Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate liver metastases and image quality between reduced-dose deep learning image reconstruction (DLIR) and standard-dose filtered back projection (FBP) contrast-enhanced abdominal CT. Materials and Methods In this prospective Health Insurance Portability and Accountability Act-compliant study (September 2019 through April 2021), participants with biopsy-proven colorectal cancer and liver metastases at baseline CT underwent standard-dose and reduced-dose portal venous abdominal CT in the same breath hold.

Medical Physics 3.0 and Its Relevance to Radiology.

Medical Physics 3.0 is a grassroots movement within the medical physics community to re-envision a new commitment and engagement of physics in the care process. In this model, a physicist, present in either the clinic or the laboratory, is to practice physics for the direct benefit of the patient, either immediately in the clinical setting or eventually through research.

Key Performance Indicators for Quality Imaging Practice: Why, What, and How.

A common trend across health care organizations is the development of key performance indicators (KPIs) for characterizing quality, identifying areas in need of change, and quantifying the impact of change. This article outlines a list of KPIs that can be used to quantify, target, and optimize value and value delivery in medical imaging practice. Of particular focus here is the aspect of practice that should be overseen and informed by the work of medical physicists, along the trajectory and expectations of a Medical Physics 3.

Proton density water fraction as a reproducible MR-based measurement of breast density.

Purpose: To introduce proton density water fraction (PDWF) as a confounder-corrected (CC) MR-based biomarker of mammographic breast density, a known risk factor for breast cancer.

Methods: Chemical shift encoded (CSE) MR images were acquired using a low flip angle to provide proton density contrast from multiple echo times. Fat and water images, corrected for known biases, were produced by a six-echo CC CSE-MRI algorithm.

Design and implementation of a practical quality control program for dual-energy CT.

A novel routine dual-energy computed tomography (DECT) quality control (QC) program was developed to address the current deficiency of routine QC for this technology. The dual-energy quality control (DEQC) program features (1) a practical phantom with clinically relevant materials and concentrations, (2) a clinically relevant acquisition, reconstruction, and postprocessing protocol, and (3) a fully automated analysis software to extract quantitative data for database storage and trend analysis. The phantom, designed for easy set up for standalone or adjacent imaging next to the ACR phantom, was made in collaboration with an industry partner and informed by clinical needs to have four iodine inserts (0.

Correction for Systematic Bias in Radiomics Measurements Due to Variation in Imaging Protocols.

Rationale And Objectives: The accuracy of measured radiomics features is affected by CT imaging protocols. This study aims to ascertain if applying bias corrections can improve the classification performance of the radiomics features.

Materials And Methods: A cohort of 144 Non-Small Cell Lung Cancer patient CT images was used to calculate radiomics features for use in predictive models of patient pathological stage.

Comparison of 12 surrogates to characterize CT radiation risk across a clinical population.

Objectives: Quantifying radiation burden is essential for justification, optimization, and personalization of CT procedures and can be characterized by a variety of risk surrogates inducing different radiological risk reflections. This study compared how twelve such metrics can characterize risk across patient populations.

Methods: This study included 1394 CT examinations (abdominopelvic and chest).

Patient-Informed Organ Dose Estimation in Clinical CT: Implementation and Effective Dose Assessment in 1048 Clinical Patients.

The purpose of this study is to comprehensively implement a patient-informed organ dose monitoring framework for clinical CT and compare the effective dose (ED) according to the patient-informed organ dose with ED according to the dose-length product (DLP) in 1048 patients. Organ doses for a given examination are computed by matching the topogram to a computational phantom from a library of anthropomorphic phantoms and scaling the fixed tube current dose coefficients by the examination volume CT dose index (CTDI) and the tube-current modulation using a previously validated convolution-based technique. In this study, the library was expanded to 58 adult, 56 pediatric, five pregnant, and 12 International Commission on Radiological Protection (ICRP) reference models, and the technique was extended to include multiple protocols, a bias correction, and uncertainty estimates.

Clinical concordance with Image Gently guidelines for pediatric computed tomography: a study across 663,417 CT scans at 53 clinical facilities.

Background: Managing patient radiation dose in pediatric computed tomography (CT) examinations is essential. Some organizations, most notably Image Gently, have suggested techniques to lower dose to pediatric patients and mitigate risk while maintaining image quality.

Objective: We sought to validate whether institutions are observing Image Gently guidelines in practice.

A comparison of COVID-19 and imaging radiation risk in clinical patient populations.

The outbreak of coronavirus SARS-COV2 affected more than 180 countries necessitating fast and accurate diagnostic tools. Reverse transcriptase polymerase chain reaction (RT-PCR) has been identified as a gold standard test with Chest CT and Chest Radiography showing promising results as well. However, radiological solutions have not been used extensively for the diagnosis of COVID-19 disease, partly due to radiation risk.

Comparison of Low Dose Performance of Photon-Counting and Energy Integrating CT.

Rationale And Objectives: The purpose of this study was to investigate the potential of photon-counting CT (PCCT) to improve quantitative image quality for low dose imaging compared to energy-integrating detector CT (EID CT).

Materials And Methods: An investigational scanner (Siemens, Germany) with PCCT and EID CT subsystems was used to compare image quality performance at four dose levels: 1.7, 2, 4, 6 mGy CTDI, all at or below current dose values used for conventional abdominal CT.

Quantification of Minimum Detectable Difference in Radiomics Features Across Lesions and CT Imaging Conditions.

Rationale And Objectives: The 3-fold purpose of this study was to (1) develop a method to relate measured differences in radiomics features in different computed tomography (CT) scans to one another and to true feature differences; (2) quantify minimum detectable change in radiomics features based on measured radiomics features from pairs of synthesized CT images acquired under variable CT scan settings, and (3) ascertain and inform the recommendations of the Quantitative Imaging Biomarkers Alliance (QIBA) for nodule volumetry.

Materials And Methods: Images of anthropomorphic lung nodule models were simulated using resolution and noise properties for 297 unique imaging conditions. Nineteen morphology features were calculated from both the segmentation masks derived from the imaged nodules and from ground truth nodules.

A database of 40 patient-based computational models for benchmarking organ dose estimates in CT.

Purpose: Patient radiation burden in computed tomography (CT) can best be characterized through risk estimates derived from organ doses. Organ doses can be estimated by Monte Carlo simulations of the CT procedures on computational phantoms assumed to emulate the patients. However, the results are subject to uncertainties related to how accurately the patient and CT procedure are modeled.

Automated quality control in nuclear medicine using the structured noise index.

Purpose: Daily flood-field uniformity evaluation serves as the central element of nuclear medicine (NM) quality control (QC) programs. Uniformity images are traditionally analyzed using pixel value-based metrics, that is, integral uniformity (IU), which often fail to capture subtle structure and patterns caused by changes in gamma camera performance, requiring visual inspections which are subjective and time demanding. The goal of this project was to implement an advanced QC metrology for NM to effectively identify nonuniformity issues, and report issues in a timely manner for efficient correction prior to clinical use.

Technical Note: Validation of TG 233 phantom methodology to characterize noise and dose in patient CT data.

Purpose: Phantoms are useful tools in diagnostic CT, but practical limitations reduce phantoms to being only a limited patient surrogate. Furthermore, a phantom with a single cross sectional area cannot be used to evaluate scanner performance in modern CT scanners that use dose reduction techniques such as automated tube current modulation (ATCM) and iterative reconstruction (IR) algorithms to adapt x-ray flux to patient size, reduce radiation dose, and achieve uniform image noise. A new multisized phantom (Mercury Phantom, MP) has been introduced, representing multiple diameters.

Why physics in medicine?

Despite its crucial role in the development of new medical imaging technologies, in clinical practice, physics has primarily been involved in technical evaluation of technologies. However, this narrow role is no longer adequate. New trajectories in medicine call for a stronger role for physics in the clinic.

Validation of algorithmic CT image quality metrics with preferences of radiologists.

Purpose: Automated assessment of perceptual image quality on clinical Computed Tomography (CT) data by computer algorithms has the potential to greatly facilitate data-driven monitoring and optimization of CT image acquisition protocols. The application of these techniques in clinical operation requires the knowledge of how the output of the computer algorithms corresponds to clinical expectations. This study addressed the need to validate algorithmic image quality measurements on clinical CT images with preferences of radiologists and determine the clinically acceptable range of algorithmic measurements for abdominal CT examinations.

Correlation of Algorithmic and Visual Assessment of Lesion Detection in Clinical Images.

Rationale And Objectives: Clinically-relevant quantitative measures of task-based image quality play key roles in effective optimization of medical imaging systems. Conventional phantom-based measures do not adequately reflect the real-world image quality of clinical Computed Tomography (CT) series which is most relevant for diagnostic decision-making. The assessment of detectability index which incorporates measurements of essential image quality metrics on patient CT images can overcome this limitation.

Organ doses from CT localizer radiographs: Development, validation, and application of a Monte Carlo estimation technique.

Purpose: The purpose of this study was to simulate and validate organ doses from different computed tomography (CT) localizer radiograph geometries using Monte Carlo methods for a population of patients.

Methods: A Monte Carlo method was developed to estimate organ doses from CT localizer radiographs using PENELOPE. The method was validated by comparing dosimetry estimates with measurements using an anthropomorphic phantom imbedded with thermoluminescent dosimeters (TLDs) scanned on a commercial CT system (Siemens SOMATOM Flash).

Design and fabrication of heterogeneous lung nodule phantoms for assessing the accuracy and variability of measured texture radiomics features in CT.

We aimed to design and fabricate synthetic lung nodules with patient-informed internal heterogeneity to assess the variability and accuracy of measured texture features in CT. To that end, 190 lung nodules from a publicly available database of chest CT images (Lung Image Database Consortium) were selected based on size ( ) and malignancy. The texture features of the nodules were used to train a statistical texture synthesis model based on clustered lumpy background.

Expanding the Concept of Diagnostic Reference Levels to Noise and Dose Reference Levels in CT.

Diagnostic reference levels were developed as guidance for radiation dose in medical imaging and, by inference, diagnostic quality. The objective of this work was to expand the concept of diagnostic reference levels to explicitly include noise of CT examinations to simultaneously target both dose and quality through corresponding reference values. The study consisted of 2851 adult CT examinations performed with scanners from two manufacturers and two clinical protocols: abdominopelvic CT with IV contrast administration and chest CT without IV contrast administration.