The phantom study showed that CBCT provides limited quantitative CT values for each pixel on sliced images for differentiating air, water and soft tissues. However, the measurement of air spaces with CBCT was quite accurate.

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Cone-beam CT (CBCT) systems specifically designed for hard-tissue imaging of the maxillofacial region have recently become commercially available. The newly-developed CBCT system, CB Throne ® (Hitachi Medical Corp., Tokyo), is characterized by a number of features such as low dose, sub-millimeter spatial resolution, and a small footprint. This system has been clinically applied at Chiba Hospital, Tokyo Dental College, since April 2005. This article reports the characteristics of this system, and its diagnostic power for maxillofacial lesions and the pre-operative planning dental implants.

Background:We explored the usefulness of myocardial strain analysis on cardiac magnetic resonance imaging (CMR) scans for the identification of cardiac amyloidosis. Methods and Results:The 61 patients with systemic amyloidosis underwent 3.0-T CMR, including CMR tagging and late-gadolinium enhanced (LGE) imaging. The circumferential strain (CS) of LGE-positive and LGE-negative patients was measured on midventricular short-axis images and compared. Logistic regression modeling of CMR parameters was performed to detect patients with LGE-positive cardiac amyloidosis. Of the 61 patients with systemic amyloidosis 48 were LGE-positive and 13 were LGE-negative. The peak CS was significantly lower in the LGE-positive than in the LGE-negative patients (−9.5±2.3 vs. −13.3±1.4%, P<0.01). The variability in the peak CS time was significantly greater in the LGE-positive than in the LGE-negative patients (46.1±24.5 vs. 21.2±20.1 ms, P<0.01). The peak CS significantly correlated with clinical biomarkers. The sensitivity, specificity, and accuracy of the diagnostic model using CS parameters for the identification of LGE-positive amyloidosis were 93.8%, 76.9%, and 90.2%, respectively. Conclusions:Myocardial strain analysis by CMR helped detect LGE-positive amyloidosis without the need for contrast medium. The peak CS and variability in the peak CS time may correlate with the severity of cardiac amyloid deposition and may be more sensitive than LGE imaging for the detection of early cardiac disease in patients with amyloidosis.

We conclude that SVV, as displayed on the Vigileo monitor, is an accurate predictor of intravascular hypovolemia and is a useful indicator for assessing the appropriateness and timing of applying fluid for improving circulatory stability during the perioperative period after esophagectomy.

Objectives Streak artifacts that appear on dental and maxillofacial X-ray computed tomography (CT) images are mainly caused by the presence of metallic prosthetic appliances. Because of the design of common CT hardware, the thin slice thickness method is routinely used in CT examinations of the dento-alveolar region. Thus, within the resulting collection of thin slice images, adjacent CT images will often depict very similar anatomical structures. We took advantage of this aspect and employed iterative correction to reduce the streak artifact caused by metallic materials. Methods The maximum likelihood-expectation maximization (ML-EM) reconstruction algorithm, a type of statistical reconstruction method, was applied to multidetector CT images. The ML-EM is an iterative restoration method that approximates between the processed image and the original projection data. In our study, we processed slices with heavy streak artifacts by using the projection data of an adjacent CT image without any major artifacts. Because the adjacent slices depicted very similar anatomical structures, they became the target of the proposed processing. Thus, the processing is essentially an iterative correction. Results The iterative correction was carried out 50 times. Processed images at the initial stage were blurred, but some streak artifacts clearly disappeared as the iteration progressed.Conclusions An ML-EM reconstruction algorithm can be used to modify iterative correction to reduce streak artifacts in dental and maxillofacial CT images. We used an image that contained heavy artifacts in our study, and after 50 iterative correction cycles, only a few weak artifacts remained on the processed image. The final image produced by our iterative correction method depicted clear anatomical structures and developed only marginal deviations from the original image.

Background-We have sometimes noted abnormal angiographic coronary dilatation, <50% of the reference vessel, at the site of sirolimus-eluting stent implantation, suggesting contrast staining outside the stent struts and named this finding peri-stent contrast staining (PSS

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