RSNA 2017: Advanced acquisition and post-processing techniques for chest CT
Chest computed tomography (CT) examinations can be improved using advanced acquisition techniques, making sound reconstruction parameter choices, and using post-processing methods to acquire quantitative information that cannot be obtained visually. Radiologists from Mayo Clinic in Rochester, MN, make recommendations in a digital poster (CH104-ED-X) that received a RSNA Certificate of Merit.
Dual energy CT
Changing the acquisition mode of a chest CT scan to Dual Energy (DE), fast acquisition or ultra low dose for specific medical situations can potentially increase the diagnostic accuracy. Lead author N.M. Weber of the Department of Radiology, explain that DECT is based on the fact that there are two mechanisms responsible for attenuation of X-rays in the CT relevant diagnostic energy range: the photoelectric effect and Compton scattering. Only materials with substantially different attenuation can be discriminated using DE CT, and the quality and accuracy of DE-based material discrimination depends on the separation between the high- and low-kV spectra.
The DECT technique that the authors recommend is to optimize DE kV pairs based on the patient size. If a patient’s lateral width is 45 cm or smaller, the DE kV should be 100/snl 40 with a QRM of 210/179, and if the patient is greater than 45 cm, use single energy instead. An optimal helical pitch should be used (⏞ 0.6) to reduce artifacts and non-uniform dose effects. Radiation dose should be adjusted to be of a similar level to a single energy exam. Iterative reconstruction is recommended to reduce noise and to make corrections to reduce iodine beam hardening.
The benefit of DE in a pulmonary embolism CT angiography (CTA) are several. Perfused blood volume maps created from DECT improve detection of segmental and chronic pulmonary emboli and improve inter- and intra-observer agreement with respect to detection. The authors state that quantification of pulmonary perfusion from perfused blood volume maps may improve assessment of severity and risk of right heart strain.
However, DE does have limitations. It is not appropriate for patients over 50 cm in lateral width. Beam hardening artifacts can be created, particularly in the bones. Undesired motion is also a factor, caused by slower rotation time and pitch.
Ultra-fast acquisition is appropriate for pediatric patients, non-compliant patients, and when performing a pulmonary embolism CTA, as it can improve temporal resolution and reduce motion artifacts. Fast rotation time, a wide detector, and dual-source high pitch mode are factors facilitating ultra-fast acquisition of images. The authors offer the caveats that as table speed increases, radiation dose requirement increases, and that the number of artifacts may increase as patient size increases.
Ultra low dose radiation protocols can be used for lung cancer screening and as follow-up imaging for lung nodules. Approaches for ultra low dose include optimized kV selection, optimizing the X-ray beam spectrum, and use of iterative reconstruction. Added beam filtration, such as the use of a tin filter, can improve dose efficiency. A tin filter will remove low-energy photons that do not contribute to image formation.
Reconstructions
Iterative reconstruction can be very useful to perform on ultra low dose images, due to the texture of the image. Use of a larger matrix (such as 1024 x 1024 compared to 512 x 512) reduces the partial volume effects for structures of interest. It can cover the entire thorax with a small picture size, and also offers potential benefits for quantitative assessments as well as qualitative diagnostic interpretation.
The authors advise that a large matrix reconstruction in conjunction with quantitative imaging has the potential to improve accuracy and reproducibility. They say that in general, it will improve qualitative assessment efficiency, accuracy, and reproducibility. Nodule measurements will be more accurate. They give the example of a line (fibrosis/reticulation) appearing as a line instead of an ill-defined boundary.
Post-processing: CAD, lung nodule analysis, and lung parenchyma
Computer-aided detection (CAD) can help improve efficiency when reading an exam and can help reduce interobserver variability. It may also help radiologists increase their nodule detection sensitivity. However, as with all CAD applications, it can generate both false positive and false negative detection.
Computer-aided nodule analysis and risk yield (CANARY) is a software algorithm that segments lung nodules from parenchyma. It provides parametric analysis of dense features that can be used as biomarkers to characterize lung nodules and assigns risk of adenocarcinoma by matching a patient’s nodule to known characteristics in its database. It also can quantify change over time.
The authors advise that use of CANARY may guide limited lung resection, local therapy such as stereotactic body radiation therapy (SBRT), radiofrequency and/or cryo-ablation, or proton beam therapy compared to standard lobectomy. CANARY also could facilitate individualized management of patients with lung nodules by matching features of adenocarcinomas. This technology, however, is limited to the evaluation of nodules representing adenocarcinoma, such as atypical adenomatous hyperplasia to invasive adenocarcinoma.
Computer-aided lung informatics for pathology evaluation and rating (CALIPER) is a software algorithm that classifies and quantifies features of lung parenchyma on volumetric high resolution CT scans. It automatically characterizes and quantifies diffuse pulmonary parenchymal disease such as emphysema or air trapping, and has been known to aid in identifying probable disease, to stratifying prognosis in early disease, and to identify and monitor progression of disease or response to therapy. It is also used to guide treatment options for patients with COPD.