Is there an incremental value to use myocardial perfusion imaging with or without CT attenuation for the diagnosis of coronary artery disease? A study in Chinese patients.

OBJECTIVE: To evaluate whether computed tomography attention correction (CTAC) has incremental diagnostic value for single photon emission tomography (SPET) myocardial perfusion imaging (MPI) for the detection of coronary artery disease (CAD) in Chinese patients. SUBJECTS AND METHODS: This retrospective study consisted of 181 suspected CAD patients who underwent one-stop SPET examination by MPI combined with a CT scan. Two observers independently evaluated non-attenuation correction (NAC) and CTAC MPI images, and coronary angiography (CAG) results were used as reference standards. The diagnostic efficacies of the two methods were compared. RESULTS: a) In the whole group, the sensitivity, specificity and accuracy for the detection of CAD were found to be 75.7%, 55.1% and 63.5% for NAC images and 52.7%, 86.9% and 72.9% for CTAC images, respectively; the areas under the receiver operating characteristic curves (AUC) were 0.654 and 0.698 (P>0.05). b) The accuracy of CTAC and the AUC were significantly higher than those for NAC in Chinese males. c) The accuracy of CTAC was also significantly increased for the right coronary artery (RCA) territory and in overweight patients (BMI≥24), although differences in the AUC were marginally insignificant. CONCLUSION: Compared to NAC MPI, CTAC improved SPET MPI specificity but decreased sensitivity, leading to no obvious improvement in overall accuracy for the diagnosis of CAD in Chinese patients. However, CTAC might be of value in the subgroups of males and overweight patients and for the RCA territory. In routine clinical application, the integration of NAC and CTAC findings combined with CAD pre-test probability could improve MPI diagnostic performance.

Coronary arteriography in the diagnosis results and prognosis analysis of suspected coronary artery disease in patients with normal SPET myocardial perfusion imaging.

OBJECTIVE: Anatomic coronary artery disease (CAD) can be determined by coronary angiography (CAG) in patients with normal stress single photon emission tomography (SPET) myocardial perfusion imaging (MPI). Coronary angiography results of patients with negative exercise MPI and the prognosis of these patients (CAG-diagnosed CAD vs. non-CAD) were investigated in the current study. SUBJECTS AND METHODS: Suspected CAD patients who had SPET-MPI and subsequent CAG studies were retrospectively reviewed from May 2002 to November 2006. Siemens Diacam SPET and Siemens Ecam SPET γ-cameras were used for the examination of rest/exercise technetium-99m methoxy isobutyl isonitrile ((99m)Tc-MIBI) myocardial imaging. Coronary angiography was performed with Philips arura angiography machine by the standard Judkins method. RESULTS: In all, 6598 patients underwent clinically indicated rest/exercise (99m)Tc-MIBI SPET-MPI, and 133 patients underwent CAG despite negative MPI. Thirty one patients were diagnosed with CAD by CAG. Most of these lesions (66%) were located in distal vessels and most of these patients (68%) had 1 vessel disease. Age (P<0.01), hypertension (P<0.01), typical angina pectoris (P<0.01), high pretest likelihood of CAD (P<0.001), exercise induced angina (P<0.05), positive exercise ECG (P<0.01), and transient enlargement of scintigraphic left ventricular size (P<0.05) were significantly different between non-CAD and CAD groups. After median follow-up time of 53 ± 18 months, annualized cardiac event rate was 0.9% and 0.2% in CAD and non-CAD group, respectively (χ² = 1.22, P=0.27). CONCLUSION: In all, 23% of 133 patients in our study we confirmed anatomic CAD by CAG, despite negative findings in SPET-MPI. Several clinical, stress, and MPI findings could be potential predictors. However, similar to non-CAD group, the CAG diagnosed CAD patients negative (99m)Tc-MIBI SPET-MPI exercise test had a good prognosis with annualized cardiac event rate less than 1.0%.

Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer.

BACKGROUND: Precise preoperative prediction of lymph node metastasis (LNM) is crucial for optimal diagnosis and treatment in patients with gastric cancer (GC), in which existing imaging methods have certain limitations. We hypothesized that PET primary lesion-based radiomics signature could provide incremental value to conventional metabolic parameters and traditional risk indicators in predicting LNM in patients with GC. METHODS: This retrospective study was performed in 127 patients with GC who underwent preoperative PET/CT. Basic clinical data and PET conventional metabolic parameters were collected. Radiomics signature was constructed by the least absolute shrinkage and selection operator algorithm (LASSO) logistic regression. Based on the postoperative histological results, the patients were divided into LNM group and non-lymph node metastasis (NLNM) group. Receiver-operating characteristic (ROC) was used to evaluate the discriminatory ability of Radiomics score (Rad-score) for predicting LNM and determine whether adding Rad-score to PET conventional metabolic parameters and traditional risk factors could improve the predictive value in LNM. The Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to further confirm the incremental value of Rad-score for predicting LNM in GC. RESULTS: The LNM group had higher Rad-score than NLNM group [(0.35 (-0.13-0.85) vs. -0.61 (-1.92-0.18), P < 0 .001)]. After adjusted for gender, age, BMI, and FBG, multivariable logistic regression analysis illustrated that Rad-score (OR: 6.38, 95% CI: 2.73-14.91, P < 0.0001) was independent risk factors for LNM in GC. Adding PET conventional parameters to traditional risk factors increased the predictive value of LNM in GC (AUC 0.751 vs 0.651, P = 0.02). Additional inclusion of Rad-score to conventional metabolic parameters and traditional risk indicators significantly improved the AUC (0.882 vs 0.751; P = 0.006). Bootstrap resampling (times = 500) was used for internal verification, 95% confidence interval (CI) was 0.802-0.948, with the sensitivity equaled to 89.5%, and positive predictive value (PPV) was 93.5%. When Rad-score was added to conventional metabolic parameters and traditional risk indicators, net reclassification improvement (NRI) was 0.293 (P = 0.0040) and integrated discrimination improvement (IDI) was 0.293 (P = 0.0045). CONCLUSION: In GC patients, PET Radiomics signature of the primary lesion-based was significantly associated with LNM and could improve the prediction of LNM above PET conventional metabolic parameters and traditional risk factors, which could provide incremental value for individual diagnosis and treatment of GC.

18F-FDG PET/CT-based radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.

Objective: Lymph node metastasis (LNM) is not only one of the important factors affecting the prognosis of gastric cancer but also an important basis for treatment decisions. The purpose of this study was to investigate the value of the radiomics nomogram based on preoperative 18F-deoxyglucose (FDG) PET/CT primary lesions and clinical risk factors for predicting LNM in gastric cancer (GC). Methods: We retrospectively analyzed radiomics features of preoperative 18F-FDG PET/CT images in 224 gastric cancer patients from two centers. The prediction model was developed in the training cohort (n = 134) and validated in the internal (n = 59) and external validation cohorts (n = 31). The least absolute shrinkage and selection operator (LASSO) regression was used to select features and build radiomics signatures. The radiomics feature score (Rad-score) was calculated and established a radiomics signature. Multivariate logistic regression analysis was used to screen independent risk factors for LNM. The minimum Akaike's information criterion (AIC) was used to select the optimal model parameters to construct a radiomics nomogram. The performance of the nomogram was assessed with calibration, discrimination, and clinical usefulness. Results: There was no significant difference between the internal verification and external verification of the clinical data of patients (all p > 0.05). The areas under the curve (AUCs) (95% CI) for predicting LNM based on the 18F-FDG PET/CT radiomics signature in the training cohort, internal validation cohort, and external validation cohort were 0.792 (95% CI: 0.712-0.870), 0.803 (95% CI: 0.681-0.924), and 0.762 (95% CI: 0.579-0.945), respectively. Multivariate logistic regression showed that carbohydrate antigen (CA) 19-9 [OR (95% CI): 10.180 (1.267-81.831)], PET/CT diagnosis of LNM [OR (95% CI): 6.370 (2.256-17.984)], PET/CT Rad-score [OR (95% CI): 16.536 (5.506-49.660)] were independent influencing factors of LNM (all p < 0.05), and a radiomics nomogram was established based on those factors. The AUCs (95% CI) for predicting LNM were 0.861 (95% CI: 0.799-0.924), 0.889 (95% CI: 0.800-0.976), and 0.897 (95% CI: 0.683-0.948) in the training cohort, the internal validation cohort, and the external validation cohort, respectively. Decision curve analysis (DCA) indicated that the 18F-FDG PET/CT-based radiomics nomogram has good clinical utility. Conclusions: Radiomics nomogram based on the primary tumor of 18F-FDG PET/CT could facilitate the preoperative individualized prediction of LNM, which is helpful for risk stratification in GC patients.

Risk analysis in peripheral clinical T1 non-small cell lung cancer correlations between tumor-to-blood standardized uptake ratio on 18F-FDG PET-CT and primary tumor pathological invasiveness: a real-world observational study.

BACKGROUND: Sublobar resection is not suitable for patients with pathological invasiveness [including lymph node metastasis (LNM), visceral pleural invasion (VPI), and lymphovascular invasion (LVI)] of peripheral clinical T1 (cT1) non-small cell lung cancer (NSCLC), while primary tumor maximum standardized uptake value (SUVmax) on 18F-FDG PET-CT is related to pathological invasiveness, the significance differed among different institutions is still challenging. This study explored the relationship between the tumor-to-blood standardized uptake ratio (SUR) of 18F-FDG PET-CT and primary tumor pathological invasiveness in peripheral cT1 NSCLC patients. METHODS: This retrospective study included 174 patients with suspected lung neoplasms who underwent preoperative 18F-FDG PET-CT. We compared the differences of the clinicopathological variables, metabolic and morphological parameters in the pathological invasiveness and less-invasiveness group. We performed a trend test for these parameters based on the tertiles of SUR. The relationship between SUR and pathological invasiveness was evaluated by univariate and multivariate logistics regression models (included unadjusted, simple adjusted, and fully adjusted models), odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated. A smooth fitting curve between SUR and pathological invasiveness was produced by the generalized additive model (GAM). RESULTS: Thirty-eight point five percent of patients had pathological invasiveness and tended to have a higher SUR value than the less-invasiveness group [6.50 (4.82-11.16) vs. 4.12 (2.04-6.61), P<0.001]. The trend of SUVmax, mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), mean CT value (CTmean), size of the primary tumor, neuron-specific enolase (NSE), the incidence of LNM, adenocarcinoma (AC), and poor differentiation in the tertiles of SUR value were statistically significant (P were <0.001, <0.001, 0.010, <0.001, <0.001, 0.002, 0.033, <0.001, 0.002, and <0.001, respectively). Univariate analysis showed that the risk of pathological invasiveness increased significantly with increasing SUR [OR: 1.13 (95% CI: 1.06-1.21), P<0.001], and multivariate analysis demonstrated SUR, as a continuous variable, was still significantly related to pathological invasiveness [OR: 1.09 (95% CI: 1.01-1.18), P=0.032] after adjusting for confounding covariates. GAM revealed that SUR tended to be linearly and positively associated with pathological invasiveness and E-value analysis suggested robustness to unmeasured confounding. CONCLUSIONS: SUR is linearly and positively associated with primary tumor pathological invasiveness independent of confounding covariates in peripheral cT1 NSCLC patients and could be used as a supplementary risk maker to assess the risk of pathological invasiveness.

Radiomics model based on preoperative 18F-fluorodeoxyglucose PET predicts N2-3b lymph node metastasis in gastric cancer patients.

OBJECTIVE: The aim of the study was to construct and validate 18F-fluorodeoxyglucose (18F-FDG) PET-based radiomics nomogram and use it to predict N2-3b lymph node metastasis in Chinese patients with gastric cancer (GC). METHODS: A total of 127 patients with pathologically confirmed GC who underwent preoperative 18F-FDG PET/CT imaging between January 2014 and September 2020 were enrolled as subjects in this study. We use the LIFEx software to extract PET radiomic features. A radiomics signature (Rad-score) was developed with the least absolute shrinkage and selection operator algorithm. Then a prediction model, which incorporated the Rad-score and independent clinical risk factors, was constructed and presented with a radiomics nomogram. Receiver operating characteristic (ROC) analysis was used to assess the performance of Rad-score and the nomogram. Finally, decision curve analysis (DCA) was applied to evaluate the clinical usefulness of the nomogram. RESULTS: The PET Rad-score, which includes four selected features, was significantly related to pN2-3b (all P < 0.05). The prediction model, which comprised the Rad-score and carcinoembryonic antigen (CEA) level, showed good calibration and discrimination [area under the ROC curve: 0.81(95% confidence interval: 0.74-0.89), P < 0.001)]. The DCA also indicated that the prediction model was clinically useful. CONCLUSION: This study presents a radiomics nomogram consisting of a radiomics signature based on PET images and CEA level that can be conveniently used for personalized prediction of high-risk N2-3b metastasis in Chinese GC patients.

Relationship between total lesion glycolysis of primary lesions based on 18F-FDG PET/CT and lymph node metastasis in gastric adenocarcinoma: a cross-sectional preliminary study.

OBJECTIVES: We explored the relationship between lymph node metastasis (LNM) and total lesion glycolysis (TLG) of primary lesions determined by 18fluoro-2-deoxyglucose PET/computed tomography (18F-FDG PET/CT) in patients with gastric adenocarcinoma, and evaluated the independent effect of this association. METHODS: This retrospective study included 106 gastric adenocarcinoma patients who were examined by preoperative 18F-FDG PET/CT imaging between April 2016 and April 2020. We measured TLG of primary gastric lesions and evaluated its association with LNM. Multivariate logistic regression and a two-piece-wise linear regression were performed to evaluate the relationship between TLG of primary lesions and LNM. RESULTS: Of the 106 patients, 75 cases (71%) had LNM and 31 cases (29%) did not have LNM. Univariate analyses revealed that a per-SD increase in TLG was independently associated with LNM [odds ratio (OR) = 2.37; 95% confidence interval (CI), 1.42-3.98; P = 0.0010]. After full adjustment of confounding factors, multivariate analyses exhibited that TLG of primary lesions was still significantly associated with LNM (OR per-SD: 2.20; 95% CI, 1.16-4.19; P = 0.0164). Generalized additive model indicated a nonlinear relationship and saturation effect between TLG of primary lesions and LNM. When TLG of primary lesions was <23.2, TLG was significantly correlated with LNM (OR = 1.26; 95% CI, 1.07-1.48; P = 0.0053), whereas when TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. CONCLUSIONS: In this preliminary study, there were saturation and segmentation effects between TLG of primary lesions determined by preoperative 18F-FDG PET/CT and LNM. When TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. TLG of primary lesions is helpful in the preoperative diagnosis of LNM in patients with gastric adenocarcinoma.

High-resolution MRI-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer.

PURPOSE: To establish and validate two predictive radiomics models for preoperative prediction of lymph node metastases (LNMs) and tumor deposits (TDs) respectively in rectal cancer (RC) patients. METHODS: A total of 139 RC patients (98 in the training cohort and 41 in the validation cohort) were enrolled in the present study. High-resolution magnetic resonance images (HRMRI) were retrieved for tumor segmentation and feature extraction. HRMRI findings of RC were assessed by three experienced radiologists. Two radiomics nomograms were established by integrating the clinical risk factors, HRMRI findings and radiomics signature. RESULTS: The predictive nomogram of LNMs showed good predictive performance (area under the curve [AUC], 0.90; 95% confidence interval [CI] 0.83-0.96) which was better than clinico-radiological (AUC, 0.83; 95% CI 0.74-0.93; Delong test, p = 0.017) or radiomics signature-only model (AUC, 0.77; 95% CI 0.67-0.86; Delong test, p = 0.003) in training cohort. Application of the nomogram in the validation cohort still exhibited good performance (AUC, 0.87; 95% CI 0.76-0.98). The accuracy, sensitivity and specificity of the combined model in predicting LNMs was 0.86,0.79 and 0.91 in training cohort and 0.83,0.85 and 0.82 in validation cohort. As for TDs, the predictive efficacy of the nomogram (AUC, 0.82; 95% CI 0.71-0.93) was not significantly higher than radiomics signature-only model (AUC, 0.80; 95% CI 0.69-0.92; Delong test, p = 0.71). Radiomics signature-only model was adopted to predict TDs with accuracy=0.76, sensitivity=0.72 and specificity=0.94 in training cohort and 0.68, 0.62 and 0.97 in validation cohort. CONCLUSION: HRMRI-based radiomics models could be helpful for the prediction of LNMs and TDs preoperatively in RC patients.

High resolution MRI-based radiomic nomogram in predicting perineural invasion in rectal cancer.

BACKGROUND: To establish and validate a high-resolution magnetic resonance imaging (HRMRI)-based radiomic nomogram for prediction of preoperative perineural invasion (PNI) of rectal cancer (RC). METHODS: Our retrospective study included 140 subjects with RC (99 in the training cohort and 41 in the validation cohort) who underwent a preoperative HRMRI scan between December 2016 and December 2019. All subjects underwent radical surgery, and then PNI status was evaluated by a qualified pathologist. A total of 396 radiomic features were extracted from oblique axial T2 weighted images, and optimal features were selected to construct a radiomic signature. A combined nomogram was established by incorporating the radiomic signature, HRMRI findings, and clinical risk factors selected by using multivariable logistic regression. RESULTS: The predictive nomogram of PNI included a radiomic signature, and MRI-reported tumor stage (mT-stage). Clinical risk factors failed to increase the predictive value. Favorable discrimination was achieved between PNI-positive and PNI-negative groups using the radiomic nomogram. The area under the curve (AUC) was 0.81 (95% confidence interval [CI], 0.71-0.91) in the training cohort and 0.75 (95% CI, 0.58-0.92) in the validation cohort. Moreover, our result highlighted that the radiomic nomogram was clinically beneficial, as evidenced by a decision curve analysis. CONCLUSIONS: HRMRI-based radiomic nomogram could be helpful in the prediction of preoperative PNI in RC patients.

Preoperative 18F-FDG SUVmax >6.3 or Size >2.3 cm of primary lesions predict lymph nodes metastasis with higher negative predictive value in peripheral cT1 non-small-cell lung cancer.

BACKGROUND: Sublobar resection is suitable for peripheral cT1N0M0 non-small-cell lung cancer (NSCLC). The traditional PET-CT criterion (lymph node size ≥1.0 cm or SUVmax ≥2.5) for predicting lymph nodes metastasis (LNM) has unsatisfactory performance. OBJECTIVE: We explore the clinical role of preoperative SUVmax and the size of the primary lesions for predicting peripheral cT1 NSCLC LNM. METHODS: We retrospectively analyzed 174 peripheral cT1 NSCLC patients underwent preoperative 18F-FDG PET-CT and divided into the LNM and non-LNM group by pathology. We compared the differences of primary lesions' baseline characteristics between the two groups. The risk factors of LNM were determined by univariate and multivariate analysis, and we assessed the diagnostic efficacy with the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value (NPV). RESULTS: Of the enrolled cases, the incidence of LNM was 24.7%. The preoperative SUVmax >6.3 or size >2.3 cm of the primary lesions were independent risk factors of peripheral cT1 NSCLC LNM (ORs, 95% CIs were 6.18 (2.40-15.92) and 3.03 (1.35-6.81). The sensitivity, NPV of SUVmax >6.3 or size >2.3 cm of the primary lesions were higher than the traditional PET-CT criterion for predicting LNM (100.0 vs. 86.0%, 100.0 vs. 89.7%). A Hosmer-Lemeshow test showed a goodness-of-fit (P = 0.479). CONCLUSIONS: The excellent sensitivity and NPV of preoperative of the SUVmax >6.3 or size >2.3 cm of the primary lesions based on 18F-FDG PET-CT might identify the patients at low-risk LNM in peripheral cT1 NSCLC.

Tumor-to-liver standard uptake ratio using fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography effectively predict occult lymph node metastasis of non-small cell lung cancer patients.

OBJECTIVES: We aimed to investigate predictive factors of occult lymph node metastasis and to explore the diagnostic value of various standardized uptake value (SUV) parameters using fluorine-18 fluorodeoxyglucose (F-FDG) positron emission tomography computed tomography (PET/CT) in predicting occult lymph node metastasis of clinical N0 non-small cell lung cancer patients. METHODS: We retrospectively analyzed PET/computed tomography parameters of tumor and clinical data of 124 clinical N0 non-small cell lung cancer patients who underwent both preoperative F-FDG PET/computed tomography and anatomical pulmonary resection with systematic lymph node dissections. The SUVmax, SUVmean, metabolic total volume, and total lesion glycolysis of the primary tumor was automatically measured on the PET/computed tomography workstation. Standardized uptake ratio (SUR) were derived from tumor standardized uptake value divided by blood SUVmean (B-SUR) or liver SUVmean (L-SUR), respectively. RESULTS: According to postoperative pathology, 19 (15%) were diagnosed as occult lymph node metastasis among 124 clinical N0 non-small cell lung cancer patients. On univariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, lobulation, and all PET parameters were associated with occult lymph node metastasis. The area under the receiver operating characteristic curve, sensitivity, and negative predictive value of L-SURmax were the highest among all PET parameters (0.778, 94.7%, and 98.4%, respectively). On multivariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax were independent risk factors for predicting occult lymph node metastasis. Compared to L-SURmax alone and the combination of carcinoembryonic antigen and cytokeratin 19 fragment, the model consisting of three independent risk factors achieved a greater area under the receiver operating characteristic curve (0.901 vs. 0.778 vs. 0.780, P = 0.021 and 0.0141). CONCLUSIONS: L-SURmax showed the most powerful predictive performance than the other PET parameters in predicting occult lymph node metastasis. The combination of three independent risk factors (carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax) can effectively predict occult lymph node metastasis in clinical N0 non-small cell lung cancer patients.

Low-grade myofibroblastic sarcoma of gastric cardia on 18F-FDG positron emission tomography/computed tomography: An extremely rare case report.

RATIONALE: Low-grade myofibroblastic sarcoma (LGMS) is a rare mesenchyme-derived tumor, which usually occurs in head, neck (especially tongue and mouth), and limbs. In this report, we described a case of gastric LGMS by F-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT), which has not been reported previously. PATIENT CONCERNS: A 51-year-old female patient was admitted to our hospital with upper abdominal discomfort for 1 year and gradually increased eating difficulties over the last 3 months. From gastroscopy, an ulcer of 1.0 cm × 1.2 cm at the entrance of cardia and stiffness of peripheral mucosa were found, leading to suspicion of cardia cancer. F-FDG PET/CT was performed for further diagnosis and staging. DIAGNOSES: According to pathological findings in combination with immunohistochemical features, diagnosis of gastric LGMS was made. INTERVENTIONS: To relieve symptoms of upper gastrointestinal obstruction in the patient, proximal gastrectomy was carried out 1 week after the F-FDG PET/CT scan. OUTCOMES: The patient died due to advanced tumor. LESSONS: F-FDG PET/CT scan showed local thickening of the gastric wall, invasion of adjacent soft tissue, diaphragmatic and peritoneal metastasis at early stage, absence of regional lymph node metastasis, and increased F-FDG metabolism in primary tumor and metastatic tumor.

Prognostic significance of left ventricular dyssynchrony by phase analysis of gated SPECT in medically treated patients with dilated cardiomyopathy.

PURPOSE: The study aimed to investigate the value of clinical variables and rest gated single-photon emission computed tomography (SPECT) in predicting cardiac deaths in medically treated dilated cardiomyopathy (DCM) patients. METHODS: This is a retrospective study. Fifty-six consecutive hospitalized DCM patients who underwent rest gated SPECT myocardial perfusion imaging were initially recruited. Patients were further excluded for receiving heart transplantation, cardiac resynchronization treatment, and noncardiac death during follow-up. The remaining 48 medically treated DCM patients were selected into the final analysis. Phase analysis of gated SPECT was conducted to identify left ventricular (LV) dyssynchrony. Cardiac death during follow-up was considered as the only endpoint. Univariate and multivariate Cox proportional hazards regression analysis were performed to identify the independent predictors of cardiac death. Kaplan-Meier cumulative survival analysis with stratification was performed, and survival curves were compared by log-rank test. RESULTS: The mean age was 47.5 ± 15.8 years (range, 15-76 yrs) and 85.4% were men. The mean LV ejection fraction was 22.2 ± 7.7%. During the follow-up period (22.7 ± 5.1 mos), 12 (25.0%) cardiac deaths occurred. Compared to survivors, patients with cardiac death had lower body mass index (BMI, P = 0.010), higher percent of prolonged QRS duration (QRSD, P = 0.043), and severe LV dyssynchrony (P = 0.002). Multivariate Cox analysis demonstrated that severe LV dyssynchrony [hazard ratio = 9.607, 95% confidential interval (95% CI) 2.064-44.713, P = 0.004] and BMI (hazard ratio = 0.851, 95% CI 0.732-0.989, P = 0.036) were predictive of cardiac death. CONCLUSION: Left ventricular dyssynchrony assessed by phase analysis of gated SPECT and BMI are predictive of cardiac death in medically treated DCM patients.

Phase analysis by gated F-18 FDG PET/CT for left ventricular dyssynchrony assessment: a comparison with gated Tc-99m sestamibi SPECT.

PURPOSE: To investigate the value of gated F-18 FDG PET/CT on left ventricular (LV) dyssynchrony assessment in comparison with gated Tc-99m sestamibi SPECT in patients with coronary artery disease (CAD). METHODS: The data of 100 consecutive CAD patients who underwent both gated myocardial Tc-99m sestamibi SPECT and F-18 FDG PET/CT imaging were analyzed. Phase standard deviation (SD) and histogram bandwidth (BW) were derived from phase analysis using Cedars software package. The correlation and agreement of SD and BW between Tc-99m sestamibi SPECT and F-18 FDG PET/CT were examined. Myocardial viability and the site of latest activation assessed by the two imaging methods were compared as well. RESULTS: A moderate correlation for SD (r = 0.58, p < 0.0001) and BW (r = 0.60, p < 0.0001) was found between gated SPECT and gated F-18 FDG PET/CT. Bland-Altman analysis revealed an overestimation of SD and BW (6.4° ± 14.3° and 22.0° ± 46.8°) by gated F-18 FDG PET/CT. Multivariate logistic regression analysis identified that significant LV remodeling on SPECT imaging, LV functional parameters and F-18 FDG uptake ratio of myocardium to blood pool (SUVM/B) were associated with the overestimation. Myocardial SPECT and F-18 FDG PET/CT had a 67.1 % identity in determining the latest activation site and 5.2 % more viable myocardium was detected by F-18 FDG PET/CT than SPECT. CONCLUSION: Gated F-18 FDG PET/CT moderately correlated with gated Tc-99m sestamibi SPECT in assessing LV dyssynchrony. Gated F-18 FDG PET/CT phase analysis should be cautiously applied in CAD patients with significant LV remodeling on SPECT imaging, severe LV functional impairment or poor myocardial F-18 FDG uptake.