Can virtual monochromatic images from dual-energy CT replace low-kVp images for abdominal contrast-enhanced CT in small- and medium-sized patients?

Increased water content in multifidus muscles of young adults with chronic nonspecific low back pain detected by dual-energy CT and MRI

OBJECTIVES

To demonstrate the feasibility of better diagnosing young adults with chronic nonspecific low back pain (CNLBP) by measuring water content in paraspinal muscles using water-muscle decomposition technique in dual-energy CT (DECT) and T2-mapping in MRI.

METHODS

This prospective cross-sectional study included 110 young individuals (56 with CNLBP at age of 25.7 ± 2.0 years and 54 of asymptomatic at age of 25.1 ± 1.9 years) who underwent both MRI and DECT on the spine. T2 values on T2 mapping in MRI and water density (WD) value on water(muscle) images in DECT were generated at the L1-L4 levels for erector spinae muscle and L2-L5 for multifidus muscle. Pain duration time, Oswestry Disability Index (ODI), Visual Analogue Scale (VAS) were recorded for CNLBP patients. Difference of T2 value and WD between the two patient groups, and correlations between T2 value and WD, and T2 value and WD with clinical indicators were analyzed.

RESULTS

Compared with asymptomatic participants, the mean WD of multifidus muscle at L4-L5 and mean T2 values of multifidus muscle at L5 were significantly higher in CNLBP patients (all P < 0.05). T2 values had moderate to strong positive correlations (r = 0.34-0.60, all P < 0.05) with DECT WD in CNLBP patients and healthy volunteers. There was a weak correlation between VAS and WD in L5-level multifidus muscle (r = 0.29, P < 0.05).

CONCLUSIONS

The T2 values in MRI and WD in DECT are higher in multifidus muscles of lower vertebra levels for young CNLBP patients, and there exists positive correlation between WD and T2 values, providing useful information for diagnosing CNLBP.

Predicting Osteoporosis and Osteopenia by Fusing Deep Transfer Learning Features and Classical Radiomics Features Based on Single-Source Dual-energy CT Imaging

RATIONALE AND OBJECTIVES

To develop and validate a predictive model for osteoporosis and osteopenia prediction by fusing deep transfer learning (DTL) features and classical radiomics features based on single-source dual-energy computed tomography (CT) virtual monochromatic imaging.

METHODS

A total of 606 lumbar vertebrae with dual-energy CT imaging and quantitative CT (QCT) evaluation were included in the retrospective study and randomly divided into the training (n = 424) and validation (n = 182) cohorts. Radiomics features and DTL features were extracted from 70-keV monochromatic CT images, followed by feature selection and model construction, radiomics and DTL features models were established. Then, we integrated the selected two types of features into a features fusion model. We developed a two-level classifier for the hierarchical pairwise classification of each vertebra. All the vertebrae were first classified into osteoporosis and non-osteoporosis groups, then non-osteoporosis group was classified into osteopenia and normal groups. QCT was used as reference. The predictive performance and clinical usefulness of three models were evaluated and compared.

RESULTS

The area under the curve (AUC) of the features fusion, radiomics and DTL models for the classification between osteoporosis and non-osteoporosis were 0.981, 0.999, 0.997 in the training cohort and 0.979, 0.943, 0.848 in the validation cohort. Furthermore, the AUCs of the previously mentioned models for the differentiation between osteopenia and normal were 0.994, 0.971, 0.996 in the training cohort and 0.990, 0.968, 0.908 in the validation cohort. The overall accuracy of the previously mentioned models for two-level classifications was 0.979, 0.955, 0.908 in the training cohort and 0.918, 0.885, 0.841 in the validation cohort. Decision curve analysis showed that all models had high clinical value.

CONCLUSION

The feature fusion model can be used for osteoporosis and osteopenia prediction with improved predictive ability over a radiomics model or a DTL model alone.

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI

OBJECTIVE

This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs).

METHODS

A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared.

RESULTS

DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups.

CONCLUSION

For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both.

CLINICAL RELEVANCE STATEMENT

The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs.

KEY POINTS

• DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. • DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. • On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.

Metallic artifacts-free spectral computed tomography angiography based on renal clearable bismuth chelate

Computed tomography angiography (CTA) is one of the most important diagnosis techniques for various vascular diseases in clinic. However, metallic artifacts caused by metal implants and calcified plaques in more and more patients severely hinder its wide applications. Herein, we propose an improved metallic artifacts-free spectral CTA technique based on renal clearable bismuth chelate (Bi-DTPA dimeglumine) for the first time. Bi-DTPA dimeglumine owns the merits of ultra-simple synthetic process, approximately 100% of yield, large-scale production capability, good biocompatibility, and favorable renal clearable ability. More importantly, Bi-DTPA dimeglumine shows superior contrast-enhanced effect in CTA compared with clinical iohexol at a wide range of X-ray energies especially in higher X-ray energy. In rabbits' model with metallic transplants, Bi-DTPA dimeglumine assisted-spectral CTA can not only effectively mitigate metallic artifacts by reducing beam hardening effect under high X-ray energy, but also enables accurate delineation of vascular structure. Our proposed strategy opens a revolutionary way to solve the bottleneck problem of metallic artifacts in CTA examinations.

Comparative study of abdominal CT enhancement in overweight and obese patients based on different scanning modes combined with different contrast medium concentrations

PURPOSE

To compare image quality, iodine intake, and radiation dose in overweight and obese patients undergoing abdominal computed tomography (CT) enhancement using different scanning modes and contrast medium.

METHODS

Ninety overweight and obese patients (25 kg/m2≤body mass index (BMI)< 30 kg/m2 and BMI≥30 kg/m2) who underwent abdominal CT-enhanced examinations were randomized into three groups (A, B, and C) of 30 each and scanned using gemstone spectral imaging (GSI) +320 mgI/ml, 100 kVp + 370 mgI/ml, and 120 kVp + 370 mgI/ml, respectively. Reconstruct monochromatic energy images of group A at 50-70 keV (5 keV interval). The iodine intake and radiation dose of each group were recorded and calculated. The CT values, contrast-to-noise ratios (CNRs), and subjective scores of each subgroup image in group A versus images in groups B and C were by using one-way analysis of variance or Kruskal-Wallis H test, and the optimal keV of group A was selected.

RESULTS

The dual-phase CT values and CNRs of each part in group A were higher than or similar to those in groups B and C at 50-60 keV, and similar to or lower than those in groups B and C at 65 keV and 70 keV. The subjective scores of the dual-phase images in group A were lower than those of groups B and C at 50 keV and 55 keV, whereas no significant difference was seen at 60-70 keV. Compared to groups B and C, the iodine intake in group A decreased by 12.5% and 13.3%, respectively. The effective doses in groups A and B were 24.7% and 25.8% lower than those in group C, respectively.

CONCLUSION

GSI +320 mgI/ml for abdominal CT-enhanced in overweight patients satisfies image quality while reducing iodine intake and radiation dose, and the optimal keV was 60 keV.

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy

OBJECTIVES

To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR).

METHODS

In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images.

RESULTS

Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates.

CONCLUSION

DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT.

CLINICAL RELEVANCE STATEMENT

Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose.

KEY POINTS

• The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques

OBJECTIVES

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF).

METHODS

A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison.

RESULTS

The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively.

CONCLUSION

The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations.

KEY POINTS

• This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Obesity-Related Pitfalls of Virtual versus True Non-Contrast Imaging-An Intraindividual Comparison in 253 Oncologic Patients

OBJECTIVES

Dual-source dual-energy CT (DECT) facilitates reconstruction of virtual non-contrast images from contrast-enhanced scans within a limited field of view. This study evaluates the replacement of true non-contrast acquisition with virtual non-contrast reconstructions and investigates the limitations of dual-source DECT in obese patients.

MATERIALS AND METHODS

A total of 253 oncologic patients (153 women; age 64.5 ± 16.2 years; BMI 26.6 ± 5.1 kg/m²) received both multi-phase single-energy CT (SECT) and DECT in sequential staging examinations with a third-generation dual-source scanner. Patients were allocated to one of three BMI clusters: non-obese: <25 kg/m² (n = 110), pre-obese: 25-29.9 kg/m² (n = 73), and obese: >30 kg/m² (n = 70). Radiation dose and image quality were compared for each scan. DECT examinations were evaluated regarding liver coverage within the dual-energy field of view.

RESULTS

While arterial contrast phases in DECT were associated with a higher CTDI_vol than in SECT (11.1 vs. 8.1 mGy; p < 0.001), replacement of true with virtual non-contrast imaging resulted in a considerably lower overall dose-length product (312.6 vs. 475.3 mGy·cm; p < 0.001). The proportion of DLP variance predictable from patient BMI was substantial in DECT (R² = 0.738) and SECT (R² = 0.620); however, DLP of SECT showed a stronger increase in obese patients (p < 0.001). Incomplete coverage of the liver within the dual-energy field of view was most common in the obese subgroup (17.1%) compared with non-obese (0%) and pre-obese patients (4.1%).

CONCLUSION

DECT facilitates a 30.8% dose reduction over SECT in abdominal oncologic staging examinations. Employing dual-source scanner architecture, the risk for incomplete liver coverage increases in obese patients.

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).

Prediction of osteoporosis using radiomics analysis derived from single source dual energy CT

BACKGROUND

With the aging population of society, the incidence rate of osteoporosis is increasing year by year. Early diagnosis of osteoporosis plays a significant role in the progress of disease prevention. As newly developed technology, computed tomography (CT) radiomics could discover radiomic features difficult to recognize visually, providing convenient, comprehensive and accurate osteoporosis diagnosis. This study aimed to develop and validate a clinical-radiomics model based on the monochromatic imaging of single source dual-energy CT for osteoporosis prediction.

METHODS

One hundred sixty-four participants who underwent both single source dual-energy CT and quantitative computed tomography (QCT) lumbar-spine examination were enrolled in a study cohort including training datasets (n = 114 [30 osteoporosis and 84 non-osteoporosis]) and validation datasets (n = 50 [12 osteoporosis and 38 non-osteoporosis]). One hundred seven radiomics features were extracted from 70-keV monochromatic CT images. With QCT as the reference standard, a radiomics signature was built by using least absolute shrinkage and selection operator (LASSO) regression on the basis of reproducible features. A clinical-radiomics model was constructed by incorporating the radiomics signature and a significant clinical predictor (age) using multivariate logistic regression analysis. Model performance was assessed by its calibration, discrimination and clinical usefulness.

RESULTS

The radiomics signature comprised 14 selected features and showed good calibration and discrimination in both training and validation cohorts. The clinical-radiomics model, which incorporated the radiomics signature and a significant clinical predictor (age), also showed good discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.938 (95% confidence interval, 0.903-0.952) in the training cohort and an AUC of 0.988 (95% confidence interval, 0.967-0.998) in the validation cohort, and good calibration. The clinical-radiomics model stratified participants into groups with osteoporosis and non-osteoporosis with an accuracy of 94.0% in the validation cohort. Decision curve analysis (DCA) demonstrated that the radiomics signature and the clinical-radiomics model were clinically useful.

CONCLUSIONS

The clinical-radiomics model incorporating the radiomics signature and a clinical parameter had a good ability to predict osteoporosis based on dual-energy CT monoenergetic imaging.

Comparison of image quality and pancreatic ductal adenocarcinoma conspicuity between the low-kVp and dual-energy CT reconstructed with deep-learning image reconstruction algorithm

PURPOSE

To compare the image quality and conspicuity of pancreatic ductal adenocarcinoma (PDAC) between the low-kVp and dual-energy pancreatic protocol CT reconstructed with deep-learning image reconstruction (DLIR).

METHOD

A cohort of 111 consecutive patients (median age, 72 years; 56 men) undergoing a pancreatic protocol CT were retrospectively analyzed. Among them, 58 patients underwent 80-kVp CT (80-kVp group), and 53 patients underwent dual-energy CT and reconstructed at 40-keV (40-keV group). The medium-strength level of DLIR were used in both groups. Quantitative measurements, qualitative image quality, PDAC conspicuity, and dose-length product (DLP) were compared between the two groups using Mann-Whitney U test.

RESULTS

A total of 20 and 16 PDACs were found in the 80-kVp and 40-keV groups, respectively. CT numbers of the vasculatures and parenchymal organs (P <.001 for all) and the background noise at both pancreatic and portal venous phases (P <.001) were higher in the 40-keV group than in the 80-kVp group. The signal-to-noise ratio (SNR) of all anatomical structures (P <.001-0.005), except for the liver in reviewer 2 (P =.47), and the tumor-to-pancreas contrast-to-noise ratio (CNR; P <.001-0.01) were higher in the 40-keV group than in the 80-kVp group. No difference was found in the image quality at both phases (P =.30-0.90). PDAC conspicuity was better in the 40-keV group than in the 80-kVp group (P =.007-0.03). DLP at pancreatic (275 vs. 313 mGy*cm; P =.05) and portal venous phases (743 vs. 766 mGy*cm; P =.20) was comparable between the two groups.

CONCLUSION

Under the same DLP, virtual monoenergetic images at 40-keV demonstrated higher SNR and tumor-to-pancreas CNR and better PDAC conspicuity compared to the 80-kVp setting.

A feasibility study of different GSI noise indexes and concentrations of contrast medium in hepatic CT angiography of overweight patients: image quality, radiation dose, and iodine intake

PURPOSE

To conduct a comparative study of image quality, radiation dose, and iodine intake in hepatic computed tomographic angiography (CTA) of overweight patients with different Gemstone Spectral Imaging (GSI) noise indexes combined with different concentrations of contrast medium.

MATERIALS AND METHODS

Ninety patients with a body mass index of ≥ 25 kg/m² were divided into three groups (A, B and C), each with 30 patients. The three groups underwent hepatic CTA with different NI of 7, 11 and 15, respectively, and were injected with different iodine concentrations of 370, 350 and 320 mgI/mL, respectively. Five sets of images at 40-60 keV (interval, 5 keV) were reconstructed in each group. The CT value, image noise, contrast-to-noise ratio (CNR) and subjective score of the hepatic artery and vein, and portal vein in different monochromatic image sets were analyzed to select the optimal energy level in each group. The differences in CT value, image noise, CNR and a subjective score of hepatic artery and vein, portal vein in the optimal monochromatic images among the three groups were compared, the volume CT dose index (CTDIvol) and dose-length product (DLP) were recorded, and the effective dose and iodine intake were calculated.

RESULTS

The 40 keV was determined to be the optimal energy level for the monochromatic image sets in each group. No significant group differences were noted in the CT value, image noise, CNR, and subjective image scores of the hepatic artery and vein, and portal vein for the optimal monochromatic images (P > 0.05). Compared with group A, the effective dose and iodine intake in group B were reduced by 50.18% and 9.3%, and by 58.12% and 14.23% in group C, respectively.

CONCLUSION

A low-concentration contrast medium combined with a high-noise GSI index in hepatic CTA of overweight patients can reduce the radiation dose and iodine intake while ensuring image quality.

Associations between paraspinal muscles fatty infiltration and lumbar vertebral bone mineral density - An investigation by fast kVp switching dual-energy CT and QCT

Purpose

To investigate the relationship between paraspinal muscles fat content and lumbar bone mineral density (BMD).

Methods

A total of 119 participants were enrolled in our study (60 males, age: 50.88 ± 17.79 years, BMI: 22.80 ± 3.80 kg·m^-2; 59 females, age: 49.41 ± 17.69 years, BMI: 22.22 ± 3.12 kg·m^-2). Fat content of paraspinal muscles (erector spinae (ES), multifidus (MS), and psoas (PS)) were measured at (ES L1/2-L4/5; MS L2/3-L5/S1; PS L2/3-L5/S1) levels using dual-energy computed tomography (DECT). Quantitative computed tomography (QCT) was used to assess BMD of L1 and L2. Linear regression analysis was used to assess the relationship between BMD of the lumbar spine and paraspinal muscles fat content with age, sex, and BMI. The variance inflation factor (VIF) was used to detect the degree of multicollinearity among the variables. P < .05 was considered to indicate a statistically significant difference.

Results

The paraspinal muscles fat content had a fairly significant inverse association with lumbar BMD after controlling for age, sex, and BMI (adjusted R ² = 0.584-0.630, all P < .05).

Conclusion

Paraspinal muscles fat content was negatively associated with BMD.Paraspinal muscles fatty infiltration may be considered as a potential marker to identify BMD loss.

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

OBJECTIVES

To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases.

METHODS

This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard.

RESULTS

DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 ± 3.23 vs. 6.05 ± 2.38 vs. 5.99 ± 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31).

CONCLUSIONS

DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images.

KEY POINTS

• DLM 40-keV VMI provides a superior image quality compared with 40-keV or 100-kVp for assessing hypoenhancing hepatic metastasis. • DLM 40-keV VMI has the highest CNR and lesion conspicuity score for hypoenhancing hepatic metastasis due to noise reduction and structural preservation. • DLM 40-keV VMI provides higher lesion detectability than standard 40-keV VMI (p = 0.012).

Reduced-Dose Full-Body CT in Lymphoma Follow-up: A Pilot Study

BACKGROUND

How to reduce the radiation dose received from full-body CT scans during the follow-up of lymphoma patients is a concern.

OBJECTIVE

The aim of the study was to investigate the image quality and radiation dose of reduced-dose full-body computerized tomography (CT) in lymphoma patients during the follow-up.

METHODS

121 patients were included and divided into conventional CT group (group 1, 120-kVp, n = 61) or reduced-dose CT group (group 2, 100-kVp combined dual-energy CT (DECT), n = 60). 140-kVp polychromatic images and 70-keV monochromatic images were reconstructed from DECT. The abdominal virtual non-enhanced (VNE) images were reconstructed from monochromatic images. Two radiologists rated the overall image quality with a five-point scale and graded the depiction of lesions using a four-point scale. The objective image quality was evaluated using image noise, signal-to-noise ratio, and contrast-to-noise ratio. The radiation dose and image quality were compared between the groups.

RESULTS

The comparable subjective image quality was observed between 70-keV and 120-kVp images in the neck, while 120-kVp images showed better objective image quality. 70-keV images showed better objective image quality in the chest. While the subjective image quality of abdominal VNE images was inferior to that of true non-enhanced images, the improved objective image quality was observed in VNE images. In the abdominal arterial phase, similar subjective image quality was observed between the groups. Abdominal 70-keV images in the arterial phase showed improved objective image quality. Similar image quality was obtained in the abdominal venous phase between the groups. The effective radiation dose in group 2 showed a significant reduction.

CONCLUSION

The application of reduced-dose full-body CT can significantly reduce the radiation dose for lymphoma patients during the follow-up while maintaining or improving the image quality.

Impact of dual-energy 50-keV virtual monoenergetic images on radiologist confidence in detection of key imaging findings of small hepatocellular carcinomas using multiphase liver CT

BACKGROUND

Dual-energy virtual monoenergetic images can increase iodine signal, potentially increasing the conspicuity of hepatic masses.

PURPOSE

To determine if dual-energy 50-keV virtual monoenergetic images improve visualization of key imaging findings or diagnostic confidence for small (≤2 cm) hepatocellular carcinomas (HCC) at multiphase, contrast-enhanced liver computed tomography (CT).

MATERIAL AND METHODS

Patients with chronic liver disease underwent multiphase dual-energy CT imaging for HCC, with late arterial and delayed phase dual-energy 50-keV images reconstructed. Two non-reader subspecialized gastrointestinal (GI) radiologists established the reference standard, determining the location and diagnosis of all hepatic lesions using predetermined criteria. Three GI radiologists interpreted mixed kV CT images without or with dual-energy 50-keV images. Radiologists identified potential HCCs and rated their confidence (0-100 scales) in imaging findings of arterial enhancement, enhancing capsule, tumor washout, and LI-RADS 5 (2018) category.

RESULTS

In total, 45 patients (14 women; mean age = 59.5 ± 10.9 years) with chronic liver disease were included. Of them, 19 patients had 25 HCCs ≤2 cm (mean size = 1.5 ± 0.4 cm). There were 17 LI-RADS 3 and 4 lesions and 19 benign lesions. Reader confidence in imaging findings of arterial enhancement, enhancing capsule, and non-peripheral washout significantly increased with dual-energy images (P ≤ 0.022). Overall confidence in HCC diagnosis increased significantly with dual-energy 50-keV images (52.4 vs. 68.8; P = 0.001). Dual-energy images demonstrated a slight but significant decrease in overall image quality.

CONCLUSION

Radiologist confidence in key imaging features of small HCCs and confidence in imaging diagnosis increases with use of dual-energy 50-keV images at multiphase, contrast-enhanced liver CT.

Computed Tomography Techniques, Protocols, Advancements, and Future Directions in Liver Diseases

Computed tomography (CT) is often performed as the initial imaging study for the workup of patients with known or suspected liver disease. Our article reviews liver CT techniques and protocols in clinical practice along with updates on relevant CT advances, including wide-detector CT, radiation dose optimization, and multienergy scanning, that have already shown clinical impact. Particular emphasis is placed on optimizing the late arterial phase of enhancement, which is critical to evaluation of hepatocellular carcinoma. We also discuss emerging techniques that may soon influence clinical care.

Comparison of low kVp CT and dual-energy CT for the evaluation of hypervascular hepatocellular carcinoma

PURPOSE

To compare lesion conspicuity and image quality of arterial phase images obtained from low kVp (90-kVp) and dual-energy (DE) scans for the evaluation of hypervascular hepatocellular carcinoma (HCC).

METHODS

This retrospective study included 229 patients with HCC who underwent either 90 kVp (n = 106) or DE scan (80- and 150-kVp with a tin filter) (n = 123) during the arterial phase. DE scans were reconstructed into a linearly blended image with a mixed ratio of 0.6 (60% 80kVp and 40% 150 kVp) and post-processed for 40 keV and 50 keV images. The contrast-to-noise ratio (CNR) of HCC to the liver and image noise was measured. Lesion conspicuity, liver parenchymal image quality, and overall image preference were assessed qualitatively by three independent radiologists.

RESULTS

DE 40 keV images had the highest CNR of HCC, and DE blended images had the lowest image noise among four image sets (p = 0.01 and p < 0.001, respectively). There was no significant difference in mean volume CT dose index and dose-length product between DE and low kVp scan (ps > 0.05). For qualitative analyses, DE blended images had the highest scores for image quality and overall image preference (ps < 0.001).

CONCLUSION

At an equal radiation dose, DE 40 keV showed higher CNR of HCC and DE blended image showed higher image quality and image preference compared with low kVp CT.

An Individualized Contrast-Enhanced Liver Computed Tomography Imaging Protocol Based on Body Mass Index in 126 Patients Seen for Liver Cirrhosis

Background

Computed tomography (CT) imaging using iodinated contrast medium is associated with the radiation dose to the patient, which may require reduction in individual circumstances. This study aimed to evaluate an individualized liver CT protocol based on body mass index (BMI) in 126 patients investigated for liver cirrhosis.

Material/Methods

From November 2017 to December 2020, in this prospective study, 126 patients with known or suspected liver cirrhosis were recruited. Patients underwent liver CT using individualized protocols based on BMI, as follows. BMI ≤24.0 kg/m²: 80 kV, 352 mg I/kg; BMI 24.1–28.0 kg/m²: 100 kV, 440 mg I/kg; BMI ≥28.1 kg/m²: 120 kV, 550 mg I/kg. Figure of merit (FOM) and size-specific dose estimates (SSDEs) were calculated and compared using the Mann-Whitney U test. Subjective image quality and timing adequacy of the late arterial phase were evaluated with Likert scales.

Results

The SSDE was significantly lower in the 80 kV protocol, corresponding to a dose reduction of 36% and 50% compared with the others (all P<0.001). In the comparison of 80-, 100-, and 120-kV protocols, no statistically significant differences were found in FOMs (P=0.108~0.620). Of all the examinations, 95.2% (120 of 126) were considered as appropriate timing for the late arterial phase. In addition, overall image quality, hepatocellular carcinoma conspicuity, and detection rate did not differ significantly among the 3 protocols (P=0.383~0.737).

Conclusions

This study demonstrated the feasibility of using an individualized liver CT protocol based on BMI, and showed that patients with lower BMI should receive lower doses of iodinated contrast medium and significantly reduced radiation dose.

Effect of deep learning image reconstruction in the prediction of resectability of pancreatic cancer: Diagnostic performance and reader confidence

OBJECTIVE

To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT) using a new deep learning image reconstruction (DLIR) algorithm.

METHODS

A retrospective review was conduct of on forty-seven patients with pathologically confirmed pancreatic cancers who underwent baseline multiphasic contrast-enhanced CT scan. Image data sets were reconstructed using filtered back projection (FBP), hybrid model-based adaptive statistical iterative reconstruction (ASiR-V) 60 %, and DLIR "TrueFidelity" at low(L), medium(M), and high strength levels(H). Four board-certified abdominal radiologists reviewed the CT images and classified cancers as resectable, borderline resectable, or unresectable. Diagnostic performance and reader confidence for categorizing the resectability of pancreatic cancer were evaluated based on the reference standards, and the interreader agreement was assessed using Fleiss k statistics.

RESULTS

For prediction of margin-negative resections(ie, R0), the average area under the receiver operating characteristic curve was significantly higher with DLIR-H (0.91; 95 % confidence interval [CI]: 0.79, 0.98) than FBP (0.75; 95 % CI:0.60, 0.86) and ASiR-V (0.81; 95 % CI:0.67, 0.91) (p = 0.030 and 0.023 respectively). Reader confidence scores were significantly better using DLIR compared to FBP and ASiR-V 60 % and increased linearly with the increase of DLIR strength level (all p < 0.001). Among the image reconstructions, DLIR-H showed the highest interreader agreement in the resectability classification and lowest subject variability in the reader confidence.

CONCLUSIONS

The DLIR-H algorithm may improve the diagnostic performance and reader confidence in the CT assignment of the local resectability of pancreatic cancer while reducing the interreader variability.

In vivo quantification of bone mineral density of lumbar vertebrae using fast kVp switching dual-energy CT: correlation with quantitative computed tomography

Background

Osteoporosis is a common, progressive disease related to low bone mineral density (BMD). If it can be diagnosed at an early stage, osteoporosis is treatable. Quantitative computed tomography (QCT) is one of the current reference standards of BMD measurement, but dual-energy computed tomography (DECT) is considered to be a potential alternative. This study aimed to evaluate the feasibility and accuracy of phantomless in vivo DECT-based BMD quantification in comparison with QCT.

Methods

A total of 128 consecutive participants who underwent DECT lumbar examinations between July 2018 and February 2019 were retrospectively analyzed. The density of calcium (water), hydroxyapatite (water), calcium (fat), and hydroxyapatite (fat) [D_Ca(Wa), D_HAP(Wa), D_Ca(Fat) and D_HAP(Fat), respectively] were measured along with BMD in the trabecular bone of lumbar level 1-2 by DECT and QCT. Linear regression analysis was performed to assess the relationship between DECT- and QCT-derived BMD at both the participant level and the vertebral level. Linear regression models were quantitatively evaluated with adjusted R-square, normalized mean squared error (NMSE) and relative error (RE). Bland-Altman analysis was conducted to assess agreement between measurements. P<0.05 was considered statistically significant.

Results

Strong correlations were observed between DECT- and QCT-derived BMD at both the participant level and the vertebral level (adjusted R² =0.983-0.987; NMSE = 1.6-2.1%; RE_linear =0.6-0.9%). Bland-Altman plots indicated high agreement between both measurements. D_Ca(Fat) and D_HAP(Fat) showed relatively similar and optimal predictive capability for QCT-derived BMD (both: adjusted R² =0.987, NMSE =1.6%, RE_linear =0.6%).

Conclusions

Fast kVp switching DECT enabled accurate phantomless in vivo BMD quantification of the lumbar spine. D_Ca(Fat) and D_HAP(Fat) had relatively similar and optimal predictive capability.

CTPA with a conventional CT at 100 kVp vs. a spectral-detector CT at 120 kVp: Comparison of radiation exposure, diagnostic performance and image quality

•

With SD-CT, increased radiation exposure is not present.

•

In the current study, CTDI_vol was lower with SD-CT than with C-CT, even when 100 kVp was used for the latter.

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With SD-CT, higher levels of diagnostic performance and image quality can be achieved.

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SD-CT may be the system of choice due to the availability of spectral data and thus additional image information.

Purpose

To compare CT pulmonary angiographies (CTPAs) as well as phantom scans obtained at 100 kVp with a conventional CT (C-CT) to virtual monochromatic images (VMI) obtained with a spectral detector CT (SD-CT) at equivalent dose levels as well as to compare the radiation exposure of both systems.

Material and Methods

In total, 2110 patients with suspected pulmonary embolism (PE) were examined with both systems. For each system (C-CT and SD-CT), imaging data of 30 patients with the same mean CT dose index (4.85 mGy) was used for the reader study. C-CT was performed with 100 kVp and SD-CT was performed with 120 kVp; for SD-CT, virtual monochromatic images (VMI) with 40, 60 and 70 keV were calculated. All datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence and diagnostic performance (sensitivity, specificity). Contrast-to-noise ratio (CNR) for different iodine concentrations was evaluated in a phantom study.

Results

CNR was significantly higher with VMI at 40 keV compared to all other datasets. Subjective image quality as well as sensitivity and specificity showed the highest values with VMI at 60 keV and 70 keV. Hereby, a significant difference to 100 kVp (C-CT) was found for image quality. The highest sensitivity was found using VMI at 60 keV with a sensitivity of more than 97 % for all localizations of PE. For diagnostic confidence and subjective contrast, highest values were found with VMI at 40 keV.

Conclusion

Higher levels of diagnostic performance and image quality were achieved for CPTAs with SD-CT compared to C-CT given similar dose levels. In the clinical setting SD-CT may be the modality of choice as additional spectral information can be obtained.