Psychometric validation of an adaptation of the Penn Alcohol Craving Scale to assess aggregated drug craving.

PURPOSE: Clinicians need a broad spectrum measurement of psychoactive substance craving (i.e., alcohol and/or drug) to assess collective treatment effects, especially in the context of polysubstance use. In three separate studies, we investigated the psychometric properties of an adapted version of the Penn Alcohol Craving Scale (PACS), designed to measure broad range substance craving. DESIGN: In Study One, we examined the latent factor structure for craving, as well as concurrent validity with measures of frequency and severity of substance use. In Study Two, we examined the short-term test-retest reliability. In Study Three, we examined the long-term sensitivity to treatment effects at 12 month postdischarge. SETTING: An inpatient SUD program in Guelph, Ontario, Canada. PARTICIPANTS: Adult patients receiving treatment for SUD: Study One, n = 971; Study Two, n = 35; Study Three, n = 191. MEASUREMENTS: We used an adapted version of the PACS, termed the Aggregated Drug Craving Scale (ADCS), and measures of substance use frequency, severity, and abstinence. FINDINGS: In Study One, confirmatory factor analysis supported the unidimensional structure of the craving scale (CFI: 0.994, RMSEA: 0.071, SRMR: 0.010). In addition, statistically significant, medium effect size associations provided evidence of concurrent validity with measures of substance use frequency and severity (CFI = 0.992; RMSEA = 0.054; SRMR = 0.015). In Study Two, the ADCS demonstrated good agreement over two time points (ICC = 0.82), exhibiting acceptable short-term retest reliability. In Study 3, the mean craving score decreased significantly from 19.6 at baseline to 7.5 at 12-month follow-up (t = -18.48, p < 0.001), demonstrating an ability to detect long-term sensitivity to treatment effects (Cohen's d = -1.54). CONCLUSIONS: Together, these findings provide initial support for a concise, broad-spectrum measure of aggregated drug cravings among an SUD treatment population.

Fractional ventilation mapping using inert fluorinated gas MRI in rat models of inflammation and fibrosis.

The purpose of this study was to extend established methods for fractional ventilation mapping using (19) F MRI of inert fluorinated gases to rat models of pulmonary inflammation and fibrosis. In this study, five rats were instilled with lipopolysaccharide (LPS) in the lungs two days prior to imaging, six rats were instilled with bleomycin in the lungs two weeks prior to imaging and an additional four rats were used as controls. (19) F MR lung imaging was performed at 3 T with rats continuously breathing a mixture of sulfur hexafluoride and O2 . Fractional ventilation maps were obtained using a wash-out approach, by switching the breathing mixture to pure O2 , and acquiring images following each successive wash-out breath. The mean fractional ventilation (r) was 0.29 ± 0.05 for control rats, 0.23 ± 0.10 for LPS-instilled rats and 0.19 ± 0.03 for bleomycin-instilled rats. Bleomycin-instilled rats had a significantly decreased mean r value compared with controls (P = 0.010). Although LPS-instilled rats had a slightly reduced mean r value, this trend was not statistically significant (P = 0.556). Fractional ventilation gradients were calculated in the anterior/posterior (A/P) direction, and the mean A/P gradient was -0.005 ± 0.008 cm(-1) for control rats, 0.013 ± 0.005 cm(-1) for LPS-instilled rats and 0.009 ± 0.018 cm(-1) for bleomycin-instilled rats. Fractional ventilation gradients were significantly different for control rats compared with LPS-instilled rats only (P = 0.016). The ventilation gradients calculated from control rats showed the expected gravitational relationship, while ventilation gradients calculated from LPS- and bleomycin-instilled rats showed the opposite trend. Histology confirmed that LPS-instilled rats had a significantly elevated alveolar wall thickness, while bleomycin-instilled rats showed signs of substantial fibrosis. Overall, (19)F MRI may be able to detect the effects of pulmonary inflammation and fibrosis using a simple and inexpensive imaging approach that can potentially be translated to humans.