Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients

Dual-Source Dual-Energy Imaging Using Photon-Counting Detector CT for Bone Edema Detection: Leveraging Tin Prefiltration for Improved Spectral Performance

OBJECTIVES

The aims of the study were to evaluate the spectral performance of an investigational dual-source (DS) scan mode using a tin (Sn) filter on the B-subsystem of a clinical photon-counting detector (PCD) CT system and to demonstrate improved material decomposition performance using clinical examples of bone imaging tasks.

MATERIALS AND METHODS

Calcium inserts (Ca 100, 200 and 300 mg/cc) were placed in water phantoms (30-, 40-, and 50-cm lateral diameter) and scanned on clinical PCD-CT (NAEOTOM Alpha, Siemens) using DS spectral scan mode (QuantumPeak). Two tube potential configurations (70/Sn150 kV and 90/Sn150 kV) were used to scan the phantoms (11 mGy to 41 mGy volume CT dose index). The phantoms were also scanned using the single-source (SS) PCD-CT scan mode at 120 kV and 140 kV tube potential, and on a DS energy-integrating detector (EID) CT (SOMATOM Force, Siemens) for quantitative comparison. CT images (from SS-PCD-CT, DS-PCD-CT, and DS-EID-CT) were reconstructed using a quantitative kernel (Qr40) at a 2-mm section thickness using iterative reconstruction strength 1. Spectral separation was quantified using the dual-energy ratio (DER) of Ca inserts and using mean absolute percent error (MAPE) of Ca mass density obtained from Ca/water material decomposition. To demonstrate clinical feasibility, 4 patients were scanned using DS-PCD-CT under an institutional review board-approved study. Bone edema maps were reconstructed from DS-PCD-CT and compared with the corresponding clinical imaging exam of the same patients (MRI or DS-EID-CT).

RESULTS

DS-PCD-CT at 70/Sn150 kV for Ca 100 mg/cc showed the highest mean DER (2.49 and 2.56 at 30 and 40 cm, respectively) among all scan configurations. For the 50-cm phantom at Ca 100 mg/cc, DS-PCD-CT at 90/Sn150 kV showed highest mean DER (1.88), followed by DS-EID-CT at 90/Sn 150 kV (1.87) and SS-PCD-CT at 140 kV (1.78). The MAPE values for DS-PCD-CT were consistently lower across all phantom sizes (MAPE max. of 1.44%) compared to SS-PCD-CT (MAPE max. 3.97%) and DS-EID-CT (MAPE max. 3.68%). Qualitatively, patient images illustrated bone edema depiction on DS-PCD-CT comparable to clinical MR images, and more precise edema depiction compared to DS-EID-CT images at the site of fractures and intramedullary lesions, and with fewer artifacts.

CONCLUSIONS

DS-PCD-CT showed superior spectral performance for calcium imaging tasks compared to SS-PCD-CT and DS-EID-CT.

Contrast-enhanced photon-counting detector CT for discriminating local recurrence from postoperative changes after resection of pancreatic ductal adenocarcinoma

BACKGROUND

We evaluated the diagnostic capability of photon-counting detector computed tomography (PCD-CT) spectral variables in late arterial phase (LAP) and portal venous phase (PVP) to discriminate between local tumor recurrence (LTR) and postoperative changes (POC) after pancreatic ductal adenocarcinoma (PDAC) resection.

METHODS

Seventy-three consecutive PCD-CT scans in 73 patients with postoperative soft-tissue lesions (PSLs) were included, 42 with POC and 31 with LTR. Regions of interest were drawn in each PSL, and spectral variables were calculated: iodine concentration (IC), normalized IC (NIC), fat fraction, attenuation at 40, 70, and 90 keV, and slope of the spectral curve between 40-90 keV. Multivariable binary logistic regression models were constructed. Diagnostic performance was assessed for LAP and PVP using receiver operating characteristic analysis.

RESULTS

In LAP, all variables except fat fraction showed significant differences between LTR and POC (p ≤ 0.025). In PVP, all variables except NIC and fat fraction demonstrated significant differences between LTR and POC (p ≤ 0.005). Logistic regression analysis included NIC and 70 keV in the LAP-based model and IC and 90 keV in the PVP-based model. Both models achieved a higher area under the curve (AUC) than individual spectral variables in each phase. The LAP-based model achieved an AUC of 0.919 with 94% sensitivity, 84% specificity, and 87% accuracy, while the PVP-based model reached 0.820, 71%, 88%, and 81%, respectively.

CONCLUSION

Spectral variables from PCD-CT help distinguish between LTR and POC in LAP and PVP post-PDAC resection. Multivariable logistic regression improves diagnostic performance, especially in LAP.

RELEVANCE STATEMENT

Measuring normalized iodine concentration and attenuation at 70 keV in late arterial phase, or iodine concentration and attenuation at 90 keV in portal venous phase, and incorporating these values into a logistic regression model can help differentiate between local tumor recurrence and postoperative changes after pancreatic ductal adenocarcinoma resection.

KEY POINTS

Distinguishing recurrence from postoperative changes on CT after pancreatic ductal adenocarcinoma resection is challenging. PCD-CT spectral variable values differed significantly between local tumor recurrence (LTR) and postoperative changes (POC). Logistic regression of spectral variables can help distinguish LTR from POC. The late arterial phase-based model reached an AUC of 0.919 with 94% sensitivity and 84% specificity.

Performance of iodine quantification through high-pitch dual-source photon-counting CT: a phantom study

PURPOSE

To investigate the feasibility and accuracy of iodine quantification using PCD-CT in standard-pitch and high-pitch scanning at different scan parameters in a phantom model.

MATERIALS AND METHODS

Four inserts with known iodine concentrations (2, 5, 10, and 15 mg/mL) were placed in the removable CT phantom and scanned using high-pitch (3.2) and standard-pitch (0.8) modes on PCD-CT. Two tube voltages (120 and 140 kVp) and four radiation doses (1, 3, 5, and 10 mGy) were alternated. Each scan setting was repeated three times. Mean iodine concentration for each insert across three consecutive slices was recorded. Percentage absolute bias (PAB) was assessed for iodine quantification.

RESULTS

A total of 96 acquisitions were conducted. In small phantom, the average for PAB was 2.96% (range: 1.75% ~ 4.56%) and 1.67% (range: 1.00% ~ 3.42%) for high-pitch and standard-pitch acquisitions, respectively. In large phantom, it was 3.72% (range: 1.75% ~ 5.97%) and 2.94% (range: 1.75% ~ 4.70%). Linear regression analysis revealed that only phantom size significantly influenced (P < 0.001) the accuracy of iodine quantification.

CONCLUSION

The high-pitch scan mode in PCD-CT can be used to quantify iodine density with similar accuracy compared with standard pitch.

Performance evaluation of single- and dual-contrast spectral imaging on a photon-counting-detector CT

BACKGROUND

The first commercially available photon-counting-detector CT (PCD-CT) has been introduced for clinical use. However, its spectral performance on single- and dual-contrast imaging tasks has not been comprehensively assessed.

PURPOSE

To evaluate the spectral imaging performance of a clinical PCD-CT system for single-contrast material [iodine (I) or gadolinium (Gd)] and dual-contrast materials (I and Gd) in comparison with a dual-source dual-energy CT (DS-DECT).

METHODS

Iodine (5, 10, and 15 mg/mL) and gadolinium (3.3, 6.6, and 9.9 mg/mL) samples, and their mixtures (I/Gd: 5/3.3 and 10/6.6 mg/mL) were prepared and placed in two torso-shaped water phantoms (lateral dimensions: 30 and 40 cm). These phantoms were scanned on a PCD-CT (NAEOTOM Alpha, Siemens) at 90, 120, and 140 kV. The same phantoms were scanned on a DS-DECT (SOMATOM Force, Siemens) with 70/Sn150, 80/Sn150, 90/Sn150, and 100/Sn150 kV. The radiation dose levels were matched [volume CT dose index (CTDIvol): 10 mGy for the 30 cm phantom and 20 mGy for the 40 cm phantom] across all tube voltage settings and between scanners. Two-material decomposition (I/water or Gd/water) was performed on iodine or gadolinium samples, and three-material decomposition (I/Gd/water) on both individual samples and mixtures. On each decomposed image, mean mass concentration (± standard deviation) was measured in circular region-of-interests placed on the contrast samples. Root-mean-square-error (RMSE) values of iodine and gadolinium concentrations were reported based on the measurements across all contrast samples and repeated on 10 consecutive slices.

RESULTS

For all material decomposition tasks on the DS-DECT, the kV pairs with greater spectral separation (70/Sn150 kV and 80/Sn150 kV) yielded lower RMSE values than other DS-DECT and PCD-CT alternatives. Specifically, for the optimal 70/Sn150 kV, RMSE values were 1.2 ± 0.1 mg/mL (I) for I/water material decomposition, 1.0 ± 0.1 mg/mL (Gd) for Gd/water material decomposition, and 4.5 ± 0.2 mg/mL (I) and 3.7 ± 0.2 mg/mL (Gd), respectively, for I/Gd/water material decomposition. On the PCD-CT, the optimal tube voltages were 120 or 140 kV for I/water decomposition with RMSE values of 2.0 ± 0.1 mg/mL (I). For Gd/water decomposition on PCD-CT, the optimal tube voltage was 140 kV with gadolinium RMSE values of 1.5 ± 0.1 mg/mL (Gd), with the 90 kV setting on PCD-CT generating higher RMSE values for gadolinium concentration compared to all DS-DECT and PCD-CT alternatives. For three material decomposition, both imaging modalities demonstrated substantially higher RMSE values for iodine and gadolinium, with 90 kV being the optimal tube potential for Gd/I quantitation on PCD-CT [5.4 ± 0.3 mg/mL (I) and 3.9 ± 0.2 mg/mL (Gd)], and DS-DECT at 100/Sn150 kV having larger RMSE values for both materials compared to the alternatives for either modality.

CONCLUSION

Optimal tube voltage for material decomposition on the clinical PCD-CT is task-dependent but inferior to DS-DECT using 70/Sn150 kV or 80/Sn150 kV in two-material decomposition for single-contrast imaging (iodine/water or gadolinium/water). Three material decomposition (iodine/gadolinium/water) in dual-contrast imaging yields substantially higher RMSE for both imaging platforms.

Photon Counting Computed Tomography in Rectal Cancer: Associations Between Iodine Concentration, Histopathology and Treatment Response: A Pilot Study

RATIONALE AND OBJECTIVES

Common computed tomography (CT) investigation plays a limited role in characterizing and assessing the response of rectal cancer (RC) to neoadjuvant radiochemotherapy (NARC). Photon counting computed tomography (PCCT) improves the imaging quality and can provide multiparametric spectral image information including iodine concentration (IC). Our purpose was to analyze associations between IC and histopathology in RC and to evaluate the role of IC in response prediction to NARC.

MATERIALS AND METHODS

Overall, 41 patients were included into the study, 14 women and 27 men, mean age, 65.5 years. PCCT in a portal venous phase of the abdomen was performed. In every case, a polygonal region of interest (ROI) was manually drawn on iodine maps. Normalized IC (NIC) was also calculated. Tumor stage, grade, lymphovascular invasion, circumferential resection margin, and tumor markers were analyzed. Tumor regression grade (absence/presence of tumor cells) after NARC was analyzed. NIC values in groups were compared to Mann-Whitney-U tests. Sensitivity, specificity, and area under the curve values were calculated. Intraclass correlation coefficient (ICC) was calculated.

RESULTS

ICC was 0.93, 95%CI= (0.88; 0.96). Tumors with lymphovascular invasion showed higher NIC values in comparison to those without (p = 0.04). Tumors with response grade 2-4 showed higher pretreatment NIC values in comparison to lesions with response grade 0-1 (p = 0.01). A NIC value of 0.36 and higher can predict response grade 2-4 (sensitivity, 73.9%; specificity, 91.7%; area under the curve, 0.85).

CONCLUSION

NIC values showed an excellent interreader agreement in RC. NIC can predict treatment response to NARC.

Microwave-assisted Facile Synthesized Carbon Dots as "on-off-on" Fluorescence Probes for Mercury and Iodine Ions in Bio-samples and Cell Imaging

A kind of nitrogen and sulfur co-doped CDs (N, S-CDs) was facilely synthesized using thiourea and citric acid as precursors, which established an "on-off-on" fluorescence probe to sequential detecting mercury and iodine ions inside water and biology samples. Under 360 nm excitation, CDs emit blue fluorescence with an optimal emission peak of 425 nm (on). The fluorescence of CDs experiences a significant quenching effect upon interaction with Hg2+ ions due to the electron transfer between CDs and Hg2+. This quenching effect is subsequently recovered upon the addition of I- owing to the formation of complexes between Hg2+ and I-. The probe exhibits high selectivity and sensitivity toward Hg2+ and I- with broad linearity in the range of 5-50 μM and 15-60 μM, respectively, and a low detection limit of 14.336 nM and 38.213 nM, respectively. The constructed fluorescence probe N, S-CDs has been successfully applied to the detection of Hg2+ and I- in water and biological samples with great recoveries. More importantly, the bioimaging study demonstrated that N, S-CDs are suitable for live monitoring in biological imaging scenarios of Hg2+ and I- in living cells.

Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications-Technical Background and Post-Processing Techniques

The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine. PCCT is a recent technology that enables a scanner to quantify the energy of each photon gathered by the detector. This method gives the possibility to decrease the radiation dose and increase the spatial and temporal resolutions of scans. Both of these techniques have found a wide range of applications in radiology, including vascular studies. In this narrative review, the authors present the principles of DECT and PCCT, outline their advantages and drawbacks, and briefly discuss the application of these methods in vascular radiology.

Iodine quantification of renal lesions: Preliminary results using spectral-based material extraction on photon-counting CT

Objectives

To assess the range of quantitative iodine values in renal cysts (RC) (with a few renal neoplasms [RNs] as a comparison) to develop an expected range of values for RC that can be used in future studies for their differentiation.

Material and Methods

Consecutive patients (n = 140) with renal lesions who had undergone abdominal examination on a clinical photon-counting computed tomography (PCCT) were retrospectively included. Automated iodine quantification maps were reconstructed, and region of interest (ROI) measurements of iodine concentration (IC) (mg/cm3) were performed on whole renal lesions. In addition, for heterogeneous lesions, a secondary ROI was placed on the area most suspicious for malignancy. The discriminatory values of minimum, maximum, mean, and standard deviation for IC were compared using simple logistic regression and receiver operating characteristic curves (area under the curve [AUC]).

Results

A total of 259 renal lesions (243 RC and 16 RN) were analyzed. There were significant differences between RC and RN for all IC measures with the best-performing metrics being mean and maximum IC of the entire lesion ROI (AUC 0.912 and 0.917, respectively) but also mean and minimum IC of the most suspicious area in heterogeneous lesions (AUC 0.983 and 0.992, respectively). Most RC fell within a range of low measured iodine values although a few had higher values.

Conclusion

Automated iodine quantification maps reconstructed from clinical PCCT have a high diagnostic ability to differentiate RCs and neoplasms. The data from this pilot study can be used to help establish quantitative values for clinical differentiation of renal lesions.

Photon-Counting Computed Tomography Versus Energy-Integrating Dual-Energy Computed Tomography: Virtual Noncontrast Image Quality Comparison

PURPOSE

This study aimed to compare the image quality of portal venous phase-derived virtual noncontrast (VNC) images from photon-counting computed tomography (PCCT) with energy-integrating dual-energy computed tomography (EI-DECT) in the same patient using quantitative and qualitative analyses.

METHODS

Consecutive patients retrospectively identified with available portal venous phase-derived VNC images from both PCCT and EI-DECT were included. Patients without available VNC in picture archiving and communication system in PCCT or prior EI-DECT and non-portal venous phase acquisitions were excluded. Three fellowship-trained radiologists blinded to VNC source qualitatively assessed VNC images on a 5-point scale for overall image quality, image noise, small structure delineation, noise texture, artifacts, and degree of iodine removal. Quantitative assessment used region-of-interest measurements within the aorta at 4 standard locations, both psoas muscles, both renal cortices, spleen, retroperitoneal fat, and inferior vena cava. Attenuation (Hounsfield unit), quantitative noise (Hounsfield unit SD), contrast-to-noise ratio (CNR) (CNR vascular , CNR kidney , CNR spleen , CNR fat ), signal-to-noise ratio (SNR) (SNR vascular , SNR kidney , SNR spleen , SNR fat ), and radiation dose were compared between PCCT and EI-DECT with the Wilcoxon signed rank test. A P < 0.05 indicated statistical significance.

RESULTS

A total of 74 patients (27 men; mean ± SD age, 63 ± 13 years) were included. Computed tomography dose index volumes for PCCT and EI-DECT were 9.2 ± 3.5 mGy and 9.4 ± 9.0 mGy, respectively ( P = 0.06). Qualitatively, PCCT VNC images had better overall image quality, image noise, small structure delineation, noise texture, and fewer artifacts (all P < 0.00001). Virtual noncontrast images from PCCT had lower attenuation (all P < 0.05), noise ( P = 0.006), and higher CNR ( P < 0.0001-0.04). Contrast-enhanced structures had lower SNR on PCCT ( P = 0.001, 0.002), reflecting greater contrast removal. The SNRfat (nonenhancing) was higher for PCCT than EI-DECT ( P < 0.00001).

CONCLUSIONS

Virtual noncontrast images from PCCT had improved image quality, lower noise, improved CNR and SNR compared with those derived from EI-DECT.

Soft Reconstruction Kernels Improve HCC Imaging on a Photon-Counting Detector CT

RATIONALE AND OBJECTIVES

Hepatocellular carcinoma (HCC) is the only tumor entity that allows non-invasive diagnosis based on imaging without further histological proof. Therefore, excellent image quality is of utmost importance for HCC diagnosis. Novel photon-counting detector (PCD) CT improves image quality via noise reduction and higher spatial resolution, inherently providing spectral information. The aim of this study was to investigate these improvements for HCC imaging with triple-phase liver PCD-CT in a phantom and patient population study focusing on identification of the optimal reconstruction kernel.

MATERIALS AND METHODS

Phantom experiments were performed to analyze objective quality characteristics of the regular body and quantitative reconstruction kernels, each with four sharpness levels (36-40-44-48). For 24 patients with viable HCC lesions on PCD-CT, virtual monoenergetic images at 50 keV were reconstructed using these kernels. Quantitative image analysis included contrast-to-noise ratio (CNR) and edge sharpness. Three raters performed qualitative analyses evaluating noise, contrast, lesion conspicuity, and overall image quality.

RESULTS

In all contrast phases, the CNR was highest using the kernels with a sharpness level of 36 (all p < 0.05), with no significant influence on lesion sharpness. Softer reconstruction kernels were also rated better regarding noise and image quality (all p < 0.05). No significant differences were found in image contrast and lesion conspicuity. Comparing body and quantitative kernels with equal sharpness levels, there was no difference in image quality criteria, neither regarding in vitro nor in vivo analysis.

CONCLUSION

Soft reconstruction kernels yield the best overall quality for the evaluation of HCC in PCD-CT. As the image quality of quantitative kernels with potential for spectral post-processing is not restricted compared to regular body kernels, they should be preferred.

Quantitative performance of photon-counting CT at low dose: Virtual monochromatic imaging and iodine quantification

BACKGROUND

Quantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon-counting detectors (PCD) has reached clinical status.

PURPOSE

This work aimed to investigate the performance of a new photon-counting CT (PC-CT) in low-dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy-integrating detector dual-energy CT (DE-CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso-center, and solvent (tissue background) composition were explored.

METHODS

Quantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi-energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual-energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC-CT both tube voltages were set to either 120 or 140 kVp with photon-counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient-related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient-specific parameters.

RESULTS

The accuracy of IQ and VMI in the PC-CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC-CT scanner outperforms the DE-CT scanner in the IQ task in all cases. Iodine quantification bias in the PC-CT (-0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE-CT (range -2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE-CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC-CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obese population.

CONCLUSIONS

The statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC-CT. Although VMI performance was mostly comparable between the scanners, the DE-CT scanner quantitatively outperformed PC-CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X-ray tube potentials.

Clinical applications of photon counting detector CT

The X-ray detector is a fundamental component of a CT system that determines the image quality and dose efficiency. Until the approval of the first clinical photon-counting-detector (PCD) system in 2021, all clinical CT scanners used scintillating detectors, which do not capture information about individual photons in the two-step detection process. In contrast, PCDs use a one-step process whereby X-ray energy is converted directly into an electrical signal. This preserves information about individual photons such that the numbers of X-ray in different energy ranges can be counted. Primary advantages of PCDs include the absence of electronic noise, improved radiation dose efficiency, increased iodine signal and the ability to use lower doses of iodinated contrast material, and better spatial resolution. PCDs with more than one energy threshold can sort the detected photons into two or more energy bins, making energy-resolved information available for all acquisitions. This allows for material classification or quantitation tasks to be performed in conjunction with high spatial resolution, and in the case of dual-source CT, high pitch, or high temporal resolution acquisitions. Some of the most promising applications of PCD-CT involve imaging of anatomy where exquisite spatial resolution adds clinical value. These include imaging of the inner ear, bones, small blood vessels, heart, and lung. This review describes the clinical benefits observed to date and future directions for this technical advance in CT imaging. KEY POINTS: • Beneficial characteristics of photon-counting detectors include the absence of electronic noise, increased iodine signal-to-noise ratio, improved spatial resolution, and full-time multi-energy imaging. • Promising applications of PCD-CT involve imaging of anatomy where exquisite spatial resolution adds clinical value and applications requiring multi-energy data simultaneous with high spatial and/or temporal resolution. • Future applications of PCD-CT technology may include extremely high spatial resolution tasks, such as the detection of breast micro-calcifications, and quantitative imaging of native tissue types and novel contrast agents.

Surgical Sealant with Integrated Shape-Morphing Dual Modality Ultrasound and Computed Tomography Sensors for Gastric Leak Detection

Postoperative anastomotic leaks are the most feared complications after gastric surgery. For diagnostics clinicians mostly rely on clinical symptoms such as fever and tachycardia, often developing as a result of an already fully developed, i.e., symptomatic, surgical leak. A gastric fluid responsive, dual modality, electronic-free, leak sensor system integrable into surgical adhesive suture support materials is introduced. Leak sensors contain high atomic number carbonates embedded in a polyacrylamide matrix, that upon exposure to gastric fluid convert into gaseous carbon dioxide (CO2 ). CO2 bubbles remain entrapped in the hydrogel matrix, leading to a distinctly increased echogenic contrast detectable by a low-cost and portable ultrasound transducer, while the dissolution of the carbonate species and the resulting diffusion of the cation produces a markedly reduced contrast in computed tomography imaging. The sensing elements can be patterned into a variety of characteristic shapes and can be combined with nonreactive tantalum oxide reference elements, allowing the design of shape-morphing sensing elements visible to the naked eye as well as artificial intelligence-assisted automated detection. In summary, shape-morphing dual modality sensors for the early and robust detection of postoperative complications at deep tissue sites, opening new routes for postoperative patient surveillance using existing hospital infrastructure is reported.

Medical Radiology: Current Progress

Recently, medical radiology has undergone significant improvements in patient management due to advancements in image acquisition by the last generation of machines, data processing, and the integration of artificial intelligence. In this way, cardiovascular imaging is one of the fastest-growing radiological subspecialties. In this study, a compressive review was focused on addressing how and why CT and MR have gained a I class indication in most cardiovascular diseases, and the potential impact of tissue and functional characterization by CT photon counting, quantitative MR mapping, and 4-D flow. Regarding rectal imaging, advances in cancer imaging using diffusion-weighted MRI sequences for identifying residual disease after neoadjuvant chemoradiotherapy and [18F] FDG PET/MRI were provided for high-resolution anatomical and functional data in oncological patients. The results present a large overview of the approach to the imaging of diffuse and focal liver diseases by US elastography, contrast-enhanced US, quantitative MRI, and CT for patient risk stratification. Italy is currently riding the wave of these improvements. The development of large networks will be crucial to create high-quality databases for patient-centered precision medicine using artificial intelligence. Dedicated radiologists with specific training and a close relationship with the referring clinicians will be essential human factors.

New Contrast Media for K-Edge Imaging With Photon-Counting Detector CT

ABSTRACT

The recent technological developments in photon-counting detector computed tomography (PCD-CT) and the introduction of the first commercially available clinical PCD-CT unit open up new exciting opportunities for contrast media research. With PCD-CT, the efficacy of available iodine-based contrast media improves, allowing for a reduction of iodine dosage or, on the other hand, an improvement of image quality in low contrast indications. Virtual monoenergetic image reconstructions are routinely available and enable the virtual monoenergetic image energy to be adapted to the diagnostic task.A key property of PCD-CT is the ability of spectral separation in combination with improved material decomposition. Thus, the discrimination of contrast media from intrinsic or pathological tissues and the discrimination of 2 or more contrasting elements that characterize different tissues are attractive fields for contrast media research. For these approaches, K-edge imaging in combination with high atomic number elements such as the lanthanides, tungsten, tantalum, or bismuth plays a central role.The purpose of this article is to present an overview of innovative contrast media concepts that use high atomic number elements. The emphasis is on improving contrast enhancement for cardiovascular plaque imaging, stent visualization, and exploring new approaches using 2 contrasting elements. Along with the published research, new experimental findings with a contrast medium that incorporates tungsten are included.Both the literature review and the new experimental data demonstrate the great potential and feasibility for new contrast media to significantly increase diagnostic performance and to enable new clinical fields and indications in combination with PCD-CT.

A single-center, retrospective, cross-sectional study comparing the number of non-diagnostic measurements ratio in the pSWE and SSI ultrasound elastography methods

The point shear wave elastography and supersonic shear imaging methods were compared regarding incorrect measurements during the liver examinations. A report-based, single-center, retrospective analysis of 425 liver elastography examinations was performed. A lower success ratio was observed for the point shear wave elastography method, as well as the older and obese patients pre-dominated in non-diagnostic studies. In our center experience, it is easier to obtain diagnostic data using the supersonic shear imaging method. However, further investigation of the subject is needed.

Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

OBJECTIVES

To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series.

METHODS

Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNC_Conv) and a novel calcium-preserving (VNC_PC) algorithm. EAT was segmented on TNC, VNC_Conv, VNC_PC, and CCTA (CTA_-30) series using thresholds of -190 to -30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA₀). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data.

RESULTS

EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R² > 0.9). Measurements on the novel VNC_PC series showed the best correlation (R² = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were -12%, -3%, -13%, and +10% for VNC_Conv, VNC_PC, CTA_-30, and CTA₀ compared to TNC. Distribution of CT values on VNC_PC showed less difference to TNC than on VNC_Conv (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016).

CONCLUSIONS

VNC_PC-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient's radiation dose.

KEY POINTS

• Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R²>0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNC_PC) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.