Strategies for radiation-dose reduction and image-quality optimization in multidetector computed tomographic coronary angiography

Using imaging modalities to predict nanoparticle distribution and treatment efficacy in solid tumors: The growing role of ultrasound

Nanomedicine in oncology has not had the success in clinical impact that was anticipated in the early stages of the field's development. Ideally, nanomedicines selectively accumulate in tumor tissue and reduce systemic side effects compared to traditional chemotherapeutics. However, this has been more successful in preclinical animal models than in humans. The causes of this failure to translate may be related to the intra- and inter-patient heterogeneity of the tumor microenvironment. Predicting whether a patient will respond positively to treatment prior to its initiation, through evaluation of characteristics like nanoparticle extravasation and retention potential in the tumor, may be a way to improve nanomedicine success rate. While there are many potential strategies to accomplish this, prediction and patient stratification via noninvasive medical imaging may be the most efficient and specific strategy. There have been some preclinical and clinical advances in this area using MRI, CT, PET, and other modalities. An alternative approach that has not been studied as extensively is biomedical ultrasound, including techniques such as multiparametric contrast-enhanced ultrasound (mpCEUS), doppler, elastography, and super-resolution processing. Ultrasound is safe, inexpensive, noninvasive, and capable of imaging the entire tumor with high temporal and spatial resolution. In this work, we summarize the in vivo imaging tools that have been used to predict nanoparticle distribution and treatment efficacy in oncology. We emphasize ultrasound imaging and the recent developments in the field concerning CEUS. The successful implementation of an imaging strategy for prediction of nanoparticle accumulation in tumors could lead to increased clinical translation of nanomedicines, and subsequently, improved patient outcomes. This article is categorized under: Diagnostic Tools In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery Emerging Technologies.

Performance of ultra-low-dose CT for the evaluation of coronary calcification: a direct comparison with coronary calcium score

AIM

To evaluate the diagnostic performance of ultra-low-dose computed tomography (ULDCT) in comparison to standard coronary calcium score (CCS) acquisition for the evaluation of coronary artery calcification (CAC).

MATERIALS AND METHODS

Standard CCS acquisition and ULDCT were performed in patients referred for coronary CT angiography for the evaluation of coronary artery disease. CAC in ULDCT was graded subjectively using a four-point scale (from 0, no calcification, to 3, severe calcification) for the complete study and for each individual coronary segment. The summation of all individual coronary segment scores generated an ULDCT total CAC score. ULDCT results were compared to standard Agatston score and sensitivity and specificity of ULDCT were calculated.

RESULTS

CCS and ULDCT were performed in 74 patients, with a mean DLP of 77.7 mGy·cm (±12.1) and 9.3 mGy·cm (±0.6), respectively (p<0.001). Coronary calcification was detected in 47 patients (63.5%) in standard CCS acquisition (median Agatston score of 41; interquartile range [IQR]:0263), in comparison to 42 patients (56.8%) in ULDCT (p<0.001). The sensitivity and specificity of the ULDCT total CAC score ≥1 was 80.9% and 85.2%, respectively, with an accuracy of 82.4%. The area under the receiver operating characteristic curve for the presence of CAC was 0.87.

CONCLUSION

ULDCT shows good sensitivity, specificity, and overall accuracy for the detection of coronary calcification with a markedly lower radiation dose in comparison to CCS. ULDCT is unlikely to miss coronary calcification in individuals with at least moderate calcium load (Agatston score >100).

Reduced exposure using asymmetric cone beam processing for wide area detector cardiac CT

The purpose of this study was to estimate dose reduction after implementation of asymmetrical cone beam processing using exposure differences measured in a water phantom and a small cohort of clinical coronary CTA patients. Two separate 320 × 0.5 mm detector row scans of a water phantom used identical cardiac acquisition parameters before and after software modifications from symmetric to asymmetric cone beam acquisition and processing. Exposure was measured at the phantom surface with Optically Stimulated Luminescence (OSL) dosimeters at 12 equally spaced angular locations. Mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at the center plus four peripheral locations in the water phantom. To assess image quality, mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at five points within the water phantom. Retrospective evaluation of 64 patients (37 symmetric; 27 asymmetric acquisition) included clinical data, scanning parameters, quantitative plus qualitative image assessment, and estimated radiation dose. In the water phantom, the asymmetric cone beam processing reduces exposure by approximately 20% with no change in image quality. The clinical coronary CTA patient groups had comparable demographics. The estimated dose reduction after implementation of the asymmetric approach was roughly 24% with no significant difference between the symmetric and asymmetric approach with respect to objective measures of image quality or subjective assessment using a four point scale. When compared to a symmetric approach, the decreased exposure, subsequent lower patient radiation dose, and similar image quality from asymmetric cone beam processing supports its routine clinical use.