Use of Contrast Media During CT-guided Thermal Ablation of Colorectal Liver Metastasis for Procedure Planning is Associated with Improved Immediate Outcomes.

PURPOSE: The aim of this study was to analyze the impact of using intra-procedural pre-ablation contrast-enhanced CT prior to percutaneous thermal ablation (pre-ablation CECT) of colorectal liver metastases (CLM) on local outcomes. MATERIALS AND METHODS: This retrospective analysis of a prospectively collected liver ablation registry included 144 consecutive patients (median age 57 years IQR [49, 65], 60% men) who underwent 173 CT-guided ablation sessions for 250 CLM between October 2015 and March 2020. In addition to oncologic outcomes, technical success was retrospectively evaluated using a biomechanical deformable image registration software for 3D-minimal ablative margin (3D-MAM) quantification. Bayesian regression was used to estimate effects of pre-ablation CECT on residual unablated tumor, 3D-MAM, and local tumor progression-free survival (LTPFS). RESULTS: Pre-ablation CECT was acquired in 71/173 (41%) sessions. Residual unablated tumor was present in one (0.9%) versus nine tumors (6.6%) ablated with versus without using pre-ablation CECT, respectively (p = 0.024). Pre-ablation CECT use decreased the odds of residual disease on first follow-up by 78% (CI95% [5, 86]) and incomplete ablation (3D-MAM ≤ 0 mm) by 58% (CI95% [13, 122]). The odds ratio for residual unablated tumor for larger CLM was lower when pre-ablation CECT was used (odds ratio 1.0 with pre-ablation CECT vs. 2.52 without). Pre-ablation CECT use was not associated with improvements on LTPFS. CONCLUSIONS: Pre-ablation CECT is associated with improved immediate outcomes by significantly reducing the incidence of residual unablated tumor and by mitigating the risk of incomplete ablation for larger CLM. We recommend performing baseline intra-procedural pre-ablation CECT as a standard imaging protocol. LEVEL OF EVIDENCE: Level 3 (retrospective cohort study).

Targeted exome-based predictors of patterns of progression of colorectal liver metastasis after percutaneous thermal ablation.

BACKGROUND: Percutaneous thermal ablation is a curative-intent locoregional therapy (LRT) for selected patients with unresectable colorectal liver metastasis (CLM). Several factors have been identified that contribute to local tumour control after ablation. However, factors contributing to disease progression outside the ablation zone after ablation are poorly understood. METHODS: In this retrospective study, using next-generation sequencing, we identified genetic biomarkers associated with different patterns of progression following thermal ablation of CLM. RESULTS: A total of 191 ablation naïve patients between January 2011 and March 2020 were included in the analysis, and 101 had genomic profiling available. Alterations in the TGFß pathway were associated with increased risk of development of new intrahepatic tumours (hazard ratio [HR], 2.75, 95% confidence interval [95% CI] 1.39-5.45, P = 0.004); and alterations in the Wnt pathway were associated with increased probability of receiving salvage LRT for any intrahepatic progression (HR, 5.8, 95% CI 1.94-19.5, P = 0.003). CONCLUSIONS: Our findings indicate that genomic alterations in cancer-related signalling pathways can predict different progression patterns and the likelihood of receiving salvage LRT following percutaneous thermal ablation of CLM.

Patient Radiation Doses in IR Procedures: The American College of Radiology Dose Index Registry-Fluoroscopy Pilot.

PURPOSE: To update normative data on fluoroscopy dose indices in the United States for the first time since the Radiation Doses in Interventional Radiology study in the late 1990s. MATERIALS AND METHODS: The Dose Index Registry-Fluoroscopy pilot study collected data from March 2018 through December 2019, with 50 fluoroscopes from 10 sites submitting data. Primary radiation dose indices including fluoroscopy time (FT), cumulative air kerma (Ka,r), and kerma area product (PKA) were collected for interventional radiology fluoroscopically guided interventional (FGI) procedures. Clinical facility procedure names were mapped to the American College of Radiology (ACR) common procedure lexicon. Distribution parameters including the 10th, 25th, 50th, 75th, 95th, and 99th percentiles were computed. RESULTS: Dose indices were collected for 70,377 FGI procedures, with 50,501 ultimately eligible for analysis. Distribution parameters are reported for 100 ACR Common IDs. FT in minutes, Ka,r in mGy, and PKA in Gy-cm2 are reported in this study as (n; median) for select ACR Common IDs: inferior vena cava filter insertion (1,726; FT: 2.9; Ka,r: 55.8; PKA: 14.19); inferior vena cava filter removal (464; FT: 5.7; Ka,r: 178.6; PKA: 34.73); nephrostomy placement (2,037; FT: 4.1; Ka,r: 39.2; PKA: 6.61); percutaneous biliary drainage (952; FT: 12.4; Ka,r: 160.5; PKA: 21.32); gastrostomy placement (1,643; FT: 3.2; Ka,r: 29.1; PKA: 7.29); and transjugular intrahepatic portosystemic shunt placement (327; FT: 34.8; Ka,r: 813.0; PKA: 181.47). CONCLUSIONS: The ACR DIR-Fluoro pilot has provided state-of-the-practice statistics for radiation dose indices from IR FGI procedures. These data can be used to prioritize procedures for radiation optimization, as demonstrated in this work.

Patient Radiation Doses in Interventional Radiology Procedures: Comparison of Fluoroscopy Dose Indices between the American College of Radiology Dose Index Registry-Fluoroscopy Pilot and the Radiation Doses in Interventional Radiology Study.

PURPOSE: To compare radiation dose index distributions for fluoroscopically guided interventions in interventional radiology from the American College of Radiology (ACR) Fluoroscopy Dose Index Registry (DIR-Fluoro) pilot to those from the Radiation Doses in Interventional Radiology (RAD-IR) study. MATERIALS AND METHODS: Individual and grouped ACR Common identification numbers (procedure types) from the DIR-Fluoro pilot were matched to procedure types in the RAD-IR study. Fifteen comparisons were made. Distribution parameters, including the 10th, 25th, 50th, 75th, and 95th percentiles, were compared for fluoroscopy time (FT), cumulative air kerma (Ka,r), and kerma area product (PKA). Two derived indices were computed using median dose indices. The procedure-averaged reference air kerma rate (Ka,r¯) was computed as Ka,r / FT. The procedure-averaged x-ray field size at the reference point (Ar) was computed as PKA / (Ka,r × 1,000). RESULTS: The median FT was equally likely to be higher or lower in the DIR-Fluoro pilot as it was in the RAD-IR study, whereas the maximum FT was almost twice as likely to be higher in the DIR-Fluoro pilot than it was in the RAD-IR study. The median Ka,r was lower in the DIR-Fluoro pilot for all procedures, as was median PKA. The maximum Ka,r and PKA were more often higher in the DIR-Fluoro pilot than in the RAD-IR study. Ka,r¯ followed the same pattern as Ka,r, whereas Ar was often greater in DIR-Fluoro. CONCLUSIONS: The median dose indices have decreased since the RAD-IR study. The typical Ka,r rates are lower, a result of the use of lower default dose rates. However, opportunities for quality improvement exist, including renewed focus on tight collimation of the imaging field of view.

Automated segmentation of colorectal liver metastasis and liver ablation on contrast-enhanced CT images.

Objectives: Colorectal cancer (CRC), the third most common cancer in the USA, is a leading cause of cancer-related death worldwide. Up to 60% of patients develop liver metastasis (CRLM). Treatments like radiation and ablation therapies require disease segmentation for planning and therapy delivery. For ablation, ablation-zone segmentation is required to evaluate disease coverage. We hypothesize that fully convolutional (FC) neural networks, trained using novel methods, will provide rapid and accurate identification and segmentation of CRLM and ablation zones. Methods: Four FC model styles were investigated: Standard 3D-UNet, Residual 3D-UNet, Dense 3D-UNet, and Hybrid-WNet. Models were trained on 92 patients from the liver tumor segmentation (LiTS) challenge. For the evaluation, we acquired 15 patients from the 3D-IRCADb database, 18 patients from our institution (CRLM = 24, ablation-zone = 19), and those submitted to the LiTS challenge (n = 70). Qualitative evaluations of our institutional data were performed by two board-certified radiologists (interventional and diagnostic) and a radiology-trained physician fellow, using a Likert scale of 1-5. Results: The most accurate model was the Hybrid-WNet. On a patient-by-patient basis in the 3D-IRCADb dataset, the median (min-max) Dice similarity coefficient (DSC) was 0.73 (0.41-0.88), the median surface distance was 1.75 mm (0.57-7.63 mm), and the number of false positives was 1 (0-4). In the LiTS challenge (n = 70), the global DSC was 0.810. The model sensitivity was 98% (47/48) for sites ≥15 mm in diameter. Qualitatively, 100% (24/24; minority vote) of the CRLM and 84% (16/19; majority vote) of the ablation zones had Likert scores ≥4. Conclusion: The Hybrid-WNet model provided fast (<30 s) and accurate segmentations of CRLM and ablation zones on contrast-enhanced CT scans, with positive physician reviews.

Combined Angio-CT Systems: A Roadmap Tool for Precision Therapy in Interventional Oncology.

Combined angiography-CT (angio-CT) systems, which combine traditional angiographic imaging with cross-sectional imaging, are a valuable tool for interventional radiology. Although cone-beam CT (CBCT) technology from flat-panel angiography systems has been established as an adjunct cross-sectional imaging tool during interventional procedures, the intrinsic advantages of angio-CT systems concerning superior soft-tissue imaging and contrast resolution, along with operational ease, have sparked renewed interest in their use in interventional oncology procedures. Owing to increases in affordability and usability due to an improved workflow, angio-CT systems have become a viable alternative to stand-alone flat-panel angiographic systems equipped with CBCT. This review aims to provide a comprehensive technical and clinical guide for the use of angio-CT systems in interventional oncology. The basic concepts related to the use of angio-CT systems, including concepts related to workflow setup, imaging characteristics, and acquisition parameters, will be discussed. Additionally, an overview on the clinical applications and the benefits of angio-CT systems in routine therapeutic and palliative interventional oncology procedures will be reviewed. Keywords: Ablation Techniques, CT-Angiography, Interventional-Body, Interventional-MSK, Chemoembolization, Embolization, Radiation Therapy/Oncology, Abdomen/GI, Skeletal-Axial Supplemental material is available for this article. © RSNA, 2021.

Revisiting the need for radiation output measurements after X-ray tube replacement in computed tomography.

PURPOSE: State regulations require that CT radiation output be measured using a dosimeter after major service. The most common major service is tube replacement. We hypothesized that historical QC data could be used instead to determine if output measurements are necessary, potentially reducing the need for output measurements that require an on-site visit by a qualified medical physicist. METHODS: Records of 65 original equipment manufacturer (OEM) tube replacements were reviewed to determine with what frequency output was outside the manufacturer's specifications. The previous 7 days of historical quality control (QC) data prior to a tube change was used to establish a baseline mean noise level and 95% inferential confidence intervals (ICIs) about the mean. This was compared to an ICI constructed using 7 days of QC data post-tube change and the region of indifference. Different methods for acquiring samples of image noise were compared using a single factor analysis of variance (ANOVA). RESULTS: None of the 65 tube replacements reviewed in this study resulted in an output change that exceeded the manufacturer's specifications. In all but one case, the results of the ICI analysis matched the measured output results. In the single case where results were discordant, the mean image noise was slightly higher after the tube change, which may have indicated the need for a larger sample size or service unrelated to the X-ray tube, for example, system calibration. The method used to sample image noise did not significantly affect the calculated mean noise. CONCLUSIONS: This review of historical OEM tube replacement data indicated the likelihood of output falling outside manufacturer specifications is low. Considering this, it is likely that using QC data from programs required by regulation and the American College of Radiology (ACR), medical physicists can reliably verify radiation output stability remotely instead of making measurements using a dosimeter.

Validation of a method for estimating peak skin dose from CT-guided procedures.

A method for estimating peak skin dose (PSD) from CTDIvol has been published but not validated. The objective of this study was to validate this method during CT-guided ablation procedures. Radiochromic film was calibrated and used to measure PSD. Sixty-eight patients were enrolled in this study, and measured PSD were collected for 46 procedures. CTDIvol stratified by axial and helical scanning was used to calculate an estimate of PSD using the method [1.2 × CTDIvol (helical) + 0.6 × CTDIvol (axial)], and both calculated PSD and total CTDIvol were compared to measured PSD using paired t-tests on the log-transformed data and Bland-Altman analysis. Calculated PSD were significantly different from measured PSD (P < 0.0001, bias, 18.3%, 95% limits of agreement, -63.0% to 26.4%). Measured PSD were not significantly different from total CTDIvol (P = 0.27, bias, 3.97%, 95% limits of agreement, -51.6% to 43.7%). Considering that CTDIvol is reported on the console of all CT scanners, is not stratified by axial and helical scanning modes, and is immediately available to the operator during CT-guided interventional procedures, it may be reasonable to use the scanner-reported CTDIvol as an indicator of PSD during CT-guided procedures. However, further validation is required for other models of CT scanner.

A Benchmark for automatic noise measurement in clinical computed tomography.

PURPOSE: Assessment of image quality directly in clinical image data is an important quality control objective as phantom-based testing does not fully represent image quality across patient variation. Computer algorithms for automatically measuring noise in clinical computed tomography (CT) images have been introduced, but the accuracy of these algorithms is unclear. This work benchmarks the accuracy of the global noise (GN) algorithm for automatic noise measurement in contrast-enhanced abdomen CT exams in comparison to precise reference noise measurements. The GN algorithm was further optimized compared to the previous report in the literature. METHODS: Reference values of noise were established in a public image dataset of 82 contrast-enhanced abdomen CT exams. The reference noise values were obtained by manual regions-of-interest measurements of pixel standard deviation in the liver parenchyma according to an instruction protocol. Noise measurements taken by six observers were averaged together to improve reference noise statistical precision. The GN algorithm was used to automatically measure noise in each image set. The accuracy of the GN algorithm was determined in terms of RMS error compared to reference noise. The GN algorithm was optimized by conducting 1000 trials with random algorithm parameter values. The trial with the lowest RMS error was used to select optimum algorithm parameters. RESULTS: The range of noise across CT image sets was 8.8-28.8 HU. Reference noise measurements were made with a precision of ±0.78 HU (95% confidence interval). The RMS error of automatic noise measurement was 0.93 HU (0.77-1.19 HU 95% confidence interval). The automatic noise measurements were equally accurate across image sets of varying noise magnitude. Optimum GN algorithm parameter values were: a kernel size of 7 pixels, and soft tissue lower and upper thresholds of 0 and 170 HU, respectively. CONCLUSIONS: The performance of automatic noise measurement was benchmarked in a large clinical CT dataset. The study provides a framework for thorough validation of automatic clinical image quality measurement methods. The GN algorithm was optimized and validated for automatic measurement of soft-tissue noise in abdomen CT exams.

Comparison of virtual to true unenhanced abdominal computed tomography images acquired using rapid kV-switching dual energy imaging.

OBJECTIVE: To compare "virtual" unenhanced (VUE) computed tomography (CT) images, reconstructed from rapid kVp-switching dual-energy computed tomography (DECT), to "true" unenhanced CT images (TUE), in clinical abdominal imaging. The ability to replace TUE with VUE images would have many clinical and operational advantages. METHODS: VUE and TUE images of 60 DECT datasets acquired for standard-of-care CT of pancreatic cancer were retrospectively reviewed and compared, both quantitatively and qualitatively. Comparisons included quantitative evaluation of CT numbers (Hounsfield Units, HU) measured in 8 different tissues, and 6 qualitative image characteristics relevant to abdominal imaging, rated by 3 experienced radiologists. The observed quantitative and qualitative VUE and TUE differences were compared against boundaries of clinically relevant equivalent thresholds to assess their equivalency, using modified paired t-tests and Bayesian hierarchical modeling. RESULTS: Quantitatively, in tissues containing high concentrations of calcium or iodine, CT numbers measured in VUE images were significantly different from those in TUE images. CT numbers in VUE images were significantly lower than TUE images when calcium was present (e.g. in the spine, 73.1 HU lower, p < 0.0001); and significantly higher when iodine was present (e.g. in renal cortex, 12.9 HU higher, p < 0.0001). Qualitatively, VUE image ratings showed significantly inferior depiction of liver parenchyma compared to TUE images, and significantly more cortico-medullary differentiation in the kidney. CONCLUSIONS: Significant differences in VUE images compared to TUE images may limit their application and ability to replace TUE images in diagnostic abdominal CT imaging.

The American College of Radiology Fluoroscopy Dose Index Registry Pilot: Technical Considerations and Dosimetric Performance of the Interventional Fluoroscopes.

PURPOSE: To characterize the accuracy and consistency of fluoroscope dose index reporting and report rates of occupational radiation safety hardware availability and use, trainee participation in procedures, and optional hardware availability at pilot sites for the American College of Radiology (ACR) Fluoroscopy Dose Index Registry (DIR). MATERIALS AND METHODS: Nine institutions participated in the registry pilot, providing fluoroscopic technical and clinical practice data from 38 angiographic C-arm-type fluoroscopes. These data included measurements of the procedure table and mattress transmission factors and accuracy measurements of the reference-point air kerma (Ka,r) and air kerma-area product (PKA). The accuracy of the radiation dose indices were analyzed for variation over time by 1-way analysis of variance (ANOVA). Sites also self-reported information on availability and use of radiation safety hardware, hardware configuration of fluoroscopes, and trainee participation in procedures. RESULTS: All Ka,r and PKA measurements were within the ±35% regulatory limit on accuracy. The mean absolute difference between correction factors for a given system in fluoroscopic and acquisition mode was 0.03 (95% confidence interval, 0.03-0.03). For the 28 fluoroscopic imaging planes that provided data for 3 time points, ANOVA yielded an F value of 0.134 with an F-critical value of 3.109 (P = .875). CONCLUSIONS: This publication provides the technical and clinical framework pertaining to the ACR Fluoroscopy DIR pilot and offers necessary context for future analysis of the clinical procedure radiation-dose data collected.

Evaluation of an automated grid artifact detection system for quality control in digital mammography.

PURPOSE: Grid artifacts occur in digital mammography when synchronization between the grid assembly and generator is not achieved, including when malfunctions occur in the grid assembly or generator subsystems. Such artifacts are not explicitly monitored or evaluated by existing mammography quality control programs. In this study, we developed an automated method for quantifying the presence of grid artifacts in two-dimensional (2D) digital mammography images and assessed its utility as a supplement to existing quality control programs. METHODS: Four digital mammography systems (Hologic Dimensions 3D 5000) were configured to automatically transfer 2D images to a server where the strength of the grid pattern, γmax , was quantified using a template-matching algorithm and stored in amySQL database. This analysis was performed on both American College of Radiology (ACR) phantom and clinical images. Changes in γmax were compared with image quality and service records to establish preliminary action limits for physicist intervention for each type of image. These action limits were applied around selected service events to evaluate their clinical utility. RESULTS: All systems exhibited a gradual increase in γmax in ACR phantom images prior to having identical major components of the generator subsystem replaced, despite the absence of visible gridlines in the images. Retrospective analysis of phantom images suggested that physicists should consider AEC testing when γ max exceeds 0.050 and that clinical image quality may be affected when γ max exceeds 0.060. Eighteen of 19 visible grid artifacts were identified using a threshold γ max value of 0.065 in clinical images. Warning limits that indicate abnormal operation before visible degradation in image quality were also established. These warning limits were 0.046 and 0.041 for the 24 × 29 cm and 18 × 24 cm paddles, respectively. Specific malfunctions in the generator and grid subsystems can be detected by applying these limits. CONCLUSIONS: Automated monitoring of γ max provides useful information about the status of digital mammography units without affecting clinical operations. When used with appropriate action limits, this type of monitoring can help physicists identify specific equipment malfunctions before they would be detected by other quality control tests and before they affect clinical images.