Exercise-rest Tc-99m tetrofosmin SPECT in patients with chronic ischemic left ventricular dysfunction: Direct comparison with Tl-201 reinjection

Background. This study was designed to compare the results of exercise-rest technetium-99m tetrofosmin single photon emission computed tomography (SPECT) with those of thallium-201 reinjection at rest after exercise-redistribution imaging in the same patients with chronic ischemic left ventricular (LV) dysfunction. Methods. Within 1 week, 33 patients with chronic myocardial infarction and LV dysfunction underwent exercise-rest tetrofosmin SPECT and Tl-201 reinjection at rest after exercise-redistribution imaging. In each patient, regional tetrofosmin and Tl-201 activity was quantitatively measured in 22 myocardial segments. Regional LV function was assessed in corresponding segments by echocardiography. Results. Agreement in the evaluation of regional perfusion status between tetrofosmin and Tl-201 imaging was observed in 78% of the 726 total segments, with a κ value of 0.61. In segments with normal function at echocardiography (n = 436), no difference between Tl-201 and tetrofosmin uptake was observed. In hypokinetic segments (n = 138), exercise tetrofosmin uptake was lower (P < .01) as compared with exercise Tl-201 activity, whereas no difference was observed between tetrofosmin uptake at rest as compared with Tl-201 activity on redistribution and reinjection images. In segments with severe functional impairment (akinetic or dyskinetic, n = 152), tetrofosmin uptake on exercise images was reduced (P < .01) as compared with exercise Tl-201 activity; furthermore, tetrofosmin uptake at rest was lower (P < .01) as compared with Tl-201 activity on both redistribution and reinjection images. In these segments, concordance in the detection of myocardial viability between tetrofosmin and Tl-201 imaging was observed in 138 (91%) of the 152 segments, with a κ value of 0.77. Conclusions. In patients with chronic coronary artery disease and LV dysfunction quantitative exercise-rest tetrofosmin and Tl-201 reinjection SPECT provide similar information in the assessment of perfusion status and in the detection of myocardial viability

Metallic elements in exhaled breath condensate of patients with interstitial lung diseases

Epidemiological data support the hypothesis that environmental and occupational agents play an important role in the development of interstitial lung diseases such as idiopathic interstitial pneumonia (IIPs) and sarcoidosis. The aim of this study was to assess the elemental composition of exhaled breath condensate (EBC) in patients with interstitial lung diseases (ILDs) of unknown etiology and healthy subjects as an indirect evaluation of tissue burden, which could improve our understanding of the role of metals in the pathogenesis of ILDs. EBC was obtained from 33 healthy subjects, 22 patients with sarcoidosis, 15 patients with non-specific interstitial pneumonia (NSIP) and 19 with IIPs. Trace elements and toxic metals in the samples were measured by means of inductively coupled plasma-mass spectrometry. There are only small overall differences in the EBC levels of a number of metallic elements among patients with idiopathic pulmonary fibrosis (IPF), NSIP or sarcoidosis, and no pattern is capable of distinguishing them with a high degree of sensitivity and specificity. However, a pattern of pneumotoxic (Si, Ni) and essential elements (Zn, Se and Cu) with the addition of Co distinguished the patients with ILDs from healthy non-smokers with relatively high degrees of sensitivity (96.4%) and specificity (90.9%). Assessing the elemental composition of EBC in patients with different ILDs seems to provide useful information. The non-invasiveness of the EBC method makes it suitable for patients with pulmonary diseases, although further studies are required to confirm the usefulness of this approach and to better understand the underlying pathophysiological processes

Bosentan treatment for Raynauds phenomenon and skin fibrosis in patients with Systemic Sclerosis and pulmonary arterial hypertension: an open-label, observational, retrospective study.

Raynaud's phenomenon (RP) and cutaneous fibrosis are the distinctive manifestations of scleroderma, in which Endothelin-1 plays a fundamental pathogenetic role. Bosentan, an Endothelin-1 receptor antagonist used for the treatment of pulmonary arterial hypertension, retards the beginning of new sclerodermic digital ulcers (DU). This open-label, observational, retrospective study verified the effect of Bosentan on RP and skin fibrosis in sclerodermic outpatients affected by pulmonary arterial hypertension without DU. Fourteen subjects (13 women, 1 man; mean age 60 ± 7.5 years; ten with limited and four with diffuse scleroderma) were observed at baseline (T0) and after four (T1), twelve (T2), twenty-four (T3) and forty-eight (T4) weeks during treatment with Bosentan. They were evaluated for daily quantity and duration of RP attacks and skin thickness (using modified Rodnan total skin score, MRSS). Videocapillaroscopic evaluation was performed at TO and T4. Bosentan decreased significantly the number and duration of RP attacks, beginning at T2 (p<0.05). Videocapillaroscopy showed significant improvement of microcirculatory patterns at T4 (p<0.05). MRSS decreased throughout the study, reaching the statistical significance at T3 and T4 (p<0.01) in the whole cohort. The present data suggest that Bosentan is effective in stabilmng the microcirculation involvement and in improving skin fibrosis irrespective of scleroderma patterns

Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging

PURPOSE Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%). RESULTS Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference). CONCLUSIONS Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone

Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning:a retrospective observational study

BACKGROUND: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal results. We evaluated whether unsupervised machine learning could identify unique phenotypes among patients with normal scans and whether those phenotypes were associated with risk of death or myocardial infarction.METHODS: Patients from a large international multicenter MPI registry (10 sites) with normal perfusion by expert visual interpretation were included in this cohort analysis. The training population included 9849 patients, and external testing population 12,528 patients. Unsupervised cluster analysis was performed, with separate training and external testing cohorts, to identify clusters, with four distinct phenotypes. We evaluated the clinical and imaging features of clusters and their associations with death or myocardial infarction.FINDINGS: Patients in Clusters 1 and 2 almost exclusively underwent exercise stress, while patients in Clusters 3 and 4 mostly required pharmacologic stress. In external testing, the risk for Cluster 4 patients (20.2% of population, unadjusted hazard ratio [HR] 6.17, 95% confidence interval [CI] 4.64-8.20) was higher than the risk associated with pharmacologic stress (HR 3.03, 95% CI 2.53-3.63), or previous myocardial infarction (HR 1.82, 95% CI 1.40-2.36).INTERPRETATION: Unsupervised learning identified four distinct phenotypes of patients with normal perfusion scans, with a significant proportion of patients at very high risk of myocardial infarction or death. Our results suggest a potential role for patient phenotyping to improve risk stratification of patients with normal imaging results.FUNDING: This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R35HL161195 to PS]. The REFINE SPECT database was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R01HL089765 to PS]. MCW was supported by the British Heart Foundation [FS/ICRF/20/26002].</p