Monitoring of neoadjuvant chemotherapy using multiparametric, <Superscript>23</Superscript>Na sodium MR,and multimodality (PET/CT/MRI) imaging in locally advanced breast cancer

We prospectively investigated using advanced magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) to identify radiological biomarkers for treatment response in patients receiving preoperative systemic therapy (PST) for locally advanced breast cancer. Patients with a stage II or III breast cancer receiving PST were selected and underwent positron emission tomography (PET), magnetic resonance imaging (MRI), and breast biopsies at baseline and after the first cycle of PST (days 7–8) during the full course of treatment. PET/CT was acquired after injection of 2-deoxy-2-[18F]-fluoro-d-glucose (¹⁸FDG, 0.22 mCi/kg) and quantified with standardized uptake value assessment (SUV). Diagnostic breast MRI and sodium (²³Na) was acquired at 1.5 T. Total tissue sodium concentration (TSC), response criteria in solid tumors (RECIST), and volumes were quantified. Treatment response was determined by pathological assessment at surgery. Immunohistochemistry values of the proliferative index (Ki-67) were performed on biopsy specimens. Six of nineteen eligible women (43 ± 11 years) who received PST underwent radiological imaging of ¹⁸FDG-PET/CT and MRI for at least two cycles of treatment. Five patients had a pathological partial response (pPR) and one had pathological non-response (pNR). TSC decreased 21% in responders with increases in the non-responder (P = 0.03). Greater reduction in SUV was observed in responders (38%) compared to the non-responder (22%; P = 0.03). MRI volumes decreased after cycle 1 by 42% (responders) and 35% (non-responder; P = 0.11). Proliferation index Ki-67 declined in responders in the first cycle (median = 47%, range = 29–20%), but increased (4%) in the non-responder. Significant decreases in TSC, SUV, and Ki-67 were observed in responders with increases in TSC and Ki-67 in non-responders. Our results demonstrate the feasibility of using multi-modality proton, ²³Na MRI, and PET/CT metrics as radiological biomarkers for monitoring response to PST in patients with operable breast cancer.     

A comparison of prospective and retrospective respiratory navigator gating in 3D MR coronary angiography

A comparison between the prospective and retrospective respiratory navigator gating in MR coronary angiography was performed with eight normal subjects. A three-dimensional (3D) ECG-gated fast gradient echo pulse sequence was used for image data acquisition. The results show that the MR coronary angiography obtained using retrospective gating retains a considerable amount of motion artifacts. In this study, the images acquired using prospective navigator gating demonstrated significantly reduced motion artifacts (p = 0.009), improved vessel visibility (p = 0.021) with reduced imaging time (p = 0.013) compared to the images obtained using retrospective navigator gating.     

Photon-Counting CT of the Brain: In Vivo Human Results and Image-Quality Assessment

BACKGROUND AND PURPOSE:Photon-counting detectors offer the potential for improved image quality for brain CT but have not yet been evaluated in vivo. The purpose of this study was to compare photon-counting detector CT with conventional energy-integrating detector CT for human brains.MATERIALS AND METHODS:Radiation dose–matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 human asymptomatic volunteers (mean age, 58.9 ± 8.5 years). Photon-counting detector thresholds were 22 and 52 keV (low-energy bin, 22–52 keV; high-energy bin, 52–120 keV). Image noise, gray matter, and white matter signal-to-noise ratios and GM–WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Reproducibility was assessed with the intraclass correlation coefficient. Energy-integrating detector and photon-counting detector CT images were compared using a paired t test and the Wilcoxon signed rank test.RESULTS:Photon-counting detector CT images received higher reader scores for GM–WM differentiation with lower image noise (all P < .001). Intrareader and interreader reproducibility was excellent (intraclass correlation coefficient, ≥0.86 and 0.79, respectively). Quantitative analysis showed 12.8%–20.6% less image noise for photon-counting detector CT. The SNR of photon-counting detector CT was 19.0%–20.0% higher than of energy-integrating detector CT for GM and WM. The contrast-to-noise ratio of photon-counting detector CT was 15.7% higher for GM–WM contrast and 33.3% higher for GM–WM contrast-to-noise ratio.CONCLUSIONS:Photon-counting detector brain CT scans demonstrated greater gray–white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.

Brain CT remains the first-line technique of choice for the evaluation of traumatic and nontraumatic brain injury and is the most-often-performed CT examination in many emergency departments.^1,2 However, there is limited gray matter–white matter differentiation with brain CT, decreasing the ability to assess the hypoattenuation and loss of GM–WM differentiation seen in early ischemic brain changes.^3,4 In addition, beam-hardening artifacts due to attenuation by the skull of lower energy photons degrade brain CT diagnostic image quality, potentially mimicking intracranial hemorrhage and reducing GM–WM differentiation.⁵The energy spectrum of x-ray tubes for CT is usually characterized by the peak kilovoltage, but the applied x-ray spectrum consists of a wide distribution of lower energy photons. Conventional CT uses energy-integrating detectors (EIDs) to combine the effects of x-ray photon number and photon energy into an intensity value through conversion of x-rays to light photons to electrical pulses. Consequently, with EID CT, low-energy photons (eg, 40–70 keV) have less contribution to the CT intensity value than high-energy photons (eg, 110–140 keV). For brain imaging however, it is these low-energy photons that have better soft-tissue discrimination for identification of gray–white matter contrast.Photon-counting detectors (PCDs) are a new technology for CT imaging that directly converts x-ray photons into electrical pulses. PCDs measure the number of detected x-ray photons (ie, photon count) and their photon energy.^6–11 These characteristics allow equal weighting of low- and high-energy photons and may therefore be useful for improving soft-tissue contrast in the brain.⁸ In addition, the direct conversion and counting of individual photons provide a better estimate of the underlying photon statistics, which, in turn, may improve image quality by reducing image noise.^8,12–14 We hypothesized that the combined effects of better contrast and reduced noise may lead to better overall GM–WM differentiation in brain PCD CT.To date, PCD CT scanning of a cadaver head¹⁵ has suggested the feasibility of PCD for brain CT, but in vivo results have not been previously studied, to our knowledge. Thus, the purpose of the current study was to compare the image quality of PCD with that of conventional EID for human brain CT.     

Assessment of acute myocardial infarction: current status and recommendations from the North American society for cardiovascular imaging and the European society of cardiac radiology

There are a number of imaging tests that are used in the setting of acute myocardial infarction and acute coronary syndrome. Each has their strengths and limitations. Experts from the European Society of Cardiac Radiology and the North American Society for Cardiovascular Imaging together with other prominent imagers reviewed the literature. It is clear that there is a definite role for imaging in these patients. While comparative accuracy, convenience and cost have largely guided test decisions in the past, the introduction of newer tests is being held to a higher standard which compares patient outcomes. Multicenter randomized comparative effectiveness trials with outcome measures are required.     

Left ventricular papillary muscle mass: relationship to left ventricular mass and volumes by magnetic resonance imaging

OBJECTIVE: To evaluate the effect of papillary muscle mass on the calculation of left ventricular (LV) function and mass and to determine the relationship between papillary muscle mass with body size and sex. METHODS: Cardiac magnetic resonance imaging examinations from 50 men and 50 women were randomly selected from the Multi-Ethnic Study of Atherosclerosis database. The contours of the papillary muscles were traced manually, and the LV wall contours were outlined semiautomatically based on short-axis images. Papillary muscle mass, LV mass, and volumes were calculated. RESULTS: Inclusion of the papillary muscles results in significantly higher total LV mass values (P<0.001) and lower end-diastolic volume values (P<0.001) compared with measurements excluding papillary muscles from the LV mass. Papillary muscle mass accounts for 8.9% of the total LV mass and is correlated with LV wall mass (r=0.81, P<0.001). CONCLUSION: Papillary muscle mass significantly affects LV volumes and mass determined by cine magnetic resonance imaging.     

3D left ventricular extracellular volume fraction by low-radiation dose cardiac CT: Assessment of interstitial myocardial fibrosis

BackgroundMyocardial fibrosis leads to impaired cardiac function and events. Extracellular volume fraction (ECV) assessed with an iodinated contrast agent and measured by cardiac CT may be a useful noninvasive marker of fibrosis.ObjectiveThe purpose of this study was to develop and evaluate a 3-dimensional (3D) ECV calculation toolkit (ECVTK) for ECV determination by cardiac CT.MethodsTwenty-four subjects (10 systolic heart failure, age, 60 ± 17 years; 5 diastolic failure, age 56 ± 20 years; 9 matched healthy subjects, age 59 ± 7 years) were evaluated. Cardiac CT examinations were done on a 320-multidetector CT scanner before and after 130 mL of iopamidol (Isovue-370; Bracco Diagnostics, Plainsboro, NJ, USA) was administered. A calcium score type sequence was performed before and 7 minutes after contrast with single gantry rotation during 1 breath hold and single cardiac phase acquisition. ECV was calculated as (ΔHU_myocardium/ΔHU_blood) × (1 ? Hct) where Hct is the hematocrit, and ΔHU is the change in Hounsfield unit attenuation = HU_{after iodine} ? HU_{before iodine}. Cardiac magnetic resonance imaging was performed to assess myocardial structure and function.ResultsMean 3D ECV values were significantly higher in the subjects with systolic heart failure than in healthy subjects and subjects with diastolic heart failure (mean, 41% ± 6%, 33% ± 2%, and 35% ± 5%, respectively; P = 0.02). Interobserver and intraobserver agreements were excellent for myocardial, blood pool, and ECV (intraclass correlation coefficient, >0.90 for all). Higher 3D ECV by cardiac CT was associated with reduced systolic circumferential strain, greater end-diastolic and -systolic volumes, and lower ejection fraction (r = 0.70, r = 0.60, r = 0.73, and r = ?0.68, respectively; all P < 0.001).Conclusion3D ECV by cardiac CT can be performed with ECVTK. We demonstrated increased ECV in subjects with systolic heart failure compared with healthy subjects. Cardiac CT results also showed good correlation with important functional heart biomarkers, suggesting the potential for myocardial tissue characterization with the use of 3D ECV by cardiac CT. This trial is registered at www.ClinicalTrials.gov as NCT01160471.     

膳食模式与动脉粥样硬化关系的多种族研究

目的人们对膳食模式、代谢紊乱与左心室功能的关系研究报道不多,本研究旨在探讨膳食模式和左心室功能之间的关系以及代谢紊乱与动脉粥样硬化的关系。方法膳食模式采用降秩回归（reduced rankregression,RRR）方法构建;左室重量、心搏量和左室射血分数采用磁共振成像测量;膳食模式和左室指数之间的关系采用横断面分析法。结果选用4601例45～84岁、无临床心血管疾病受试者,RRR膳食模式得分数与高血糖指数、高脂肉类、奶酪、加工食品的摄人量呈正相关,而与蔬菜、大豆、水果、绿茶、黑茶、低脂甜点、种子、坚果和鱼肉的低摄入量呈负相关。多变量分析显示,RRR膳食模式得分增加1个单位,左室重量／体表面积就增加0．32g／ ㎡,心博量减少0．43mL／㎡,左室射血分数则减少0．21％。调整代谢综合征组分后,RRR膳食模式得分与左室重量和心搏指数之间的相关性减低,变为差异有统计学意义（P％0．05）。结论RRR膳食模式、代谢紊乱与左室功能紊乱有关。本研究属于横断面研究,结果的可靠性有待前瞻性研究进一步证实。     

Magnetic resonance imaging of the breast prior to biopsy

Context  Breast magnetic resonance imaging (MRI) has been shown to have high sensitivity for cancer detection and is increasingly used following mammography to evaluate suspicious breast lesions. Objective  To determine the accuracy of breast MRI in conjunction with mammography for the detection of breast cancer in patients with suspicious mammographic or clinical findings. Design, Setting, and Patients  Prospective multicenter investigation of the International Breast MR Consortium conducted at 14 university hospitals in North America and Europe from June 2, 1998, through October 31, 2001, of 821 patients referred for breast biopsy for American College of Radiology category 4 or 5 mammographic assessment or suspicious clinical or ultrasound finding. Interventions  MRI examinations performed prior to breast biopsy; MRI results were interpreted at each site, which were blinded to pathological results. Main Outcome Measures  Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of breast MRI. Results  Among the 821 patients, there were 404 malignant index lesions, of which 63 were ductal carcinoma in situ (DCIS) and 341 were invasive carcinoma. Of the 417 nonmalignant index lesions, 366 were benign, 47 showed atypical histology, and 4 were lobular carcinoma in situ. The AUC pooled over all institutions was 0.88 (95% confidence interval [CI], 0.86-0.91). MRI correctly detected cancer in 356 of 404 cancer cases (DCIS or invasive cancer), resulting in a sensitivity of 88.1% (95% CI, 84.6%-91.1%), and correctly identified as negative for cancer 281 of 417 cases without cancer, resulting in a specificity of 67.7% (95% CI, 62.7%-71.9%). MRI performance was not significantly affected by mammographic breast density, tumor histology, or menopausal status. The positive predictive values for 356 of 492 patients was 72.4% (95% CI, 68.2%-76.3%) and of mammography for 367 of 695 patients was 52.8% (95% CI, 49.0%-56.6%) (P<.005). Dynamic MRI did not improve the AUC compared with 3-dimensional MRI alone, but the specificity of a washout pattern for 123 of 136 patients without cancer was 90.4% (95% CI, 84%-95%). Conclusions  Breast MRI has high sensitivity but only moderate specificity independent of breast density, tumor type, and menopausal status. Although the positive predictive value of MRI is greater than mammography, MRI does not obviate the need for subsequent tissue sampling in this setting.