Optimal Phase of Dynamic Computed Tomography for Reliable Size Measurement of Metastatic Neuroendocrine Tumors of the Liver: Comparison between Pre- and Post-Contrast Phases

Machine learning-based identification of contrast-enhancement phase of computed tomography scans

Contrast-enhanced computed tomography scans (CECT) are routinely used in the evaluation of different clinical scenarios, including the detection and characterization of hepatocellular carcinoma (HCC). Quantitative medical image analysis has been an exponentially growing scientific field. A number of studies reported on the effects of variations in the contrast enhancement phase on the reproducibility of quantitative imaging features extracted from CT scans. The identification and labeling of phase enhancement is a time-consuming task, with a current need for an accurate automated labeling algorithm to identify the enhancement phase of CT scans. In this study, we investigated the ability of machine learning algorithms to label the phases in a dataset of 59 HCC patients scanned with a dynamic contrast-enhanced CT protocol. The ground truth labels were provided by expert radiologists. Regions of interest were defined within the aorta, the portal vein, and the liver. Mean density values were extracted from those regions of interest and used for machine learning modeling. Models were evaluated using accuracy, the area under the curve (AUC), and Matthew's correlation coefficient (MCC). We tested the algorithms on an external dataset (76 patients). Our results indicate that several supervised learning algorithms (logistic regression, random forest, etc.) performed similarly, and our developed algorithms can accurately classify the phase of contrast enhancement.

The role of unenhanced phase of the liver in the scanning protocol of metastatic breast cancer: implications for sensitivity, response evaluation and size measurement

Background

To analyse if performing unenhanced CT of the liver aids in the evaluation of metastatic lesions, response assessment or alter the size of the lesions, compared with portal phase alone, in patients with hepatic metastases from breast carcinoma.

Patients and methods

One-hundred and fifty-three CT scans of 36 women were included. Scans consisted of unenhanced, arterial and portal delayed phases of the liver. Two readers sorted which phase was best for visualization of metastases, evaluated the number of lesions detected in each phase, selected the best phase for assessment of response in two consecutive scans, and measured one target lesion in all the phases. Χ2 was used to compare differences among phases and paired t test for measurement differences.

Results

Unenhanced, arterial and portal phases were considered better phases by readers 1/2 in 68/67%, 27/28% and 69/70%, and some lesions were missed in 2%, 11% and 7%, respectively. Sensitivity was significantly better for unenhanced and portal phases compared to arterial phase. Comparison between consecutive scans was considered better in unenhanced (80/79%), followed by portal (70/69%) and arterial phases (31/31%). Maximum diameter of target lesions was 15% greater in unenhanced phase (p < 0.001).

Conclusions

Portal and unenhanced phases of the liver allow better detection and delineation of metastatic hepatic lesions from breast carcinoma. In most cases, unenhanced CT is the best phase to assess response and provides the largest diameter. Therefore, we recommend the use of unenhanced CT in the evaluation of patients with breast carcinoma and suspected or known hepatic metastatic disease.

Optoacoustic imaging in endocrinology and metabolism

Imaging is an essential tool in research, diagnostics and the management of endocrine disorders. Ultrasonography, nuclear medicine techniques, MRI, CT and optical methods are already used for applications in endocrinology. Optoacoustic imaging, also termed photoacoustic imaging, is emerging as a method for visualizing endocrine physiology and disease at different scales of detail: microscopic, mesoscopic and macroscopic. Optoacoustic contrast arises from endogenous light absorbers, such as oxygenated and deoxygenated haemoglobin, lipids and water, or exogenous contrast agents, and reveals tissue vasculature, perfusion, oxygenation, metabolic activity and inflammation. The development of high-performance optoacoustic scanners for use in humans has given rise to a variety of clinical investigations, which complement the use of the technology in preclinical research. Here, we review key progress with optoacoustic imaging technology as it relates to applications in endocrinology; for example, to visualize thyroid morphology and function, and the microvasculature in diabetes mellitus or adipose tissue metabolism, with particular focus on multispectral optoacoustic tomography and raster-scan optoacoustic mesoscopy. We explain the merits of optoacoustic microscopy and focus on mid-infrared optoacoustic microscopy, which enables label-free imaging of metabolites in cells and tissues. We showcase current optoacoustic applications within endocrinology and discuss the potential of these technologies to advance research and clinical practice.

Multimodality Imaging of Ileal Neuroendocrine (Carcinoid) Tumor

OBJECTIVE. The purpose of this article is to provide a multimodality imaging review of ileal carcinoid tumor. CONCLUSION. Ileal carcinoid tumors display a variety of radiologic findings. Delay in diagnosis is common because of initial nonspecific symptoms and subtle imaging findings. Reviewing the multimodality imaging appearance of the primary tumor, metastatic disease, and associated ancillary findings can help improve patient care.