Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters

OBJECTIVE

To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve.

RESULTS

Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency.

CONCLUSIONS

The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients.

CRITICAL RELEVANCE STATEMENT

The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression.

KEY POINTS

• Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.

Effect of iodine concentration reduction by comparison of virtual monoenergetic image quality with dual-energy computed tomography

This study aimed to evaluate the image quality of virtual monoenergetic images (VMIs) with tube voltage modulation in pediatric abdominal computed tomography (CT) examination and to determine the effect of decreasing contrast agent concentration. Using a 1-year old pediatric phantom, five contrast agent concentration diluent tubes of 100%, 80%, 60%, 40%, and 20% of the same concentration as the average Hounsfield unit (HU) in the descending aorta were inserted, and the mixed image and VMIs (40, 60, and 80 keV) acquired using dual-energy CT were compared with single-energy CT (SECT) images. For quantitative evaluation, the HU and coefficient of variation (COV) of each image were compared and analyzed. The analysis revealed that the HU of the 40 keV VMIs, acquired with a tube voltage of 70 kV and 100% contrast agent concentration, was 61% higher than that of the SECT image. The results showed that SECT had the lowest COV among all contrast agent concentration and tube voltage combinations, while the 40 keV image acquired at 70 kV had the second-lowest COV value. The HU of the 40 keV image acquired at 70 kV at a contrast agent concentration of 100% was 9% higher than that of SECT at 80% concentration. This study confirms that 40 keV VMIs are more useful than SECT images for vascular diagnosis with contrast in pediatric abdominal CT examinations and that a 20% reduction in contrast agent concentration can reduce the risk of contrast agent concentration-induced nephrotoxicity in pediatric patients by increasing the subjective acceptability of image quality for diagnosis.

The evolution and current situation in the application of dual-energy computed tomography: a bibliometric study

Background

Dual-energy computed tomography (DECT) has received extensive attention in clinical practice; however, a quantitative assessment of published literature in this domain is presently lacking. This study thus aimed to characterize the application conditions, developmental trends, and research hot spots of DECT using bibliometric analysis.

Methods

All literature on DECT was retrieved from the Web of Science Core Collection (WoSCC) on January 22, 2023. The co-occurrence, cooperation network, and co-citation of countries, institutions, references, authors, journals, and keywords were analyzed using CiteSpace, VOSviewer, and R-bibliometrix software.

Results

In total, 4,720 original articles and reviews were included. The number of publications related to DECT has rapidly increased since 2006. The USA (n=1,662) and Mayo Clinic (n=178) were found to be the most productive country and institution, respectively. The most cited article was published by Johnson TRC et al., while the article published by McCollough CH et al. in 2015 had the most co-citations. Schoepf UJ ranked first with most articles among 16,838 authors. The journal with the most published articles was European Radiology, with 411 publications. The timeline analysis indicated that material decomposition was the most recent topic, followed by gout, radiomics, proton therapy, and bone marrow edema.

Conclusions

An increasing number of researchers are committed to researching DECT, with the USA making the most significant contributions in this area. Prior studies have primarily concentrated on cardiovascular diseases, and contemporary hot spots include expansion into to other fields, such as iodine quantification, deep learning, and bone marrow edema.

Lobar pulmonary perfusion quantification with dual-energy CT angiography: Interlobar variability and relationship with regional clot burden in pulmonary embolism

Purpose

Semi-automated lobar segmentation tools enable an anatomical assessment of regional pulmonary perfusion with Dual-Energy CTA (DE-CTA). We aimed to quantify lobar pulmonary perfusion with DE-CTA, analyze the perfusion distribution among the pulmonary lobes in subjects without cardiopulmonary diseases and assess the correlation between lobar perfusion and regional endoluminal clots in patients with acute pulmonary embolism (PE).

Methods

We evaluated 151 consecutive subjects with suspected PE and without cardiopulmonary comorbidities. DE-CTA derived perfused blood volume (PBV) of each pulmonary lobe was measured applying a semi-automated lobar segmentation technique. In patients with PE, blood clot location was assessed, and CT-based vascular obstruction index of each lobe (CTOI_lobe) was calculated and classified into three groups: CTOI_lobe= 0, low CTOI_lobe (1–50%) and high CTOI_lobe (>50%).

Results

Among patients without PE (103/151, 68.2%), median lobar PBV was 13.7% (IQR 10.2–18.0%); the right middle lobe presented lower PBV when compared to all the other lobes (p < .001). In patients with PE (48/151, 31.8%), lobar PBV was 12.6% (IQR 9.6–15.7%), 13.7% (IQR 10.1–16.7%) and 6.5% (IQR 5.1–10.2%) in the lobes with CTOI_lobe= 0, low CTOI_lobe and high CTOI_lobe scores, respectively, with a significantly decreased PBV in the lobes with high CTOI_lobe score (p < .001). ROC analysis of lobar PBV for prediction of high CTOI_lobe score revealed AUC of 0.847 (95%CI 0.785–0.908).

Conclusion

Pulmonary perfusion was heterogeneously distributed along the pulmonary lobes in patients without cardiopulmonary diseases. In patients with PE, the lobes with high vascular obstruction score (CTOI_lobe> 50%) presented a decreased lobar perfusion.

•

Semi-automated tools enable assessment of lobar perfusion with Dual-Energy CTA.

•

The pulmonary perfusion is heterogeneously distributed along the pulmonary lobes.

•

Lobar perfusion was decreased only in the lobes with high vascular obstruction index.

Projection decomposition via univariate optimization for dual-energy CT

Dual-energy computed tomography (DECT) acquires two x-ray projection datasets with different x-ray energy spectra, performs material-specific image reconstruction based on the energy-dependent non-linear integral model, and provides more accurate quantification of attenuation coefficients than single energy spectrum CT. In the diagnostic energy range, x-ray energy-dependent attenuation is mainly caused by photoelectric absorption and Compton scattering. Theoretically, these two physical components of the x-ray attenuation mechanism can be determined from two projection datasets with distinct energy spectra. Practically, the solution of the non-linear integral equation is complicated due to spectral uncertainty, detector sensitivity, and data noise. Conventional multivariable optimization methods are prone to local minima. In this paper, we develop a new method for DECT image reconstruction in the projection domain. This method combines an analytic solution of a polynomial equation and a univariate optimization to solve the polychromatic non-linear integral equation. The polynomial equation of an odd order has a unique real solution with sufficient accuracy for image reconstruction, and the univariate optimization can achieve the global optimal solution, allowing accurate and stable projection decomposition for DECT. Numerical and physical phantom experiments are performed to demonstrate the effectiveness of the method in comparison with the state-of-the-art projection decomposition methods. As a result, the univariate optimization method yields a quality improvement of 15% for image reconstruction and substantial reduction of the computational time, as compared to the multivariable optimization methods.

Evaluating image quality and optimal parameters for non-linear blending dual-energy computed tomography images of hepatic portal veins by blending-property-map

BACKGROUND

Blending technology is usually used to improve quality of dual-energy computed (DECT) images.

OBJECTIVES

To evaluate the blended DECT image qualities by employing the Blending-Property-Map (BP-Map) and elucidating the optimal parameters with the highest signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).

METHODS

Sixty pairs of 80 kV and 140 kV CT images are blended non-linearly by four methods. Protocol A uses the fixed values of blending width (BW) and blending center (BC); Protocol B uses the values of BW =  (CThepatic portal vein - CThepatic parenchymal) / 2 and BC =  (CThepatic portal vein + CThepatic parenchymal) / 2; Protocol C uses a BW ranging from 10 to 100 HU at an interval of 10 HU and BC = (CThepatic portal vein + CThepatic parenchymal) / 2; Protocol D uses the BP-Map that covers all possible values of BW and BC.

RESULTS

When using CT value of adipose tissue as noise, the calculated SNR and CNR of optimal blending width and blending center were 123.22±41.73 and 9.00±3.52, respectively, by the BP-Map in the protocol D. By employing the CT value of back muscle as noise, the SNR and CNR of the best-blended images were 75.90±14.52 and 6.39±2.37, respectively. The subjective score of protocol D was 4.88±0.12.

CONCLUSIONS

Compared to traditional blending methods, the BP-Map technique can determine the optimal blending parameter and provide the best-blended images with the highest SNR and CNR.

Application of machine learning with multiparametric dual-energy computed tomography of the breast to differentiate between benign and malignant lesions

BACKGROUND

Multiparametric dual-energy computed tomography (mpDECT) is widely used to differentiate various kinds of tumors; however, the data regarding its diagnostic performance with machine learning to diagnose breast tumors is limited. We evaluated univariate analysis and machine learning performance with mpDECT to distinguish between benign and malignant breast lesions.

METHODS

In total, 172 patients with 214 breast lesions (55 benign and 159 malignant) who underwent preoperative dual-phase contrast-enhanced DECT were included in this retrospective study. Twelve quantitative features were extracted for each lesion, including CT attenuation (precontrast, arterial, and venous phases), the arterial-venous phase difference in normalized effective atomic number (nZ_eff), normalized iodine concentration (NIC), and slope of the spectral Hounsfield unit (HU) curve (λ_Hu). Predictive models were developed using univariate analysis and eight machine learning methods [logistic regression, extreme gradient boosting (XGBoost), stochastic gradient descent (SGD), linear discriminant analysis (LDA), adaptive boosting (AdaBoost), random forest (RF), decision tree, and linear support vector machine (SVM)]. Classification performances were assessed based on the area under the receiver operating characteristic curve (AUROC). The best performances of the conventional univariate analysis and machine learning methods were compared using the Delong test.

RESULTS

The univariate analysis showed that the venous phase λ_Hu had the highest AUROC (0.88). Machine learning with mpDECT achieved an excellent and stable diagnostic performance, as shown by the mean classification performances in the training dataset (AUROC, 0.88-0.99) and testing (AUROC, 0.83-0.96) datasets. The performance of the AdaBoost model based on mpDECT was more stable than the other machine learning models and superior to the univariate analysis (AUROC, 0.96 vs. 0.88; P<0.001).

CONCLUSIONS

The performance of the AdaBoost classifier based on mpDECT data achieved the highest mean accuracy compared to the other machine learning models and univariate analysis in differentiating between benign and malignant breast lesions.

Predicting Pathological Invasiveness of Lung Adenocarcinoma Manifesting as GGO-Predominant Nodules: A Combined Prediction Model Generated From DECT

RATIONALE AND OBJECTIVES

To evaluate qualitative and quantitative indicators generated from Dual-energy computed tomography (DECT) for preoperatively differentiating between invasive adenocarcinoma (IAC) and preinvasive or minimally invasive adenocarcinoma (MIA) lesions manifesting as ground-glass opacity-predominant (GGO-predominant) nodules.

MATERIALS AND METHODS

We retrospectively enrolled 143 cases of completely resected GGO-predominant lung adenocarcinoma with DECT examinations between December 2017 and July 2019. Qualitative and quantitative parameters of GGO-predominant nodules were compared after grouping nodules into IAC and preinvasive-MIA groups. A multivariate logistic regression models were used for analyzing these parameters. The diagnostic performance of different parameters was compared by receiver operating characteristic (ROC) curves and Z tests.

RESULTS

This study included 137 patients (58 years ± 11; male: female = 52:91) with 143 GGO-predominant nodules. The proportion of margins, internal dilated/distorted/cut-off bronchi, internal thickened/stiff/distorted vasculature, pleural indentation, and vascular convergence were higher in the IAC group than in the preinvasive-MIA group, as were the maximum diameter (D_max), the diameter of the solid component (D_solid) and the enhanced monochromatic CT value at 40 keV-190 keV (CT_{40 keV-190 keV}) (p range: 0.001-0.019). Logistic regression analyses revealed that margin, D_max, and CT_{60 keV} values were independent predictors of the IAC group. The area under the curve (AUC) for the combination of margin, D_max, and CT_{60 keV} was 0.896 (90.2% sensitivity, 70.7% specificity, 84.6% accuracy), which was significantly higher than that for each two of them (all p < 0.05).

CONCLUSION

The combined prediction model generated from DECT allows for effective preoperative differentiation between IAC and preinvasive-MIA in GGO-predominant lung adenocarcinomas.

Myocardial extracellular volume fraction analysis in doxorubicin-induced beagle models: comparison of dual-energy CT with equilibrium contrast-enhanced single-energy CT

Background

Dual-energy CT (DECT) permits the simultaneous operation of two different kV levels, providing a potential method toward the assessment of diffuse myocardial fibrosis. The purpose of this study was to determine the accuracy of DECT for evaluation of the myocardial extracellular volume (ECV) fraction in comparison with single-energy CT (SECT).

Methods

Myocardial ECV was quantified in fifteen dogs using DECT and dynamic equilibrium SECT before and after doxorubicin administration. Cardiac magnetic resonance imaging (CMRI) was used to assess myocardial function. The histological collagen volume fraction (CVF) was calculated as the gold standard. The Bland-Altman analysis was performed to compare the agreement between DECT-ECV and SECT-ECV. The association among ECV values derived from DECT and SECT, CVF, and left ventricular ejection fraction (LVEF) were determined by correlation analysis. The variations of these values were evaluated using repeated ANOVA.

Results

The DECT- and SECT-ECV were increased with the elongation of modeling time (pre-modeling vs. 16-week models vs. 24-week models: DECT-ECV 24.1%±1.1%, 35.1%±1.3% and 37.6%±1.4%; SECT-ECV 22.9%±0.8%, 33.6%±1.2% and 36.3%±1.0%; n=30 in per-subject analysis, all P<0.05). Both ECV values of DECT and SECT correlated well with the histological CVF results (R=0.935 and 0.952 for the DECT-ECV and SECT-ECV; all P<0.001; n=13). Bland-Altman plots showed no significant differences between DECT- and SECT-ECV.

Conclusions

DECT-ECV correlated well with both SECT-ECV and histology, showing the feasibility of DECT in evaluating doxorubicin-induced diffuse myocardial interstitial fibrosis.

Could both intrinsic and extrinsic iodine be successfully suppressed on virtual non-contrast CT images for detecting thyroid calcification?

PURPOSE

Although virtual non-contrast (VNC) successfully removes iodinated contrast, uncertainty exists regarding the feasibility of VNC to suppress iodine for detecting thyroid calcification. Therefore, we evaluated whether both intrinsic and extrinsic iodine attenuation were suppressed on VNC images.

MATERIAL AND METHODS

We enrolled 128 patients (male: female 17:111; age 48.0 ± 10.4 years) who underwent dual-layer dual-energy CT (DL-DECT) examination before their thyroid cancer surgeries. Two additional sets of VNC (VNCu, VNCc) images were retrospectively generated from their true unenhanced (TUE) and true contrast-enhanced (TCE) series. We compared CT attenuation values measured on the VNCu and VNCc images by drawing identical regions of interest encompassing thyroid parenchyma, then subjectively determined the concordance of calcification.

RESULTS

Although CT attenuation discrepancies between the VNCu and VNCc were significant (2.0 ± 5.7HU, p < 0.001),61.7%, 89.1%, and 100.0% of all measurements were < 5HU, < 10HU, and < 15HU. Based on Bland-Altman analysis, the limits of agreement were - 9.2HU and 13.2HU, whereas the proportional differences were small for VNC images generated from both TUE and TCE images. There was no discordance between two VNC image sets in detecting thyroid calcification.

CONCLUSIONS

VNC technique could be a feasible method to suppress both intrinsic and extrinsically administered iodine for detecting thyroid calcification.

Feasibility study of using virtual non-contrast images derived from dual-energy CT to replace true non-contrast images in patients diagnosed with papillary thyroid carcinoma

OBJECTIVE

To assess the feasibility of using virtual non-contrast (VNC) images derived from dual-energy computed tomography (DECT) to replace true non-contrast (TNC) images of papillary thyroid carcinoma (PTC) patients.

METHODS

Images of 96 PTC patients were retrospectively analyzed. TNC images were acquired under the single-energy mode of DECT after the plain scanning. The arterial and venous phase VNC (VNC-a and VNC-v) images were generated by the post-processing algorithm from the arterial phase and venous phase of contrast-enhanced CT images, respectively. Mean attenuation values, image noise, number and length of calcification were measured. Radiation dose was also calculated. Last, subjective score of image quality was evaluated by a 5-point scale.

RESULTS

Signal-to-noise ratio (SNR) of each tissue in TNC images is significantly higher than that of VNC images (p<0.050). Contrast-to-noise ratio (CNR) of fat, muscle, thyroid nodules and internal carotid artery in TNC images is significantly higher than that of VNC images, while CNR in TNC images is lower for cervical vertebra (p<0.001). Calcification is detected on TNC images of 44 patients, while it is omitted on VNC images of 14 patients (31.8%). The subjective score of TNC images is higher than VNC images (p<0.001). The effective dose reduction is 47.6% by avoiding plain scanning.

CONCLUSIONS

Considering the different attenuation value, SNR, CNR and especially reduced detection rate of calcification, we deem that VNC images cannot be directly used to replace TNC images in PTC patients, despite the reduced radiation dose.

Prognostic Value of Dual-Energy CT-Based Iodine Quantification versus Conventional CT in Acute Pulmonary Embolism: A Propensity-Match Analysis

Objective

The present study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters offer an incremental risk stratification benefit over the CT ventricular diameter ratio in patients with acute pulmonary embolism (PE) by using propensity score analysis.

Materials and Methods

This study was conducted on 480 patients with acute PE who underwent CT pulmonary angiography (CTPA) or DECT pulmonary angiography (DE CT-PA). This propensity-matched study population included 240 patients with acute PE each in the CTPA and DECT groups. Altogether, 260 (54.1%) patients were men, and the mean age was 64.9 years (64.9 ± 13.5 years). The primary endpoint was all-cause death within 30 days. The Cox proportional hazards regression model was used to identify associations between CT parameters and outcomes and to identify potential predictors. Concordance (C) statistics were used to compare the prognoses between the two groups.

Results

In both CTPA and DECT groups, right to left ventricle diameter ratio ≥ 1 was associated with an increased risk of all-cause death within 30 days (hazard ratio: 3.707, p < 0.001 and 5.573, p < 0.001, respectively). However, C-statistics showed no statistically significant difference between the CTPA and DECT groups for predicting death within 30 days (C-statistics: 0.759 vs. 0.819, p = 0.117).

Conclusion

Quantitative measurement of lung perfusion defect volume by DECT had no added benefit over CT ventricular diameter ratio for predicting all-cause death within 30 days.

Dual energy computed tomography evaluation of skeletal traumas

Skeletal traumas are among the most common routine challenges faced by Emergency Radiologists, in particular in case of radiographically occult nondisplaced fractures or in case of soft tissue injuries. With the development of Dual Energy Computed Tomography (DECT) technology, new post-processing applications have gained a useful diagnostic role in many fields of musculoskeletal imaging including acute skeletal trauma imaging. In addition to conventional CT images, DECT allows for the generation of virtual calcium-suppressed images subtracting calcium from unenhanced CT images based on the fact that material attenuation varies at different energy levels. In this way, virtual-non-calcium (VNC) images can precisely characterize traumatic bone marrow edema in both axial and appendicular skeleton, facilitating prompt clinical decision, especially when magnetic resonance method is contraindicated or unavailable. Other DECT emerging applications in the trauma setting include metal artifact reduction and collagen mapping for the evaluation of injuries affecting ligament, tendon, and intervertebral disk. This review focuses on the basic principles of DECT and related post-processing algorithms, highlighting the current advantages and limitations of these new imaging advances in the Emergency Department related to skeletal traumas.

Gout of ankle and foot: DECT versus US for crystal detection

OBJECTIVE

To compare dual-energy computed tomography (DECT) and ultrasound (US) in detecting monosodium urate (MSU) crystals in the ankle and foot in patients with acute gouty arthritis.

METHODS

Bilateral ankle and foot were examined by DECT and US and the differences between the findings were compared.

RESULTS

A total of 50 patients underwent DECT and US examinations. At the patient level, the overall positivity of crystal deposition detected by DECT was higher than that by US (92% vs 68%, P = 0.005). The agreement of detecting crystal deposition between DECT and US was not very strong (К = 0.44, P = 0.003). At different joint/area levels, there were significant differences between the two examinations in the area of the dorsum (36% vs 12%, P = 0.009) and metatarsal bone (34% vs 12%, P = 0.017), but the sensitivity of DECT and US was similar in the first metatarsophalangeal joint (MTP) and ankle areas (P>0.05). Agreement between the two examinations in the ankle and first MTP was very strong (К = 0.86, P < 0.001; К = 0.79, P < 0.001, respectively). However, agreement between the two examinations in other joints/areas was poor.

CONCLUSION

These findings indicated that DECT should be the first choice for acute gouty arthritis in patients with ankle and foot involvement. Key Points • There is little data regarding DECT and US in detecting MSU crystals in the ankle and foot in patients with acute gouty arthritis. • The overall positivity of crystal deposition detected by DECT was higher than that by US, but the sensitivity of DECT and US was similar in the first metatarsophalangeal joint (MTP) and ankle areas. • Agreement between the two examinations in the ankle and first MTP was very strong; however, agreement between the two examinations in other joints/areas was poor.

Diagnostic value of ultrasound versus dual-energy computed tomography in patients with different stages of acute gouty arthritis

OBJECTIVE

Previous studies of the diagnostic accuracy of ultrasound (US) and dual-energy computed tomography (DECT) in patients with gout have reported different results. The aim of this study is to compare the diagnostic value of US and DECT in patients with different stages of acute gouty arthritis.

METHODS

Based on the presence of monosodium urate (MSU) crystals in the synovial fluid, patients (n = 37) were divided into three groups according to gout duration: early stage (within 1 year, n = 15), middle stage (1 to 3 years, n = 12), and late stage (more than 3 years, n = 10). All the affected joints were examined by US and DECT.

RESULTS

In the early-stage group, the sensitivity of US was significantly higher than DECT in identifying MSU deposition (66.7% vs 26.6%, p < 0.05), while in the middle- and late-stage groups, the sensitivity of US and DECT was similar. In the early-stage group, the US results in nine joints were positive (four with double contour sign, four with snowstorm sign, and one with both double contour sign and snowstorm sign), while DECT did not show any urate crystal deposits.

CONCLUSION

These findings indicate that US should be the first choice for acute gouty arthritis, especially in patients with early-stage disease.Key Points• Previous studies have compared DECT with US to evaluate the reliability of each method in diagnosing gout but have reported different results, which may be partly due to different gout duration.• In our study, the sensitivity of US was significantly higher than DECT in identifying MSU deposition in the early-stage group, while in the middle- and late-stage groups, the sensitivity of US and DECT was similar.• US should be the first choice for the diagnosis of acute gouty arthritis, especially in patients with early-stage disease.

Fast kilovoltage (KV)-switching dual-energy computed tomography hydroxyapatite (HAP)-water decomposition technique for identifying bone marrow edema in vertebral compression fractures

Background

Hydroxyapatite (HAP) is the main component of bone mineral. The utility of using HAP-water decomposition technique with fast kilovoltage (KV)-switching dual-energy computed tomography (DECT) to detect abnormal edema in vertebral compression fractures (VCFs) has not been widely reported.

Methods

A total of 31 consecutive patients with 80 VCFs who underwent DECT and magnetic resonance imaging (MRI) of the spine were retrospectively enrolled in our study between October 2018 and January 2019. VCFs in MR examinations served as the standard of reference. Two radiologists blindly and independently evaluated color-coded overlay virtual nonhydroxyapatite (VNHAP) images for the presence of abnormal edema. The inter-reader agreement, specificity, sensitivity, accuracy, and predictive values of VNHAP images for edema detection were calculated. The diagnostic accuracy of two readers was compared using McNemar's test. Two additional radiologists performed a quantitative analysis on VNHAP images, receiver operating characteristic (ROC) curve analysis was conducted, and the threshold was calculated.

Results

MRI depicted 45 edematous and 35 nonedematous VCFs. For visual analysis, the VNHAP technique showed a sensitivity of 93.3%, a specificity of 97.1%, a positive predictive value (PPV) of 97.7%, a negative predictive value (NPV) of 91.9%, and an accuracy of 95.0%. The inter-reader agreement was almost perfect (k=0.90). The diagnostic accuracy of the two readers showed no significant differences in the assessment of VNHAP images (P=1.00). Significant differences in CT numbers between vertebrae with and without bone marrow edema were found by quantitative analysis (P<0.01). The area under the curve (AUC) of the VNHAP images was estimated to be 0.917. The threshold of 1,003.2 mg/cm³ yielded a sensitivity of 88.9% and a specificity of 82.9% for the differentiation of fresh and old VCFs.

Conclusions

Fast KV-switching DECT HAP-water decomposition technique had excellent diagnostic performance for identifying acute and chronic VCFs in visual and quantitative analyses.

Application value of dual-energy computed tomography spectrum curve combined with clinical risk factors in predicting adherent perinephric fat

Background

Adherent perinephric fat (APF) is evaluated preoperatively with the Mayo adhesive probability (MAP) scoring system using conventional single form computed tomography (CT) images. An objective or quantitative indicator for predicting APF is urgently needed for clinical application.

Methods

Data obtained from 150 renal tumor patients with partial nephrectomy (PN) were used in the present study. Patients were divided into two groups based on the surgical results: an APF group (n=100) and a non-APF group (n=50). All patients had renal contrast-enhanced dual-energy CT (DECT) scan, and the data were brought into a post-processing workstation. Monoenergetic plus mode was adopted to analyze the spectrum curve of the region of interest (ROI). Logistic stepwise relapse investigation was utilized to analyze the related risk factors. The maximum Youden index was taken as the cut-off value. The sensitivity, specificity, accuracy, and 95% CI of the model were calculated.

Results

APF is related to patients' clinical characteristics of age, gender, BMI, smoking, tumor diameter, exophytic, and benign or malignant nature of the renal masses (P<0.05). The shape of the curve of ROI₁ in the APF group was different from that of the ROI₄ in the non-APF group, and the curve slope of K1 (-0.21±0.47) was different from that of K4 (-1.30±0.14) (P<0.001). Statistical analysis showed that the slope K was solely retained in the model index. The best cut-off point for the K value was -0.95. The AUC of the cut-off point was 0.97 (95% CI: 0.96-0.99).

Conclusions

The DECT spectrum curve performed well in predicting APF, and the curve slope K can be used as an objective quantitative indicator.

Predictive factors for treatment response using dual-energy computed tomography in patients with advanced lung adenocarcinoma

PURPOSE

This study aimed to investigate whether the quantitative parameters of dual-energy computed tomography (DECT) can predict the effects of chemotherapy in advanced adenocarcinoma based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines.

MATERIALS AND METHODS

A total of 90 patients (59 males, 31 females, age 61.4 ± 12.3 (23-85)) with unresectable lung adenocarcinoma (TNM stage IIIB or IV) who underwent DECT before chemotherapy were prospectively included in this study. By comparing baseline studies with the best response achieved during 1 st line chemotherapy, patients were divided into two groups according to RECIST (version 1.1) guidelines as follows; responders (CR or PR) and non-responders (SD or PD). Quantitative measurements were performed on baseline DECT, and a logistic regression model was used to evaluate predictive factors for a response to chemotherapy.

RESULTS

Among 90 patients, 38 were categorized as responders, while 52 patients were non-responders. The mean iodine concentration measurements were significantly higher in responders compared with non-responders (1.81 ± 0.51 vs 1.33 ± 0.76 mg/ml, p < 0.001). On multivariate analysis, EGFR mutation (odds ratio (OR): 3.116, 95% confidential interval (CI):1.182-8.213, p = .019) and iodine concentration (OR: 1.112, 95% CI:1.034-1.196, p = .006) were found to be significant for predicting a treatment response.

CONCLUSIONS

Dual-energy CT using a quantitative analytic method based on iodine concentration measurements can be used to predict the effects of chemotherapy in patients with advanced adenocarcinoma.

Monosodium urate crystal deposition associated with the progress of radiographic grade at the sacroiliac joint in axial SpA: a dual-energy CT study

Background

Previous studies have revealed that ankylosing spondylitis (AS), as the progenitor of axial spondyloarthritis (AxSpA), has been characterized by the insidiously progressive nature of sacroiliitis and spondylitis. Dual-energy computed tomography (DECT) has recently been used to analyse the deposition of monosodium urate (MSU) crystals with higher sensitivity and specificity. However, it remains unclear whether the existence of the MSU crystal deposition detected by DECT at the sacroiliac joint in patients with AxSpA also is associated with the existing structural damage. Here, we performed this study to show the DECT MSU crystal deposits in AxSpA patients without coexisting gout and to ascertain the relationship between the MSU crystal deposition and the structural joint damage of sacroiliac joints.

Methods

One hundred and eighty-six AxSpA patients without coexisting gout were recruited. The plain radiographs of the sacroiliac joint were obtained, along with the DECT scans at the pelvis and the clinical variables. All statistics based on the left or right sacroiliac joint damage grading (0–4) were calculated independently. Bivariate analysis and ordinal logistic regression was performed between the clinical features and radiographic grades at the sacroiliac joint.

Results

At the pelvis, large quantities of MSU crystal deposition were found in patients with AxSpA. The average MSU crystal volume at the left sacroiliac joint, the right sacroiliac joint, and the pelvis were 0.902 ± 1.345, 1.074 ± 1.878, and 5.272 ± 9.044 cm³, values which were correlated with serum uric acid concentrations (r = 0.727, 0.740, 0.896; p < 0.001). In bivariate analysis, wide clinical variables were associated with the changes in sacroiliac joint damage. Further, the AxSpA duration, BASFI score, and the volume of MSU crystal at both sides of sacroiliac joint were associated with the progress of radiographic grade at the sacroiliac joints in the ordinal logistic models (left AOR = 1.180, 3.800, 1.920; right AOR = 1.190, 3.034, 1.418; p < 0.01).

Conclusions

Large quantities of MSU crystal deposition detected by DECT were found at the pelvis in AxSpA patients without coexisting gout. In addition to AxSpA duration and BASFI score, the MSU crystal deposition at the sacroiliac joint is associated with the progress of radiographic grade at sacroiliac joints in those patients.

Quantification of lung perfusion blood volume (lung PBV) by dual-energy CT in patients with chronic thromboembolic pulmonary hypertension (CTEPH) before and after balloon pulmonary angioplasty (BPA): Preliminary results

OBJECTIVES

Balloon pulmonary angioplasty (BPA) is a treatment option for patients with chronic thromboembolic pulmonary hypertension (CTEPH). Its effect on pulmonary perfusion has not been quantified; we examined the clinical significance of pulmonary blood volume (PBV) using dual-energy computed tomography (DECT) in patients with CTEPH undergoing BPA.

METHODS

In this retrospective study of 16 BPAs in eight female patients with CTEPH, we evaluated both-lung (n=16), right- or left-lung (n=32), and three right- or left-segment (upper, middle, and lower) (n=96) PBVs before and after BPA, using DECT. We evaluated the relationships between improvement in lung PBV and pulmonary artery (PA) pressure (PAP), cardiac index (CI), pulmonary vascular resistance (PVR), and 6-min walking distance. We measured PA enhancement (PAenh) on DECT images and calculated lung PBV/PAenh to adjust timing.

RESULTS

Pre- and post-BPA 6-segment lung PBV/PAenh were 0.067±0.021 and 0.077±0.019, respectively, in the treated segment (p<0.0001). There were significant positive correlations between pre- to post-BPA improvements in both-lung PBV/PAenh and PAP (R=0.69, p=0.005), PVR (R=0.56, p=0.03), and 6-min walking distance (R=0.67, p=0.01).

CONCLUSIONS

Improved PBV after BPA, reflecting increased lung perfusion, was positively correlated with PAP, PVR, and 6-min walking distance. Lung PBV may be an indicator of BPA treatment effect.

Dual-energy CT-based iodine quantification for differentiating pulmonary artery sarcoma from pulmonary thromboembolism: a pilot study

OBJECTIVES

The purpose of this study was to determine whether dual-energy computed tomography (DECT) angiography could differentiate pulmonary thromboembolism (PTE) from pulmonary artery sarcoma (PAS).

METHODS

We prospectively enrolled 19 patients that had a filling defect in the main pulmonary artery on DECT. Six patients who had PAS and underwent DECT were retrospectively enrolled for comparison. Pathological results or follow-up CT after anticoagulation therapy were used to make the final diagnosis. Two investigators measured the following parameters at the filling defect in the main pulmonary artery: CT attenuation density [Hounsfield units (HU)], iodine-related HU (IHU) and iodine concentration (IC, mg/ml).

RESULTS

From a total of 25 patients (M:F = 10:15; mean age, 65 years old), 19 were categorised into the PTE group and six were categorised into the PAS group. The mean HU values were not significantly different between the PTE and PAS groups (45.5 ± 15.9 vs 47.1 ± 9.2 HU; P = 0.776). However, the mean IHU and IC values of the lesions were significantly different between the PTE and PAS groups (10.6 ± 7.2 vs 27.9 ± 9.1 HU; P = 0.004, and 0.61 ± 0.39 vs 1.49 ± 0.57; P = 0.001).

CONCLUSIONS

DECT angiography using a quantitative analytic methodology can be used to differentiate PTE and PAS.

KEY POINTS

• DECT can be useful for differentiation of PAS and PTE. • With quantitative analysis, DECT offers tissue characterisation by detecting lesion parameter increases. • The patients without predisposing factors for PTE can be candidates for DECT.

Detection of different kidney stone types: an ex vivo comparison of ultrashort echo time MRI to reference standard CT

BACKGROUND AND PURPOSE

With the development of ultrashort echo time (UTE) sequences, it may now be possible to detect kidney stones by using magnetic resonance imaging (MRI). In this study, kidney stones of varying composition and sizes were imaged using both UTE MRI as well as the reference standard of computed tomography (CT), with different surrounding materials and scan setups.

METHODS

One hundred and fourteen kidney stones were inserted into agarose and urine phantoms and imaged both on a dual-energy CT (DECT) scanner using a standard renal stone imaging protocol and on an MRI scanner using the UTE sequence with both head and body surface coils. A subset of the stones representing all composition types and sizes was then inserted into the collecting system of porcine kidneys and imaged in vitro with both CT and MRI.

RESULTS

All of the stones were visible on both CT and MRI imaging. DECT was capable of differentiating between uric acid and nonuric acid stones. In MRI imaging, the choice of coil and large field of view (FOV) did not affect stone detection or image quality. The MRI images showed good visualization of the stones' shapes, and the stones' dimensions measured from MRI were in good agreement with the actual values (R(2)=0.886, 0.895, and 0.81 in the agarose phantom, urine phantom, and pig kidneys, respectively). The measured T2 relaxation times ranged from 4.2 to 7.5ms, but did not show significant differences among different stone composition types.

CONCLUSIONS

UTE MRI compared favorably with the reference standard CT for imaging stones of different composition types and sizes using body surface coil and large FOV, which suggests potential usefulness of UTE MRI in imaging kidney stones in vivo.