Computed tomography is vulnerable to a wide variety of artifacts, including patient- and technique-specific artifacts, some of which are unique to imaging of the heart. Motion is the most common source of artifacts and can be caused by patient, cardiac, or respiratory motion. Cardiac motion artifacts can be reduced by decreasing the heart rate and variability and the duration of data acquisition; adjusting the placement of the data window within a cardiac cycle; performing single-heartbeat scanning; and using multisegment reconstruction, motion-correction algorithms, and electrocardiographic editing. Respiratory motion artifacts can be minimized with proper breath holding and shortened scan duration. Partial volume averaging is caused by the averaging of attenuation values from all tissue contained within a voxel and can be reduced by improving the spatial resolution, using a higher x-ray energy, or displaying images with a wider window width. Beam-hardening artifacts are caused by the polyenergetic nature of the x-ray beam and can be reduced by using x-ray filtration, applying higher-energy x-rays, altering patient position, modifying contrast material protocols, and applying certain reconstruction algorithms. Metal artifacts are complex and have multiple causes, including x-ray scatter, underpenetration, motion, and attenuation values that exceed the typical dynamic range of Hounsfield units. Quantum mottle or noise is caused by insufficient penetration of tissue and can be improved by increasing the tube current or peak tube potential, reconstructing thicker sections, increasing the rotation time, using appropriate patient positioning, and applying iterative reconstruction algorithms. RSNA, 2016.

OBJECTIVEManagement of diabetic foot infection (DFI) has been hampered by limited means of accurately classifying disease severity. New hybrid nuclear/computed tomography (CT) imaging techniques elucidate a combination of wound infection parameters not previously evaluated as outcome prognosticators. Our aim is to determine if a novel standardized hybrid image–based scoring system, Composite Severity Index (CSI), has prognostic value in DFI.RESEARCH DESIGN AND METHODSMasked retrospective 99mTc-white blood cell (WBC) single photon emission CT (SPECT)/CT image interpretation and independent chart review of 77 patients (101 feet) suspected of DFI-associated osteomyelitis at a large municipal hospital between January 2007 and July 2009. CSI scores were correlated with probability of favorable outcome (no subsequent amputation/readmission after therapeutic intervention) during median 342-day follow-up.RESULTSCSI ranged from 0–13. Receiver operating characteristic accuracy for predicting favorable outcome was 0.79 (optimal cutoff CSI, ≤2; odds ratio of therapeutic failure for CSI >2, 15.1 [95% CI 4.4–51.5]). CSI of 0 had a 92% chance of favorable outcome, which fell progressively to 25% as indices rose to ≥7. Image-based osteomyelitis versus no osteomyelitis assessment was less accurate than CSI at predicting outcome (P = 0.016). In patients with intermediate severity (CSI 3–6), treatment failure decreased from 68 to 36% when antibiotic duration was extended to ≥42 days (P = 0.026).CONCLUSIONS99mTc-WBC SPECT/CT hybrid image–derived wound infection parameters incorporated into a standardized scoring system, CSI, has prognostic value in DFI.

Simulation-based training improves overall procedure time, number of skin punctures and needle adjustments, and subjective performance.

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