Early reduction in spectral dual-layer detector CT parameters as favorable imaging biomarkers in patients with metastatic renal cell carcinoma

Performance of novel multiparametric second-generation dual-layer spectral detector CT in gouty arthritis

OBJECTIVES

This study aimed to compare the performance of different dual-energy computed tomography (DECT) technologies in detecting monosodium urate (MSU) crystals and evaluate the potential clinical value of novel second-generation dual-layer spectral detector CT (dlDECT) in gouty arthritis.

METHODS

Using data collected from a tertiary hospital, we examined the diagnostic accuracy of different DECT technologies for the diagnosis of MSU. We used two standards: (1) demonstration of MSU crystals in synovial fluid (gold) and (2) 2015 ACR/EULAR gout classification criteria (silver). Furthermore, six novel spectral parameters derived from dlDECT were quantitatively calculated and analyzed for MSU diagnostic efficiency.

RESULTS

Of the 243 patients with 387 joints, 68 (27.98%) had synovial fluid analysis. Compared with the gold standard, MSU diagnostic accuracy statistics for dlDECT, dual-source DECT (dsDECT) and rapid kilovolt peak switching DECT (rsDECT) were as follows: area under the curve (AUC): 0.85, 0.80 and 0.75, respectively. Findings were replicated compared with the silver standard. Multiparametric analysis in dlDECT demonstrated the highest MSU detection rate (92.86%), significantly higher than rsDECT (42.08%) and dsDECT (85.80%). Among novel parameters in dlDECT, Calcium-suppressed index 25 (CaSupp-I 25) exhibited the best performance in distinguishing materials (MSU, muscle, and bone), with an AUC of 0.992. The differentiation was also aided by histograms, scatter plots, and attenuation curves.

CONCLUSION

The novel dlDECT is likely not inferior to other DECT technologies in MSU detection, especially its spectral parameter CaSupp-I 25. Multiparameter analysis showed the potential value for detecting MSU crystals in gouty arthritis, providing valuable clinical insights for gout diagnosis.

KEY POINTS

Question The performance of different DECT technologies in detecting monosodium urate (MSU), and the value of dual-layer spectral detector CT (dlDECT) in gouty arthritis remains unclear. Findings The dlDECT was likely not inferior to other DECT technologies in MSU detection, and its multiparametric analysis provided valuable information for MSU diagnosis. Clinical relevance Novel dlDECT may improve the accurate detection of MSU crystals in gouty arthritis compared to other DECT technologies, providing valuable clinical insights and potentially improving patient outcomes for more precise gout diagnosis.

Diagnostic value of dual-layer spectral detector CT parameters for differentiating high- from low-grade bladder cancer

OBJECTIVES

This study aimed to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in distinguishing between low- and high-grade bladder cancer (BCa).

METHODS

This single-center retrospective study included pathologically confirmed BCa patients who underwent preoperative contrast-enhanced DLCT. Patients were divided into low- and high-grade groups based on pathology. We measured and calculated the following spectral CT parameters: iodine density (ID), normalized ID (NID), arterial enhancement fraction (AEF), extracellular volume (ECV) fraction, virtual non-contrast (VNC), slope of the attenuation curve, and Z effective (Zeff). Univariate and multivariable logistic regression analyses were used to determine the best predictive factors in differentiating between low- and high-grade BCa. We used receiver operating characteristic curve analysis to assess diagnostic performance and decision curve analysis to determine the net benefit.

RESULTS

The study included 64 patients (mean age, 64 ± 11.0 years; 46 men), of whom 42 had high-grade BCa and 22 had low-grade BCa. Univariate analysis revealed that differences in ID and NID in the corticomedullary phase, AEF, ECV, VNC, and Zeff images were statistically significant (p = 0.001-0.048). Multivariable analysis found that AEF was the best predictor of high-grade tumors (p = 0.006). With AEF higher in high-grade BCa, AEF results were as follows: area under the curve (AUC), 0.924 (95% confidence interval, 0.861-0.988); sensitivity, 95.5%; specificity, 81.0%; and accuracy, 85.9%. The cutoff valve of AEF for predicting high-grade BCa was 67.7%.

CONCLUSION

Using DLCT AEF could help distinguish high-grade from low-grade BCa.

CRITICAL RELEVANCE STATEMENT

This research demonstrates that the arterial enhancement fraction (AEF), a parameter derived from dual-layer spectral detector CT (DLCT), effectively distinguishes between high- and low-grade bladder cancer, thereby aiding in the selection of appropriate clinical treatment strategies.

KEY POINTS

This study investigated the value of dual-layer spectral detector CT in the assessment of bladder cancer (BCa) histological grade. The spectral parameter arterial enhancement fraction could help determine BCa grade. Our results can help clinicians formulate initial treatment strategies and improve prognostications.

What to Expect (and What Not) from Dual-Energy CT Imaging Now and in the Future?

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.

Nomogram combining pre-operative clinical characteristics and spectral CT parameters for predicting the WHO/ISUP pathological grading in clear cell renal cell carcinoma

PURPOSE

To develop a novel clinical-spectral-computed tomography (CT) nomogram incorporating clinical characteristics and spectral CT parameters for the preoperative prediction of the WHO/ISUP pathological grade in clear cell renal cell carcinoma (ccRCC).

METHODS

Seventy-three ccRCC patients who underwent spectral CT were included in this retrospective analysis from December 2020 to June 2023. The subjects were pathologically divided into low- and high-grade groups (WHO/ISUP 1/2, n = 52 and WHO/ISUP 3/4, n = 21, respectively). Information on clinical characteristics, conventional CT imaging features, and spectral CT parameters was collected. Multivariate logistic regression analyses were conducted to create a nomogram combing clinical data and image data for preoperatively predicting the pathological grade of ccRCC, and the area under the curve (AUC) was utilized to assess the predictive performance of the model.

RESULTS

Multivariate logistic regression analyses revealed that age, systemic immune-inflammation index (SII), and the slope of the spectrum curve in the cortex phase (CP-K) were independent predictors for predicting high-grade ccRCC. The clinical-spectral-CT model exhibited high evaluation efficacy, with an AUC of 0.933 (95% confidence interval [CI]: 0.878-0.998; sensitivity: 0.810; specificity: 0.923). The calibration curve revealed that the predicted probability of the clinical-spectral-CT nomogram could better fit the actual probability, with high calibration. The Hosmer-Lemeshow test showed that the model had a good fitness (χ2 = 5.574, p = 0.695).

CONCLUSION

The clinical-spectral-CT nomogram has the potential to predict WHO/ISUP grading of ccRCC preoperatively.

Evaluation of microcirculation in asymptomatic cerebral infarction with multi-parameter imaging of spectral CT

OBJECTIVE

To investigate the role of spectral CT multiparametric imaging in the evaluation of cerebral microcirculatory perfusion.

METHODS

The imaging data of 145 patients with asymptomatic cerebral infarction confirmed by MR were retrospectively analyzed, and all cases underwent head CTA and cranial CT perfusion imaging (CTP) on double-layer detector spectral CT. Single energy level images (MonoE45 keV), iodine density maps, and effective atomic number maps were reconstructed based on spectral CTA data, and CT values, iodine density values, and effective atomic number values were measured in the infarcted area, healthy control area, centrum semiovale and posterior limb of the internal capsule, respectively; perfusion values, such as cerebral blood volume (CBV) values, cerebral blood flow (CBF) values, time to peak (TTP) values, and mean passage time, were measured in the above-mentioned areas on CTP images. (TTP) values, and mean time to passage (MTT) values. CT values, iodine density values, effective atomic number values, and perfused CBV, CBF, TTP, and MTT values were compared between the infarcted area and the healthy side, the center of the hemianopia, and the posterior limb of the internal capsule. The role of spectral CT parameters and perfusion parameters in the evaluation of asymptomatic cerebral infarction was analyzed.

RESULTS

CT values, iodine density values, and effective atomic number values were statistically different between the infarcted area and the healthy side; CT values, iodine density values, and effective atomic number values were not statistically different between the infarcted side and the healthy side of the hemispheric centrum and the posterior limb of the internal capsule; CBV and CBF were statistically different between the infarcted side and the healthy side, and MTT and TTP were not statistically different. There were statistically significant differences in TTP between the infarcted area and the healthy side of the hemiaxial center, and no statistically significant differences in CBV, CBF, and MTT. There were no statistical differences in CBV, CBF, TTP, and MTT in the inner capsule area. ROC curve analysis of spectral CT-related parameters and CT perfusion parameters for the diagnosis of asymptomatic cerebral infarction: area under the curve of MonoE 45Kv 0.71, area under the curve of iodine density values 0.76, area under the curve of effective atomic number values 0.74; area under the curve of CBV value 0.64, area under the curve of CBF value 0.61, area under the curve of MTT value 0.50, The area under the TTP curve was 0.52. The area under the ROC curve of the multivariate logistic regression model based on spectral parameters is 0.76, which is higher than that of the logistic regression model with perfusion parameters (P < 0.05).

CONCLUSION

Spectral CT can better demonstrate small intracranial ischemic lesions, and iodine density values have a better evaluation of microcirculation in asymptomatic cerebral infarcts.

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Early evaluation of liver metastasis using spectral CT to predict outcome in patients with colorectal cancer treated with FOLFOXIRI and bevacizumab

PURPOSE

Early evaluation of the efficacy of first-line chemotherapy combined with bevacizumab in patients with colorectal cancer liver metastasis (CRLM) remains challenging. This study used 2-month post-chemotherapy spectral computed tomography (CT) to predict the overall survival (OS) and response of CRLM patients with bevacizumab-containing therapy.

METHOD

This retrospective analysis was performed in 104 patients with pathologically confirmed CRLM between April 2017 and October 2021. Patients were treated with 5-fluorouracil, leucovorin, oxaliplatin or irinotecan with bevacizumab. Portal venous phase spectral CT was performed on the target liver lesion within 2 months of commencing chemotherapy to demonstrate the iodine concentration (IoD) of the target liver lesion. The patients were classified as responders (R +) or non-responders (R -) according to the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 at 6 months. Multivariate analysis was performed to determine the relationships of the spectral CT parameters, tumor markers, morphology of target lesions with OS and response. The differences in portal venous phase spectral CT parameters between the R + and R - groups were analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of spectral CT parameters.

RESULTS

Of the 104 patients (mean age ± standard deviation: 57.73 years ± 12.56; 60 men) evaluated, 28 (26.9%) were classified as R + . Cox multivariate analysis identified the iodine concentration (hazard ratio [HR]: 1.238; 95% confidence interval [95% CI]: 1.089-1.408; P < 0.001), baseline tumor longest diameter (BLD) (HR: 1.022; 95% CI: 1.005-1.038, P = 0.010), higher baseline CEA (HR: 1.670; 95% CI: 1.016-2.745, P = 0.043), K-RAS mutation (HR: 2.027; 95% CI: 1.192-3.449; P = 0.009), and metachronous liver metastasis (HR: 1.877; 95% CI: 1.179-2.988; P = 0.008) as independent risk factors for patient OS. Logistic multivariate analysis identified the IoD (Odds Ratio [OR]: 2.243; 95% CI: 1.405-4.098; P = 0.002) and clinical N stage of the primary tumor (OR: 4.998; 95% CI: 1.210-25.345; P = 0.035) as independent predictor of R + . Using IoD cutoff values of 4.75 (100ug/cm³) the area under the ROC curve was 0.916, sensitivity and specificity were 80.3% and 96.4%, respectively.

CONCLUSIONS

Spectral CT IoD can predict the OS and response of patients with CRLM after 2 months of treatment with bevacizumab-containing therapy.

Added value of spectral parameters in diagnosing metastatic lymph nodes of pT1-2 rectal cancer

PURPOSE

To investigate the added value of spectral parameters derived from dual-layer spectral detector CT (SDCT) in diagnosing metastatic lymph nodes (LNs) of pT1-2 (stage 1-2 determined by pathology) rectal cancer.

METHODS

A total of 80 LNs (57 non-metastatic LNs and 23 metastatic LNs) from 42 patients with pT1-T2 rectal cancer were retrospectively analyzed. The short-axis diameter of LNs was measured, then its border and enhancement homogeneity were evaluated. All spectral parameters, including iodine concentration (IC), effective atomic number (Z_eff), normalized IC (nIC), normalized Z_eff (nZ_eff), and slope of the attenuation curve (λ), were measured or calculated. The chi-square test, Fisher's exact test, independent-samples t-test, or Mann-Whitney U test was used to compare the differences of each parameter between the non-metastatic group and the metastatic group. Multivariable logistic regression analyses were used to determine the independent factors for predicting LN metastasis. Diagnostic performances were assessed by ROC curve analysis and compared with the DeLong test.

RESULTS

The short-axis diameter, border, enhancement homogeneity, and each spectral parameter of LNs showed significant differences between the two groups (P < 0.05). The nZ_eff and short-axis diameter were independent predictors of metastatic LNs (P < 0.05), with areas under the curve (AUC) of 0.870 and 0.772, sensitivity of 82.5% and 73.9%, and specificity of 82.6% and 78.9%. After combining nZ_eff and the short-axis diameter, the AUC (0.966) was the highest with sensitivity of 100% and specificity of 87.7%.

CONCLUSION

The spectral parameters derived from SDCT might help us to improve the diagnostic accuracy of metastatic LNs in patients with pT1-2 rectal cancer, the highest diagnostic performance can be achieved after combining nZ_eff with the short-axis diameter of LNs.