retrospectively analyzed in this study. The maximum SUV (SUVmax); Hounsfield units (HUs); and volumes of osteoblastic, osteolytic, mixed, CT-negative metastatic and benign bone lesions, and normal vertebrae were compared. Receiver operating characteristic curves were used to determine the optimal cutoff SUVmax between metastatic and benign lesions as well as the cutoff SUVmax between CT-negative metastatic lesions and normal vertebrae. The linear correlation between SUVmax and HUs of metastatic lesions as well as that between SUVmax and the volume of all bone lesions were investigated.
Results: A total of 252 bone metastatic lesions, 140 benign bone lesions, and 199 normal vertebrae from 115 patients with lung adenocarcinoma were studied (48 males, 67 females, median age: 59 years). Metastatic lesions had a significantly higher SUVmax (23.85 ± 14.34) than benign lesions (9.67 ± 7.47) and normal vertebrae (6.19 ± 1.46; P < 0.0001). The SPECT/CT hotspot of patients with bone metastases could be distinguished from benign lesions using a cutoff SUVmax of 11.10, with a sensitivity of 87.70% and a specificity of 80.71%. The SUVmax of osteoblastic (29.16 ± 16.63) and mixed (26.62 ± 14.97) lesions was significantly greater than that of osteolytic (15.79 ± 5.57) and CT-negative (16.51 ± 6.93) lesions (P < 0.0001, P = 0.0003, and 0.002). SUVmax at the cutoff value of 8.135 could distinguish CT-negative bone metastases from normal vertebrae, with a sensitivity of 100.00% and a specificity of 91.96%. SUVmax showed a weak positive linear correlation with HUs in all bone metastases and the volume of all bone lesions.
Conclusion: SUVmax of quantitative SPECT/CT is a useful index for distinguishing benign bone lesions from bone metastases in patients with lung adenocarcinoma, particularly in the diagnosis of CT-negative bone metastases, but other factors that may affect SUVmax should be considered.
Lymphoscintigraphy is still considered the gold standard imaging modality for diagnosing lymphedema, due to ineffective lymphatic transport resulting in edema and skin damage. However, protocol variability and poor image resolution can make the interpretation challenging. Up to now, 99 mTc-labeled colloid lymphatic travel is monitored with dual-head cameras, but single-photon emission CT (SPECT) has proved its interest. Here, we present the case of a 59-year-old-man with bilateral asymmetric lower limb edema which was explored using dual-head and new 3D-ring cadmium -zinc-telluride (CZT) SPECT cameras, confirming bilateral lower limb lymphatic dysfunction. In line with other recently published reports, this case report promotes the use of SPECT/CT in the lymphoscintigraphic exploration of lower limb edema. The recognition of the clinicopathologic features of lower limb edema is required to prevent missed diagnoses, such as compressive disease, tumors, etc., as well as to better influence the management of patients.
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