Organ-based tube current modulation in chest CT. A comparison of three vendors

Potential of employing a quantum iterative reconstruction algorithm for ultra-high-resolution photon-counting detector CT of the hip

INTRODUCTION

This study investigated the image quality of a new quantum iterative reconstruction algorithm (QIR) for high resolution photon-counting CT of the hip.

METHODS

Using a first-generation photon-counting CT scanner, five cadaveric specimens were examined with ultra-high-resolution protocols matched for radiation dose. Images were post-processed with a sharp convolution kernel and five different strength levels of iterative reconstruction (QIR 0 - QIR 4). Subjective image quality was rated independently by three radiologists on a five-point scale. Intraclass correlation coefficients (ICC) were computed for assessing interrater agreement. Objective image quality was evaluated by means of contrast-to-noise-ratios (CNR) in bone and muscle tissue.

RESULTS

For osseous tissue, subjective image quality was rated best for QIR 2 reformatting (median 5 [interquartile range 5-5]). Contrarily, for soft tissue, QIR 4 received the highest ratings among compared strength levels (3 [3-4]). Both ICC_bone (0.805; 95% confidence interval 0.711-0.877; p < 0.001) and ICC_muscle (0.885; 0.824-0.929; p < 0.001) suggested good interrater agreement. CNR in bone and muscle tissue increased with ascending strength levels of iterative reconstruction with the highest results recorded for QIR 4 (CNR_bone 29.43 ± 2.61; CNR_muscle 8.09 ± 0.77) and lowest results without QIR (CNR_bone 3.90 ± 0.29; CNR_muscle 1.07 ± 0.07) (all p < 0.001).

CONCLUSION

Reconstructing photon-counting CT data with an intermediate QIR strength level appears optimal for assessment of osseous tissue, whereas soft tissue analysis benefitted from applying the highest strength level available.

IMPLICATIONS FOR PRACTICE

Quantum iterative reconstruction technique can enhance image quality by significantly reducing noise and improving CNR in ultra-high resolution CT imaging of the hip.

Design of a 3D printed coronary artery model for CT optimization

INTRODUCTION

To design a custom phantom of the coronary arteries to optimize CT coronary angiography (CCTA) protocols.

METHODS

Characteristics of the left and right coronary arteries (mean Hounsfield Unit (HU) values and diameters) were collected from consecutive CCTA examinations (n = 43). Four different materials (two mixtures of glycerine, gelatine and water, pig hearts, Ecoflex™ silicone) were scanned inside a Lungman phantom using the CCTA protocol to find the closest model to in vivo data. A 3D printed model of the coronary artery tree was created using CCTA data by exporting a CT volume rendering into Autodesk Meshmixer™ software. The model was placed in an acid bath for 5 h, then covered in Ecoflex™, which was removed after drying. Both the Ecoflex™ and pig heart were later filled with a mixture of contrast (Visipaque 320 mg I/ml), NaCl and gelatin and scanned with different levels of tube current and iterative reconstruction (ASiR-V). Objective (HU, noise and size (vessel diameter) and subjective analysis were performed on all scans.

RESULTS

The gelatine mixtures had HU values of 130 and 129, Ecoflex™ 65 and the pig heart 56. At the different mA/ASiR-V levels the contrast filled Ecoflex™ had a mean HU 318 ± 4, noise 47±7HU and diameter of 4.4 mm. The pig heart had a mean HU of 209 ± 5, noise 38±4HU and a diameter of 4.4 mm. With increasing iterative reconstruction level the visualisation of the pig heart arteries decreased so no measurements could be performed.

CONCLUSION

The use of a 3D printed model of the arteries and casting with the Ecoflex™ silicone is the most suitable solution for a custom-designed phantom.

IMPLICATIONS FOR PRACTICE

Custom designed phantoms using 3D printing technology enable cost effective optimisation of CT protocols.

Radiation dose reduction considerations and imaging patterns of ground glass opacities in coronavirus: risk of over exposure in computed tomography

This article aims to summarize the available data on the severe acute respiratory syndrome coronavirus 2 (SAR-CoV-2) imaging patterns as well as reducing radiation dose exposure in chest computed tomography (CT) protocols. First, the general aspects of radiation dose in CT and radiation risk are discussed, followed by the effect of changing parameters on image quality. This article attempts to highlight some of the common chest CT signs that radiologists and emergency physicians are likely to encounter. With the increasing trend of using chest CT scans as an imaging tool to diagnose and monitor SAR-CoV-2, we emphasize that pattern recognition is the key, and this pictorial essay should serve as a guide to help establish correct diagnosis coupled with correct scanner parameters to reduce radiation dose without affecting imaging quality in this tragic pandemic the world is facing.