Faculty Bibliography

AIM: To investigate diagnostic accuracy of high, low and mixed voltage dual energy computed tomography (DECT) for detection of prior myocardial infarction (MI). METHODS: Twenty-four consecutive patients (88% male, mean age 65 +/- 11 years old) with clinically documented prior MI (> 6 mo) were prospectively recruited to undergo late phase DECT for characterization of their MI. Computed tomography (CT) examinations were performed using a dual source CT system (64-slice Definition or 128-slice Definition FLASH, Siemens Healthcare) with initial first pass and 10 min late phase image acquisitions. Using the 17-segment model, regional systolic function was analyzed using first pass CT as normal or abnormal (hypokinetic, akinetic, dyskinetic). Regions with abnormal systolic function were identified as infarct segments. Late phase DE scans were reconstructed into: 140 kVp, 100 kVp, mixed (120 kVp) images and iodine-only datasets. Using the same 17-segment model, each dataset was evaluated for possible (grade 2) or definite (grade 3) late phase myocardial enhancement abnormalities. Logistic regression for correlated data was used to compare reconstructions in terms of the accuracy for detecting infarct segments using late myocardial hyperenhancement scores. RESULTS: All patients reported prior history of documented myocardial infarction, with most occurring more than 5 years prior (n = 18; 75% of cohort). Fifty-five of 408 (13%) segments demonstrated abnormal wall motion and were classified as infarct. The remaining 353 segments were classified as non-infarcted segments. A total of 1692 segments were analyzed for late phase enhancement abnormalities, with 91 (5.5%) segments not interpretable due to artifact. Combined grades 2 and 3 compared to grade 3 only enhancement abnormalities demonstrated significantly higher sensitivity and similar specificity for detection of infarct segments for all reconstructions evaluated. Evaluation of different voltage acquisitions demonstrated the highest diagnostic performance for the 100 kVp reconstruction which had higher diagnostic accuracy (87%; 95%CI: 80%-90%), sensitivity (86%-93%; 95%CI: 54%-78%) and specificity (90%; 95%CI: 86%-93%) compared to the other reconstructions. For sensitivity, there were significant differences noted between 100 kVp vs 140 kVp (P < 0.0005), 100 kVp vs mixed (P < 0.0001), and 100 kVp vs iodine only (P < 0.005) using combined grade 2 and grade 3 perfusion abnormalities. For specificity, there were significant differences noted between 100 kVp vs 140 kVp (P < 0.005), and 100 kVp vs mixed (P < 0.01) using combined grades 2 and 3 perfusion abnormalities. CONCLUSION: Low voltage acquisition CT, 100 kVp in this study, demonstrates superior diagnostic performance when compared to higher and mixed voltage acquisitions for detection of prior MI.

BACKGROUND AND PURPOSE:Along with cortical abnormalities, white matter microstructural changes such as axonal loss and myelin breakdown are implicated in the pathogenesis of Alzheimer disease. Recently, a white matter model was introduced that relates non-Gaussian diffusional kurtosis imaging metrics to characteristics of white matter tract integrity, including the axonal water fraction, the intra-axonal diffusivity, and the extra-axonal axial and radial diffusivities.MATERIALS AND METHODS:This study reports these white matter tract integrity metrics in subjects with amnestic mild cognitive impairment (n = 12), Alzheimer disease (n = 14), and age-matched healthy controls (n = 15) in an effort to investigate their sensitivity, diagnostic accuracy, and associations with white matter changes through the course of Alzheimer disease.RESULTS:With tract-based spatial statistics and region-of-interest analyses, increased diffusivity in the extra-axonal space (extra-axonal axial and radial diffusivities) in several white matter tracts sensitively and accurately discriminated healthy controls from those with amnestic mild cognitive impairment (AUC = 0.82-0.95), while widespread decreased axonal water fraction discriminated amnestic mild cognitive impairment from Alzheimer disease (AUC = 0.84). Additionally, these white matter tract integrity metrics in the body of the corpus callosum were strongly correlated with processing speed in amnestic mild cognitive impairment (r = |0.80-0.82|, P < .001).CONCLUSIONS:These findings have implications for the course and spatial progression of white matter degeneration in Alzheimer disease, suggest the mechanisms by which these changes occur, and demonstrate the viability of these white matter tract integrity metrics as potential neuroimaging biomarkers of the earliest stages of Alzheimer disease and disease progression.

BACKGROUND AND OBJECTIVE: To examine whether clinically benign multiple sclerosis patients (BMS) show similar losses of their global N-acetylaspartate (NAA) neuronal marker relative to more clinically disabled patients of similar disease duration. METHODS: The whole-brain NAA concentration (WBNAA) was acquired with whole-head non-localizing proton MR spectroscopy. Fractional brain parenchymal volume (fBPV), T2 and T1 lesion loads, were obtained from the MRI in: (i) 24 BMS patients: 23.1+/-7.2 years disease duration, median Expanded Disability Status Scale (EDSS) score of 2.0 (range: 0-3); (ii) 26 non-benign MS patients (non-BMS), 24.5+/-7.4 years disease duration, median EDSS of 4.0 (range: 3.5-6.5); (iii) 15 healthy controls. RESULTS: Controls' 12.4+/-2.3mM WBNAA was significantly higher than the BMS's and non-BMS's 10.5+/-2.4 and 9.9+/-2.1mM (both p<0.02), but the difference between the patients' groups was not (p>0.4). Likewise, the controls' 81.2+/-4.5% fBPV exceeded the BMS and non-BMS's 77.0+/-5.8% and 76.3+/-8.6% (p<0.03), which were also not different from one another (p>0.7). BMS patients' T1-hypointense lesion load, 2.1+/-2.2cm(3), was not significantly different than the non-BMS's 4.1+/-5.4cm(3) (p>0.08) and T2-hyperintense loads: 6.0+/-5.7cm(3) and 8.7+/-7.8cm(3), were also not different (p>0.1). CONCLUSIONS: WBNAA differentiates normal controls from MS patients but does not distinguish BMS from more disabled MS patients of similar disease duration. Nevertheless, all MS patients who remain RR for 15+ years suffered WBNAA loss similar to the average RR MS population at fourfold shorter disease duration suggesting relative global neuronal sparing or leveling-off of the neurodegeneration rate.

Purpose: To compare the recently proposed Prostate Imaging Reporting and Data System (PI-RADS) scale that incorporates fixed criteria and a standard Likert scale based on overall impression in prostate cancer localization using multiparametric magnetic resonance (MR) imaging. Materials and Methods: This retrospective study was HIPAA compliant and institutional review board approved. Seventy patients who underwent 3-T pelvic MR imaging, including T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast material-enhanced imaging, with a pelvic phased-array coil before radical prostatectomy were included. Three radiologists, each with 6 years of experience, independently scored 18 regions (12 peripheral zone [PZ], six transition zone [TZ]) using PI-RADS (range, scores 3-15) and Likert (range, scores 1-5) scales. Logistic regression for correlated data was used to compare scales for detection of tumors larger than 3 mm in maximal diameter at prostatectomy. Results: Maximal accuracy was achieved with score thresholds of 8 and higher and of 3 and higher for PI-RADS and Likert scales, respectively. At these thresholds, in the PZ, similar accuracy was achieved with the PI-RADS scale and the Likert scale for radiologist 1 (89.0% vs 88.2%, P = .223) and radiologist 3 (88.5% vs 88.2%, P = .739) and greater accuracy was achieved with the PI-RADS scale than the Likert scale for radiologist 2 (89.6% vs 87.1%, P = .008). In the TZ, accuracy was lower with the PI-RADS scale than with the Likert scale for radiologist 1 (70.0% vs 87.1%, P < .001), radiologist 2 (87.6% vs 92.6%, P = .002), and radiologist 3 (82.9% vs 91.2%, P < .001). For tumors with Gleason score of at least 7, sensitivity was higher with the PI-RADS scale than with the Likert scale for radiologist 1 (88.6% vs 82.6%, P = .032), and sensitivity was similar for radiologist 2 (78.0% vs 76.5, P = .467) and radiologist 3 (77.3% vs 81.1%, P = .125). Conclusion: Radiologists performed well with both PI-RADS and Likert scales for tumor localization, although, in the TZ, performance was better with the Likert scale than the PI-RADS scale. (c) RSNA, 2013 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13122233/-/DC1.

OBJECTIVES: To investigate the impact of prostate computed diffusion-weighted imaging (DWI) on image quality and tumour detection. METHODS: Forty-nine patients underwent 3-T magnetic resonance imaging using a pelvic phased-array coil before prostatectomy, including DWI with b values of 50 and 1,000 s/mm(2). Computed DW images with b value 1,500 s/mm(2) were generated from the lower b-value images. Directly acquired b-1,500 DW images were obtained in 39 patients. Two radiologists independently assessed DWI for image quality measures and location of the dominant lesion. A third radiologist measured tumour-to-peripheral-zone (PZ) contrast. Pathological findings from prostatectomy served as the reference standard. RESULTS: Direct and computed b-1,500 DWI showed better suppression of benign prostate tissue than direct b-1,000 DWI for both readers (P /= 0.180). Tumour-to-PZ contrast was greater on computed b-1,500 than on either direct DWI set (P < 0.001). CONCLUSION: Computed DWI of the prostate using b value >/=1,000 s/mm(2) improves image quality and tumour detection compared with acquired standard b-value images. KEY POINTS: * Diffusion weighted MRI is increasingly used for diagnosing and assessing prostate carcinoma. * Prostate computed DWI can extrapolate high b-value images from lower b values. * Computed DWI provides greater suppression of benign tissue than lower b-value images. * Computed DWI provides less distortion and artefacts than images using same b value. * Computed DWI provides better diagnostic performance than lower b-value images.

OBJECTIVES: To evaluate the image quality of T1-weighted fat-suppressed breast MRI at 7 T and to compare 7-T and 3-T images. METHODS: Seventeen subjects were imaged using a 7-T bilateral transmit-receive coil and 3D gradient echo sequence with adiabatic inversion-based fat suppression (FS). Images were graded on a five-point scale and quantitatively assessed through signal-to-noise ratio (SNR), fibroglandular/fat contrast and signal uniformity measurements. RESULTS: Image scores at 7 and 3 T were similar on standard-resolution images (1.1 x 1.1 x 1.1-1.6 mm(3)), indicating that high-quality breast imaging with clinical parameters can be performed at 7 T. The 7-T SNR advantage was underscored on 0.6-mm isotropic images, where image quality was significantly greater than at 3 T (4.2 versus 3.1, P