Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR). METHODS: A contrast-detail phantom consisting of low-contrast objects was scanned at five CT dose index levels (10, 6, 3, 2, and 1 mGy). A total of 154 participants with 305 hepatic lesions who underwent abdominal CT were enrolled in a prospective non-inferiority trial with a three-arm design based on phantom results. Data sets with full dosage (13.6 mGy) and low dosages (9.5, 6.8, or 4.1 mGy) were acquired from two consecutive portal venous acquisitions, respectively. All images were reconstructed with FBP (reference), IR (control), and DLIR (test). Eleven readers evaluated phantom data sets for object detectability using a two-alternative forced-choice approach. Non-inferiority analyses were performed to interpret the differences in image quality and metastasis detection of low-dose DLIR relative to full-dose FBP/IR. RESULTS: The phantom experiment showed the dose reduction potential from DLIR was up to 57% based on the reference FBP dose index. Radiation decreases of 30% and 50% resulted in non-inferior image quality and hepatic metastasis detection with DLIR compared to full-dose FBP/IR. Radiation reduction of 70% by DLIR performed inferiorly in detecting small metastases (< 1 cm) compared to full-dose FBP (difference: -0.112; 95% confidence interval [CI]: -0.178 to 0.047) and full-dose IR (difference: -0.123; 95% CI: -0.182 to 0.053) (p < 0.001). CONCLUSION: DLIR enables a 50% dose reduction for detecting low-contrast hepatic metastases while maintaining comparable image quality to full-dose FBP and IR. KEY POINTS: • Non-inferiority study showed that deep learning image reconstruction (DLIR) can reduce the dose to oncological patients with low-contrast lesions without compromising the diagnostic information. • Radiation dose levels for DLIR can be reduced to 50% of full-dose FBP and IR for detecting low-contrast hepatic metastases, while maintaining comparable image quality. • The reduction of radiation by 70% by DLIR is clinically acceptable but insufficient for detecting small low-contrast hepatic metastases (< 1 cm).

Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules.

OBJECTIVES: The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN). METHODS: CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared. The cohort was divided into a low-, medium-, and high-risk group based on the respective LCP scores; shifts between the groups were studied to evaluate the potential impact on nodule management. Two different malignancy risk score thresholds were analyzed: a higher threshold of ≥ 9 ("rule-in" approach) and a lower threshold of > 4 ("rule-out" approach). RESULTS: In total, 169 patients with 196 nodules could be included (mean age ± SD, 64.5 ± 9.2 year; 49% females). Mean LCP scores for original, 25% and 5% dose levels were 8.5 ± 1.7, 8.4 ± 1.7 (p > 0.05 vs. original dose) and 8.2 ± 1.9 (p < 0.05 vs. original dose), respectively. The proportion of correctly classified nodules with the "rule-in" approach decreased with simulated dose reduction from 58.2 to 56.1% (p = 0.34) and to 52.0% for the respective dose levels (p = 0.01). For the "rule-out" approach the respective values were 95.9%, 96.4%, and 94.4% (p = 0.12). When reducing the original dose to 25%/5%, eight/twenty-two nodules shifted to a lower, five/seven nodules to a higher malignancy risk group. CONCLUSION: CT dose reduction may affect the analyzed LCP-CNN regarding the classification of pulmonary malignancies and potentially alter pulmonary nodule management. CLINICAL RELEVANCE STATEMENT: Utilization of a "rule-out" approach with a lower malignancy risk threshold prevents underestimation of the nodule malignancy risk for the analyzed software, especially in high-risk cohorts. KEY POINTS: • LCP-CNN may be affected by CT image parameters such as noise resulting from low-dose CT acquisitions. • CT dose reduction can alter pulmonary nodule management recommendations by affecting the outcome of the LCP-CNN. • Utilization of a lower malignancy risk threshold prevents underestimation of pulmonary malignancies in high-risk cohorts.

High Spatial-Resolution Skull Base Imaging With Photon-Counting Computed Tomography and Energy-Integrating Computed Tomography: A Comparative Phantom Study.

ABSTRACT: Photon-counting computed tomography (PCCT) offers better high-resolution and noise performance than energy integrating detector (EID) CT. In this work, we compared both technologies for imaging of the temporal bone and skull base. A clinical PCCT system and 3 clinical EID CT scanners were used to image the American College of Radiology image quality phantom using a clinical imaging protocol with matched CTDI vol (CT dose index-volume) of 25 mGy. Images were used to characterize the image quality of each system across a series of high-resolution reconstruction options. Noise was calculated from the noise power spectrum, whereas resolution was quantified with a bone insert by calculating a task transfer function. Images of an anthropomorphic skull phantom and 2 patient cases were examined for visualization of small anatomical structures. Across measured conditions, PCCT had a comparable or smaller average noise magnitude (120 Hounsfield units [HU]) to the EID systems (144-326 HU). Photon-counting CT also had comparable resolution (task transfer function f25 : 1.60 mm -1 ) to the EID systems (1.34-1.77 mm -1 ). Imaging results supported quantitative findings as PCCT more clearly showed the 12-lp/cm bars from the fourth section of the American College of Radiology phantom and better represented the vestibular aqueduct and oval and round windows when compared with the EID scanners. A clinical PCCT system was able to image the temporal bone and skull base with improved spatial resolution and lower noise than clinical EID CT systems at matched dose.

Minimum perceivable size difference: how well can radiologists visually detect a change in lung nodule size from CT images?

OBJECTIVE: The purpose of this study was to determine how well radiologists could visually detect a change in lung nodule size on the basis of visual image perception alone. SUBJECTS AND METHODS: Under IRB approval, 109 standard chest CT image series were anonymized and exported from PACS. Nine hundred forty virtual lung nodule pairs (six baseline diameters, six relative volume differences, two nodule types-solid and ground glass-and 14 repeats) were digitally inserted into the chest CT image series (same location, different sizes between the pair). These digitally altered CT image pairs were shown to nine radiologists who were tasked to visually determine which image contained the larger nodule using a two-alternative forced-choice perception experimental design. These data were statistically analyzed using a generalized linear mixed effects model to determine how accurately the radiologists were able to correctly identify the larger nodule. RESULTS: Nominal baseline nodule diameter, relative volume difference, and nodule type were found to be statistically significant factors (p < 0.001) in influencing the radiologists' accuracy. For solid (ground-glass) nodules, the baseline diameter needed to be at least 6.3 mm (13.2 mm) to be able to visually detect a 25% change in volume with 95 ± 1.4% accuracy. Accuracy was lowest for the nodules with the smallest baseline diameters and smallest relative volume differences. Additionally, accuracy was lower for ground-glass nodules compared to solid nodules. CONCLUSIONS: Factors that impacted visual size assessment were baseline nodule diameter, relative volume difference, and solid versus non-solid nodule type, with larger and more solid lesions offering a more precise assessment of change. KEY POINTS: • For solid nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 6.3-mm baseline diameter. • For ground-glass nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 13.2-mm baseline diameter. • Accuracy in detecting a change in nodule size began to stabilize around 90-100% for nodules with larger baseline diameters (> 8 mm for solid nodules, > 12 mm for ground-glass nodules) and larger relative volume differences (>15% for solid nodules, > 25% for ground-glass nodules).

Optimizing Identification of Power Injectable Ports on the Scout Images for Multidetector Computed Tomography Procedures.

OBJECTIVE: The objective of this study was to assess the impact of tube voltage and image display on the identification of power ports features on anterior-posterior scout images to inform optimal workflow for multidetector computed tomography (MDCT) examinations. MATERIALS AND METHODS: Four ports, representing variable material composition (titanium/silicone), shapes, and computed tomography (CT) markings, were imaged on an adult anthropomorphic chest phantom using a dual-source MDCT at variable peak tube voltages (80, 100, 120, 150, and Sn150 kVp). Images were reviewed at variable image display setting by 5 blinded readers to assess port features of material composition, shape, and text markings as well as overall preferred image quality. RESULTS: Material composition was correctly identified for all ports by all readers across all kilovoltage-peak settings. The identification by shape was more reliable than CT markers for all but one of the ports. CT marker identification was up to 80% for titanium ports at window level settings optimized for metal (window width, 200; window center, -150) and at a soft tissue setting (window width, 400; window center, 40) for silicone ports. Interreader agreement for best image quality per kilovoltage-peak setting was moderate to substantial for 3 ports (k = 0.5-0.62) but only fair for 1 port (k = 0.27). The highest overall rank for image quality was given unanimously to Sn150 kVp for imaging titanium ports and 100 kVp for silicone ports. CONCLUSIONS: Power port identification on MDCT scout images can be optimized with modification of MDCT scout acquisition and display settings based on the main port material.

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 (0.5, 1, 2, and 5 mg/ml) and one calcium insert (100 mg/ml) equally spaced in a cylindrical water-equivalent background. The imaging protocol was based on a clinical DECT abdominal protocol capable of producing material specific concentration maps, virtual unenhanced images, and virtual monochromatic images. The QC automated analysis software uses open-source technologies which integrates well with our current automated CT QC database. The QC program was tested on a GE 750 HD scanner and two Siemens SOMATOM FLASH scanners over a 3-month period. The automated algorithm correctly identified the appropriate region of interest (ROI) locations and stores measured values in a database for monitoring and trend analysis. Slight variations in protocol settings were noted based on manufacturer. Overall, the project proved to provide a convenient and dependable clinical tool for routine oversight of DE CT imaging within the clinic.

Reproducibility of CT Radiomic Features within the Same Patient: Influence of Radiation Dose and CT Reconstruction Settings.

Background Results of recent phantom studies show that variation in CT acquisition parameters and reconstruction techniques may make radiomic features largely nonreproduceable and of limited use for prognostic clinical studies. Purpose To investigate the effect of CT radiation dose and reconstruction settings on the reproducibility of radiomic features, as well as to identify correction factors for mitigating these sources of variability. Materials and Methods This was a secondary analysis of a prospective study of metastatic liver lesions in patients who underwent staging with single-energy dual-source contrast material-enhanced staging CT between September 2011 and April 2012. Technique parameters were altered, resulting in 28 CT data sets per patient that included different dose levels, section thicknesses, kernels, and reconstruction algorithm settings. By using a training data set (n = 76), reproducible intensity, shape, and texture radiomic features (reproducibility threshold, R2 ≥ 0.95) were selected and correction factors were calculated by using a linear model to convert each radiomic feature to its estimated value in a reference technique. By using a test data set (n = 75), the reproducibility of hierarchical clustering based on 106 radiomic features measured with different CT techniques was assessed. Results Data in 78 patients (mean age, 60 years ± 10; 33 women) with 151 liver lesions were included. The percentage of radiomic features deemed reproducible for any variation of the different technical parameters was 11% (12 of 106). Of all technical parameters, reconstructed section thickness had the largest impact on the reproducibility of radiomic features (12.3% [13 of 106]) if only one technical parameter was changed while all other technical parameters were kept constant. The results of the hierarchical cluster analysis showed improved clustering reproducibility when reproducible radiomic features with dedicated correction factors were used (ρ = 0.39-0.71 vs ρ = 0.14-0.47). Conclusion Most radiomic features are highly affected by CT acquisition and reconstruction settings, to the point of being nonreproducible. Selecting reproducible radiomic features along with study-specific correction factors offers improved clustering reproducibility. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.

How accurate and precise are CT based measurements of iodine concentration? A comparison of the minimum detectable concentration difference among single source and dual source dual energy CT in a phantom study.

OBJECTIVES: To assess the impact of scan- and patient-related factors on the error and the minimum detectable difference in iodine concentration among different generations of single-source (SS) fast kV-switching and dual-source (DS) dual-energy CT (DECT). METHODS: Lesions having eight different iodine concentrations (0.2-4 mgI/mL) were emulated in a 3D-printed phantom of medium and large size. Each combination of concentration and size was scanned in dual-energy mode on four different SS and DS DECTs. Radiation doses were 7 and 10 mGy (medium size) and 10, 13, and 16 mGy (large size). Iodine maps were reconstructed with filtered back projection (FBP) and vendor-specific iterative reconstruction algorithms (IRs). Absolute error of iodine quantification (E) was measured. Multivariate regression models determined the influence of CT scanner, iodine concentration, phantom size, radiation dose, and reconstruction algorithm on E. The minimum detectable difference in iodine concentration (ICmin) under the same imaging conditions (intra-conditional) and among different imaging conditions (inter-conditional) was calculated. RESULTS: The error was significantly lower in current than in previous DECT generations (p < 0.001). For all CT scanner conditions, the error was significantly higher with increasing phantom size and decreasing radiation dose (p < 0.001). Iodine concentration only significantly affected the error for SS DECT (p < 0.001). ICmin depended on patient- and scan-related factors and ranged from 0.4 to 1.5 mgI/mL. CONCLUSIONS: Patient- and scan-related factors have a significant impact on the error and minimum detectable difference in iodine concentration within and among SS fast kV-switching and DS DECT. KEY POINTS: • Patient- and scan-related factors have a significant impact on the error and minimum detectable difference in dual-energy CT-based iodine quantification. • Third-generation DECTs outperformed second-generation scanners for both single-source and dual-source dual-energy CT. • The minimum intra- and inter-conditional detectable difference in iodine concentration ranged from 0.4 to 1.5 mg iodine/mL.

High-Pitch Wide-Coverage Fast-Kilovoltage-Switching Dual-Energy CT: Impact of Pitch on Noise, Spatial Resolution, and Iodine Quantification in a Phantom Study.

OBJECTIVE: The purpose of this study was to assess the impact of high pitch values on image noise, spatial resolution, and iodine quantification in single-source wide-coverage fast-kilovoltage-switching dual-energy CT (DECT). MATERIALS AND METHODS: Two phantom experiments were conducted. First, image noise and spatial resolution in the x-, y-, and z-directions were assessed. Second, the accuracy of iodine quantification was investigated with multiple-size phantoms with pure iodine and blood-iodine inserts. Both phantoms were scanned repeatedly with a third-generation fast-kilovoltage-switching DECT scanner with a collimation width of 80 mm at four different pitch values (0.5, 0.99, 1.375, 1.53) and three different gantry rotation times (0.6, 0.8, 1.0 second). Image noise, spatial resolution, and absolute error of iodine concentration (E) were measured. A linear mixed effects model was used to determine the effect of pitch, rotation time, and size on the error of iodine concentration. RESULTS: Image noise and xy spatial resolution were comparable among the four pitch values. Spatial resolution in the z-direction was inferior and had higher variance at a low pitch of 0.5 compared with pitches of 0.99, 1.375, and 1.53. Error of iodine concentration was significantly affected by pitch and rotation time (p < 0.001). E decreased with increasing pitch and decreasing rotation time. In detail, mean E was 0.91 ± 0.47 mg I/mL for a pitch of 0.5, 0.52 ± 0.29 mg I/mL for 0.99, 0.44 ± 0.25 mg I/mL for 1.375, and 0.40 ± 0.25 mg I/mL for 1.53. CONCLUSION: High-pitch wide-coverage fast-kilovoltage-switching DECT can be performed without impairing image quality or iodine quantification, and the results are superior to those of imaging at a low pitch of 0.5.

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

OBJECTIVE. 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. MATERIALS AND METHODS. 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. An institutional informatics system was used to automatically extract protocol type, patient diameter, volume CT dose index, and noise magnitude from images. The data were divided into five reference patient size ranges. Noise reference level, noise reference range, dose reference level, and dose reference range were defined for each size range. RESULTS. The data exhibited strong dependence between dose and patient size, weak dependence between noise and patient size, and different trends for different manufacturers with differing strategies for tube current modulation. The results suggest size-based reference intervals and levels for noise and dose (e.g., noise reference level and noise reference range of 11.5-12.9 HU and 11.0-14.0 HU for chest CT and 10.1-12.1 HU and 9.4-13.7 HU for abdominopelvic CT examinations) that can be targeted to improve clinical performance consistency. CONCLUSION. New reference levels and ranges, which simultaneously consider image noise and radiation dose information across wide patient populations, were defined and determined for two clinical protocols. The methods of new quantitative constraints may provide unique and useful information about the goal of managing the variability of image quality and dose in clinical CT examinations.

A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.

OBJECTIVE: The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. MATERIALS AND METHODS: A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1.25-10 mGy). Images were reconstructed with filtered back projection (FBP), ASIR-V with 50% blending with FBP (ASIR-V 50%), and ASIR-V without blending (ASIR-V 100%). In the first phantom, noise properties were assessed by noise power spectrum analysis. Spatial resolution properties were measured by use of task transfer functions for objects of different contrasts. Noise magnitude, noise texture, and resolution were compared between the three groups. In the second phantom, low-contrast detectability was assessed by nine human readers independently for each condition. The dose reduction potential of ASIR-V was estimated on the basis of a generalized linear statistical regression model. RESULTS: On average, image noise was reduced 37.3% with ASIR-V 50% and 71.5% with ASIR-V 100% compared with FBP. ASIR-V shifted the noise power spectrum toward lower frequencies compared with FBP. The spatial resolution of ASIR-V was equivalent or slightly superior to that of FBP, except for the low-contrast object, which had lower resolution. Lesion detection significantly increased with both ASIR-V levels (p = 0.001), with an estimated radiation dose reduction potential of 15% ± 5% (SD) for ASIR-V 50% and 31% ± 9% for ASIR-V 100%. CONCLUSION: ASIR-V reduced image noise and improved lesion detection compared with FBP and had potential for radiation dose reduction while preserving low-contrast detectability.

Effect of Radiation Dose Reduction and Reconstruction Algorithm on Image Noise, Contrast, Resolution, and Detectability of Subtle Hypoattenuating Liver Lesions at Multidetector CT: Filtered Back Projection versus a Commercial Model-based Iterative Reconstruction Algorithm.

Purpose To determine the effect of radiation dose and iterative reconstruction (IR) on noise, contrast, resolution, and observer-based detectability of subtle hypoattenuating liver lesions and to estimate the dose reduction potential of the IR algorithm in question. Materials and Methods This prospective, single-center, HIPAA-compliant study was approved by the institutional review board. A dual-source computed tomography (CT) system was used to reconstruct CT projection data from 21 patients into six radiation dose levels (12.5%, 25%, 37.5%, 50%, 75%, and 100%) on the basis of two CT acquisitions. A series of virtual liver lesions (five per patient, 105 total, lesion-to-liver prereconstruction contrast of -15 HU, 12-mm diameter) were inserted into the raw CT projection data and images were reconstructed with filtered back projection (FBP) (B31f kernel) and sinogram-affirmed IR (SAFIRE) (I31f-5 kernel). Image noise (pixel standard deviation), lesion contrast (after reconstruction), lesion boundary sharpness (average normalized gradient at lesion boundary), and contrast-to-noise ratio (CNR) were compared. Next, a two-alternative forced choice perception experiment was performed (16 readers [six radiologists, 10 medical physicists]). A linear mixed-effects statistical model was used to compare detection accuracy between FBP and SAFIRE and to estimate the radiation dose reduction potential of SAFIRE. Results Compared with FBP, SAFIRE reduced noise by a mean of 53% ± 5, lesion contrast by 12% ± 4, and lesion sharpness by 13% ± 10 but increased CNR by 89% ± 19. Detection accuracy was 2% higher on average with SAFIRE than with FBP (P = .03), which translated into an estimated radiation dose reduction potential (±95% confidence interval) of 16% ± 13. Conclusion SAFIRE increases detectability at a given radiation dose (approximately 2% increase in detection accuracy) and allows for imaging at reduced radiation dose (16% ± 13), while maintaining low-contrast detectability of subtle hypoattenuating focal liver lesions. This estimated dose reduction is somewhat smaller than that suggested by past studies. © RSNA, 2017 Online supplemental material is available for this article.

Dual-Source Single-Energy Multidetector CT Used to Obtain Multiple Radiation Exposure Levels within the Same Patient: Phantom Development and Clinical Validation.

Purpose To develop, in a phantom environment, a method to obtain multidetector computed tomographic (CT) data sets at multiple radiation exposure levels within the same patient and to validate its use for potential dose reduction by using different image reconstruction algorithms for the detection of liver metastases. Materials and Methods The American College of Radiology CT accreditation phantom was scanned by using a dual-source multidetector CT platform. By adjusting the radiation output of each tube, data sets at six radiation exposure levels (100%, 75%, 50%, 37.5%, 25%, and 12.5%) were reconstructed from two consecutive dual-source single-energy (DSSE) acquisitions, as well as a conventional single-source acquisition. A prospective, HIPAA-compliant, institutional review board-approved study was performed by using the same DSSE strategy in 19 patients who underwent multidetector CT of the liver for metastatic colorectal cancer. All images were reconstructed by using conventional weighted filtered back projection (FBP) and sinogram-affirmed iterative reconstruction with strength level of 3 (SAFIRE-3). Objective image quality metrics were compared in the phantom experiment by using multiple linear regression analysis. Generalized linear mixed-effects models were used to analyze image quality metrics and diagnostic performance for lesion detection by readers. Results The phantom experiment showed comparable image quality between DSSE and conventional single-source acquisition. In the patient study, the mean size-specific dose estimates for the six radiation exposure levels were 13.0, 9.8, 5.8, 4.4, 3.2, and 1.4 mGy. For each radiation exposure level, readers' perception of image quality and lesion conspicuity was consistently ranked superior with SAFIRE-3 when compared with FBP (P ≤ .05 for all comparisons). Reduction of up to 62.5% in radiation exposure by using SAFIRE-3 yielded similar reader rankings of image quality and lesion conspicuity when compared with routine-dose FBP. Conclusion A method was developed and validated to synthesize multidetector CT data sets at multiple radiation exposure levels within the same patient. This technique may provide a foundation for future clinical trials aimed at estimating potential radiation dose reduction by using iterative reconstructions. © RSNA, 2016 Online supplemental material is available for this article.

Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.

PURPOSE: To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). MATERIALS AND METHODS: Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. RESULTS: Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998). CONCLUSION: Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.

Diagnostic Performance of an Advanced Modeled Iterative Reconstruction Algorithm for Low-Contrast Detectability with a Third-Generation Dual-Source Multidetector CT Scanner: Potential for Radiation Dose Reduction in a Multireader Study.

PURPOSE: To assess the effect of radiation dose reduction on low-contrast detectability by using an advanced modeled iterative reconstruction (ADMIRE; Siemens Healthcare, Forchheim, Germany) algorithm in a contrast-detail phantom with a third-generation dual-source multidetector computed tomography (CT) scanner. MATERIALS AND METHODS: A proprietary phantom with a range of low-contrast cylindrical objects, representing five contrast levels (range, 5-20 HU) and three sizes (range, 2-6 mm) was fabricated with a three-dimensional printer and imaged with a third-generation dual-source CT scanner at various radiation dose index levels (range, 0.74-5.8 mGy). Image data sets were reconstructed by using different section thicknesses (range, 0.6-5.0 mm) and reconstruction algorithms (filtered back projection [FBP] and ADMIRE with a strength range of three to five). Eleven independent readers blinded to technique and reconstruction method assessed all data sets in two reading sessions by measuring detection accuracy with a two-alternative forced choice approach (first session) and by scoring the total number of visible object groups (second session). Dose reduction potentials based on both reading sessions were estimated. Results between FBP and ADMIRE were compared by using both paired t tests and analysis of variance tests at the 95% significance level. RESULTS: During the first session, detection accuracy increased with increasing contrast, size, and dose index (diagnostic accuracy range, 50%-87%; interobserver variability, ±7%). When compared with FBP, ADMIRE improved detection accuracy by 5.2% on average across the investigated variables (P < .001). During the second session, a significantly increased number of visible objects was noted with increasing radiation dose index, section thickness, and ADMIRE strength over FBP (up to 80% more visible objects, P < .001). Radiation dose reduction potential ranged from 56% to 60% and from 4% to 80% during the two sessions, respectively. CONCLUSION: Low-contrast detectability performance increased with increasing object size, object contrast, dose index, section thickness, and ADMIRE strength. Compared with FBP, ADMIRE allows a substantial radiation dose reduction while preserving low-contrast detectability. Online supplemental material is available for this article.

Development of a separability index for task specific characterization of spectral computed tomography.

PURPOSE: In this work, we define a signal detection based metrology to characterize the separability of two different multi-dimensional signals in spectral CT acquisitions. METHOD: Signal response was modelled as a random process with a deterministic signal and stochastic noise component. A linear Hotelling observer was used to estimate a scalar test statistic distribution that predicts the likelihood of an intensity value belonging to a signal. Two distributions were estimated for two materials of interest and used to derive two metrics separability: a separability index (s') and the area under the curve of the test statistic distributions. Experimental and simulated data of photon-counting CT scanners were used to evaluate each metric. Experimentally, vials of iodine and gadolinium (2, 4, 8 mg/mL) were scanned at multiple tube voltages, tube currents and energy thresholds. Additionally, a simulated dataset with low tube current (10-150 mAs) and material concentrations (0.25-4 mg/mL) was generated. RESULTS: Experimental data showed that conditions favorable for low noise and expression of k-edge signal produced the highest separability. Material concentration had the greatest impact on separability. The simulated data showed that under more difficult separation conditions, difference in material concentration still had the greatest impact on separability. CONCLUSION: The results demonstrate the utility of a task specific metrology to measure the overlap in signal between different materials in spectral CT. Using experimental and simulated data, the separability index was shown to describe the relationship between image formation factors and the signal responses of material.

Relating noise to image quality indicators in CT examinations with tube current modulation.

OBJECTIVE: Modern CT systems use surrogates of noise-noise index (NI) and quality reference effective tube current-time product (Q)-to infer the quality of images acquired using tube current modulation. This study aimed to determine the relationship between actual noise and these surrogates for two CT scanners from two different manufacturers. MATERIALS AND METHODS: Two phantoms (adult and 1-year-old child) were imaged on two CT scanners (64 and 128 MDCT) using a clinical range of NI (6-22) and Q (30-300 mA). Each scan was performed twice, and noise was measured in the mediastinum, lung, and abdomen using an image subtraction technique. The effect on noise from changing other imaging parameters, such as beam collimation, pitch, peak kilovoltage, slice thickness, FOV, reconstruction kernel or algorithm, and patient age category (adult or pediatric), was investigated. RESULTS: On the 64-MDCT scanner, noise increased linearly along with NI, with the slope affected by changing the anatomy of interest, peak kilovoltage, reconstruction algorithm, and convolution kernel. The noise-NI relationship was independent of phantom size, slice thickness, pitch, FOV, and beam width. On the 128-MDCT scanner, noise decreased nonlinearly along with increasing Q, slice thickness, and peak tube voltage. The noise-Q relationship also depended on anatomy of interest, phantom size, age selection, and reconstruction algorithm but was independent of pitch, FOV, and detector configuration. CONCLUSION: We established how noise changes with changing image quality indicators across a clinically relevant range of imaging parameters. This work can aid in optimizing protocols by targeting specific noise levels for different types of CT examinations.

Making CT Dose Monitoring Meaningful: Augmenting Dose with Imaging Quality.

Due to the concerns about radiation dose associated with medical imaging, radiation dose monitoring systems (RDMSs) are now utilized by many radiology providers to collect, process, analyze, and manage radiation dose-related information. Currently, most commercially available RDMSs focus only on radiation dose information and do not track any metrics related to image quality. However, to enable comprehensive patient-based imaging optimization, it is equally important to monitor image quality as well. This article describes how RDMS design can be extended beyond radiation dose to simultaneously monitor image quality. A newly designed interface was evaluated by different groups of radiology professionals (radiologists, technologists, and physicists) on a Likert scale. The results show that the new design is effective in assessing both image quality and safety in clinical practices, with an overall average score of 7.8 out of 10.0 and scores ranging from 5.5 to 10.0. Radiologists rated the interface highest at 8.4 out of 10.0, followed by technologists at 7.6 out of 10.0, and medical physicists at 7.5 out of 10.0. This work demonstrates how the assessment of the radiation dose can be performed in conjunction with the image quality using customizable user interfaces based on the clinical needs associated with different radiology professions.

Impact Evaluation of a Resident-Driven Research Training Workshop in Idaho: A Feasibility Study.

Objectives: Engagement in research activities is a critical component of clinical residency training. It is vital to build research capacity of residents to help interpret evidence-based medicine and design quality improvement projects. A mixed methods study was conducted to assess the impact of a 1-day research training workshop conducted at Eastern Idaho Regional Medical Centre, Idaho in May 2022. The workshop was targeted to improve the research knowledge of current clinical residents of Internal Medicine and Family Medicine. Methods: Workshop comprised of expert presentations, with assessment of difference in knowledge with a pretest and post-test. The sessions were organized around the core competencies of Institute of Medicine. Suggestions were also gathered from the audience. A pretest and post-test based on 13 questions was administered to the participants to assess change in research-related knowledge. Comments and suggestions of the participants were also recorded. Wilcoxon rank test was applied to determine statistical difference across each question and cumulative knowledge score. Conventional content analysis was applied to explore the comments and feedback. Results: The mean score of participants improved across all 12 questions. Statistically significant results were observed for the questions about types of studies qualifying as qualitative research. The cumulative score of participants increased in the post-test from 8.57 to 9.35. The participants gained new knowledge (94.3%), and felt more comfortable in application of research methods (74.3%). Encouraging feedback was obtained from the audience. They stated that they had benefited from the workshop and felt more prepared and motivated to indulge in scholarly activities. Conclusion: The study shows improvement in research-related knowledge of clinical residents attending a 1-day training workshop. We recommend inclusion of such workshops in the curriculum of residents for skill building and enhanced indulgence in research activities in order to prepare them as future leaders in quality improvement, health policy, and hospital administration.