Joachim Ernst Wildberger

Background: Stress perfusion cardiac magnetic resonance imaging (MRI) enables accurate detection of myocardial ischemia. While contrast injection parameters, particularly iodine delivery rate, are known to influence image quality in CT, their impact in cardiac MRI remains insufficiently studied. This study aimed to evaluate the effect of different gadolinium-based contrast agent (GBCA) injection rates on objective and subjective image quality in perfusion cardiac MRI in patients with suspected ischemic heart disease. Methods: Ninety patients scheduled for a stress perfusion cardiac MRI were retrospectively included and allocated to 3 groups based on the GBCA injection rate used (eg, group 1: 6 mL/s, group 2: 4 mL/s, and group 3: 2 mL/s). Blood-pool signal intensity was extracted on a frame-by-frame basis to generate signal-intensity time curves. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated for all relevant regions, including SNR _ischemia , SNR _blood , SNR _myocardium , CNR _{ischemia–blood} , CNR _{myocardium–blood} , and CNR _{ischemia–myocardium} . Subjective image quality was scored on a 5-point Likert scale, blindly assessed in consensus by 2 cardiovascular radiologists. Results: Blood-pool peak intensity was the highest in the group with flow rates of 6 mL/s. Peak signal intensity was for the 6, 4, and 2 mL/s group, respectively, 17525±3616, 15213±3416, and 15534±2990 a.u. ( P =0.019) and post hoc comparison demonstrated a significant difference between the 6 mL/s and 4 mL/s group ( P =0.027). No significant differences in signal intensity of the myocardium, blood pool and the infarcted region were found between groups ( P =0.475, 0.399 and 0.519, respectively). Image noise was significantly higher in group 1 compared to group 3 ( P value=0.036). SNR of myocardium, blood, and ischemia was not significantly different between groups ( P =0.525, 0.595, and 0.453, respectively). CNR for ischemia-blood, myocardium-blood and ischemia-myocardium were the highest in group 3, but not significantly different ( P =0.373, 0.896, and 0.346, respectively). Subjective image quality and reader confidence were not significantly different between groups ( P values of 0.985 and 0.842). Although contrast quality demonstrated a statistically significant difference across groups ( P =0.026), this finding was not considered clinically relevant. Conclusion: Higher GBCA injection rates resulted in higher blood-pool peak enhancement, yet did not translate into significant differences in objective image and subjective image quality. Lower injection rates appear sufficient to achieve adequate myocardial perfusion imaging, suggesting a plateau in image quality in which increasing flow rates do not show added benefit.

Purpose: Conventional energy integrating detector (EID) CT provides polyenergetic images where CT values depend on the tube voltage (kV), hampering quantitative analysis across different CT scans. To mitigate this problem, spectral CT such as photon-counting detector (PCD) CT offers virtual monoenergetic images (VMI) where CT values depend only on the keV level but, ideally, not on the tube voltage. The purpose of this study was to investigate the kV dependence of VMI CT values in PCD-CT across a wide range of tissue types, keV levels, and kV settings for various phantom sizes, and to determine which kV settings yield the optimal contrast-to-noise ratio ( CNR ) for a given VMI energy and phantom size. The phantom study was complemented with an exploratory patient study. Materials and Methods: A spectral abdomen phantom (QSA-543; QRM) with 2 optional fat rings was scanned on a PCD-CT (NAEOTOM Alpha; Siemens Healthineers). The phantom contained rods with 2/5/10/15 mg/mL iodine (QRM); muscle/fat/liver equivalent tissue; and 400 mg/mL calcium (Gammex Sun Nuclear). A standard abdomen protocol was used at tube voltages of 70/90/120/140 kV. Polyenergetic images and VMIs (range: 40 to 100 keV in 5 keV increments) were reconstructed. For each VMI energy (keV), the percentage deviation ΔCT (%) of the mean CT value across the different kV settings was determined for each rod using region-of-interest (ROI) analysis. A ΔCT of 10% was considered the clinically acceptable upper limit. For each kV setting, the iodine CNR was calculated and normalized to the radiation dose ( CTDIvol ) to obtain CNR _D . Higher CNR _D indicated higher radiation dose efficiency. Edge spread functions (EFS) and noise power spectra (NPS) were evaluated for various kV settings. In the retrospective patient study, a standard cerebral CT angiography (CTA) protocol was applied at either 140 kV (n = 42) or 90 kV (n = 25), with VMI reconstructed at 55 keV. Both the ΔCT (%) and the CNR _D relative to the ventricles were determined for various cerebral arteries. The 2 groups were compared using unpaired t tests. Results: For all iodine and calcium rods and all phantom sizes, CT values remained stable within the predefined 10% tolerance across all kV settings in the VMI energy range of 40 to 70 keV, with ΔCT ≤8.4%. At 100 keV, ΔCT increased for low iodine concentration, reaching up to 36%, corresponding to a deviation of 19 HU from the mean CT value of 54 HU for 5 mg/mL iodine. Adipose tissue and liver exhibited ΔCT ≤10% at 45 to 70 keV. At 40 keV, deviations were larger but remained small in absolute terms (11.0 HU for liver and 19.6 HU for adipose tissue in the large phantom). For the small phantom and 40-60 keV, CNR _D was 10% to 13% higher for 70/90 kV compared with 120/140 kV. EFS and NPS were consistent across kV settings. This advantage was lost at higher keV and larger phantoms. In patient VMIs at 55 keV, CNR _D was 17% to 29% higher at 90 kV than at 140 kV, albeit generally not statistically significant. Conclusions: In VMIs acquired with PCD-CT, CT values were stable within the predefined 10% tolerance for all phantom sizes and tube voltages in the energy range of 45 to 70 keV, which is relevant for contrast-enhanced CT. This represents a significant step towards the meaningful comparison of CT values across different CT scans. At low keV and small phantom sizes, scans at 70 or 90 kV demonstrated greater radiation dose efficiency compared with scans at 120 or 140 kV. Therefore, for routine contrast-enhanced CT examinations of small patients or small body parts (eg, CTA of the head), scanning at low tube voltage may be considered if no spectral results other than VMIs are required.

Background/Objectives: 18F-fluorocholine is a positron emission tomography (PET) tracer earlier found to be a marker of macrophage content in carotid plaques. We aimed to assess the feasibility of 18F-choline PET-MRI to non-invasively localize vulnerable coronary plaques, using optical coherence tomography (OCT) as a reference standard. Methods: Patients with recent myocardial infarction who were scheduled for a secondary angiography of a non-culprit vessel underwent 18F-fluorocholine coronary PET-MRI. Subsequently, OCT was performed during the secondary angiography. Maximum target-to-background (TBRmax) values of 18F-fluorocholine uptake were determined in two vessel sections that contained either vulnerable or stable plaques as defined by OCT. The OCT-based definition of a vulnerable plaque was a fibrous cap thickness < 70 µm. To enhance the detectability of coronary plaques using PET, three different motion-correction strategies were used: multigate respiratory gating motion correction (MRG-MOCO), extended MR-based motion correction (eMR-MOCO), and extended MR-based motion correction with ECG gating (eMR-MOCO-ECG). Results: Fifteen patients were included in this study. One patient needed to be excluded due to extravasation of the tracer. In another patient, no region with only a stable plaque could be identified. TBRmax values were as follows for three different reconstructions in vulnerable versus stable plaques: MRG-MOCO: mean TBRmax 1.45 vs. 1.35, p = 0.52 (n = 13); eMR-MOCO: mean TBRmax 1.47 vs. 1.27, p = 0.26 (n = 11); eMR-MOCO-ECG: mean TBRmax 1.49 vs. 1.26, p = 0.21 (n = 11). Conclusions: 18F-fluorocholine uptake in vulnerable atherosclerotic plaques in coronary arteries was not significantly different from uptake in stable plaques, even though advanced motion-correction methods were applied. That may be caused by multiple factors, such as small coronary plaque size, tracer biology, or remaining cardiac motion.

Objectives: To develop a simple rule-of-thumb on how to reduce the contrast medium (CM) dose in photon-counting detector CT (PCD-CT) when lowering the energy of the reconstructed virtual mono-energetic images (VMI) while maintaining the contrast-to-noise ratio (CNR) for parenchymal CT and CTA. Materials and Methods: Spectral abdominal and chest CT phantoms were scanned using a portal venous phase (PVP) abdominal and a high-pitch CTA protocol, respectively, on a first-generation dual-source PCD-CT. The phantoms contained cylindrical rods with iodine in water equivalent material (0.5/1.0/2.0/5.0/10.0/15.0 mg I/mL) and ICRU muscle tissue. The phantoms were complemented with 2 fat equivalent rings to mimic different patient sizes. Iodine contrast, image noise, noise power spectra (NPS), and iodine CNR were investigated in VMIs with different energies (40 to 60 keV in steps of 5 keV). This was done for different iodine concentrations, phantom sizes, x-ray tube voltages (120 kV and 140 kV) and radiation doses. In addition, 15 abdominal and 15 CT angiographic patient scans [body mass index (BMI) range: 17 to 37 kg/m ² ] were retrospectively analyzed to determine the CNR at different VMI energies. Results: Contrast at a given iodine concentration and VMI energy was independent of phantom size, radiation dose, and acquisition voltage (kV). With decreasing VMI energy, the maximum of the NPS curves increased, while their shape remained similar, indicating higher noise but similar noise texture. The CNR increased with lower VMI energy for a given iodine concentration and phantom size, while CNR decreased with increasing phantom size for a given VMI energy and iodine concentration. When the VMI energy was lowered by 5 keV steps in the range of 60 to 40 keV, similar CNR could be maintained when reducing the iodine concentration at each step by 11.7% to 13.7% for abdominal PVP scans and 11.8% to 14.5% for CTAs. CNR analysis of the patient scans confirmed these findings: a 5 keV reduction in VMI energy led to a mean±SD 11.4%±0.4% and 13.7%±1.0% increase in CNR for abdomen PVP and CTA scans, respectively. This can be translated to a corresponding reduction in CM dose when a constant CNR is aimed for. From these results, a simple, robust rule-of-thumb was derived, the 10-to-5 rule: For the evaluated PCD-CT protocols, CNR can be maintained with about 10% less CM dose for each reduction of the VMI energy by 5 keV. Conclusions: This phantom study, which was complemented with a retrospective proof-of-principle patient study, showed that a simple, easy to implement 10-to-5 rule-of-thumb might be used in daily practice for contrast-enhanced PCD-CT. It allows for individual adaptation of the CM dose to the VMI energy applied.

Background/Objectives: To validate an artificial intelligence-based arterial input function (AI-AIF) deep learning model for myocardial blood flow (MBF) quantification during stress perfusion and assess its extension to rest perfusion, enabling myocardial perfusion reserve (MPR) calculation. Methods: Sixty patients with or at risk for vascular cognitive impairment, prospectively enrolled in the CRUCIAL consortium, underwent quantitative stress and rest myocardial perfusion imaging using a 3 T MRI system. Perfusion imaging was performed using a dual-sequence (DS) protocol after intravenous administration of 0.05 mmol/kg gadobutrol. Retrospectively, the AI-AIF was estimated from standard perfusion images using a 1-D U-Net model trained to predict an unsaturated AIF from a saturated input. MBF was quantified using Fermi function-constrained deconvolution with motion compensation. MPR was calculated as the stress-to-rest MBF ratio. MBF and MPR estimates from both AIF methods were compared using Bland–Altman analyses. Results: Complete stress and rest perfusion datasets were available for 31 patients. A bias of −0.07 mL/g/min was observed between AI-AIF and DS-AIF for stress MBF (median 2.19 vs. 2.30 mL/g/min), with concordant coronary artery disease classification based on the optimal MBF threshold in over 92% of myocardial segments and coronary arteries. Larger biases of 0.12 mL/g/min and −0.30 were observed for rest MBF (1.12 vs. 1.02 mL/g/min) and MPR (2.31 vs. 1.84), respectively, with lower concordance using the optimal MPR threshold (85% of segments, 72% of arteries). Conclusions: The AI-AIF model showed comparable performance to DS-AIF for stress MBF quantification but requires further training for accurate rest MBF and MPR assessment.

Hybrid PET-MRI systems are being used more frequently. One of the drawbacks of PET-MRI imaging is its inferiority in detecting lung nodules, so it is often combined with a computed tomography (CT) of the chest. However, chest CT often detects additional, indeterminate lung nodules. The objective of this study was to assess the sensitivity of detecting metastatic versus indeterminate nodules with PET-MRI compared to chest CT. A total of 328 patients were included. All patients had a PET/MRI whole-body scan for (re)staging of cancer combined with an unenhanced chest CT performed at our center between 2014 and 2020. Patients had at least a two-year follow-up. Six percent of the patients had lung metastases at initial staging. The sensitivity and specificity of PET-MRI for detecting lung metastases were 85% and 100%, respectively. The incidence of indeterminate lung nodules on chest CT was 30%. The sensitivity of PET-MRI to detect indeterminate lung nodules was poor (23.0%). The average size of the indeterminate lung nodules detected on PET-MRI was 7 ± 4 mm, and the missed indeterminate nodules on PET-MRI were 4 ± 1 mm (p < 0.001). The detection of metastatic lung nodules is fairly good with PET-MRI, whereas the sensitivity of PET-MRI for detecting indeterminate lung nodules is size-dependent. This may be an advantage, limiting unnecessary follow-up of small, indeterminate lung nodules while adequately detecting metastases.

Objective: Photon-counting detector computed tomography (PCD-CT) enables spectral data acquisition of CT angiographies allowing for reconstruction of virtual monoenergetic images (VMIs) in routine practice. Specifically, it has potential to reduce the blooming artifacts associated with densely calcified plaques. However, calcium blooming and iodine attenuation are inversely affected by energy level (keV) of the VMIs, creating a challenge for contrast media (CM) injection protocol optimization. A pragmatic and simple rule for calcium-dependent CM injection protocols is investigated and proposed for VMI-based coronary CT angiography with PCD-CT. Materials and Methods: A physiological circulation phantom with coronary vessels including calcified lesions (maximum CT value >700 HU) with a 50% diameter stenosis was injected into at iodine delivery rates (IDRs) of 0.3, 0.5, 0.7, 1.0, 1.5, 2.0, 2.5, and 3.0 g I/s. Images were acquired using a first-generation dual-source PCD-CT and reconstructed at various VMI levels (between 45 and 190 keV). Iodine attenuation in the coronaries was measured at each IDR for each keV, and blooming artifacts from the calcified lesions were assessed including stenosis grading error (as % overestimation vs true lumen). The IDR to achieve 300 HU at each VMI level was then calculated and compared with stenosis grading accuracy to establish a general rule for CM injection protocols. Results: Plaque blooming artifacts and intraluminal iodine attenuation decreased with increasing keV. Fixed windowing (representing absolute worst case) resulted in stenosis overestimation from 77% ± 4% at 45 keV to 5% ± 2% at 190 keV, whereas optimized windowing resulted in overestimation from 29% ± 3% at 45 keV to 4% ± 1% at 190 keV. The required IDR to achieve 300 HU showed a strong linear correlation to VMI energy (R ² = 0.98). Comparison of this linear plot versus stenosis grading error and blooming artifact demonstrated that multipliers of 1, 2, and 3 times the reference IDR for theoretical clinical regimes of no, moderate, and severe calcification density, respectively, can be proposed as a general rule. Conclusions: This study provides a proof-of-concept in an anthropomorphic phantom for a simple pragmatic adaptation of CM injection protocols in coronary CT angiography with PCD-CT. The 1-2-3 rule demonstrates the potential for reducing the effects of calcium blooming artifacts on overall image quality.

Objectives: Calcified plaques induce blooming artifacts in coronary computed tomography angiography (CCTA) potentially leading to inaccurate stenosis evaluation. Tungsten represents a high atomic number, experimental contrast agent with different physical properties than iodine. We explored the potential of a tungsten-based contrast agent for photon-counting detector (PCD) CCTA in heavily calcified coronary vessels. Materials and Methods: A cardiovascular phantom exhibiting coronaries with calcified plaques was imaged on a first-generation dual-source PCD-CT. The coronaries with 3 different calcified plaques were filled with iodine and tungsten contrast media solutions equating to iodine and tungsten delivery rates (IDR and TDR) of 0.3, 0.5, 0.7, 1.0, 1.5, 2.0, 2.5, and 3.0 g/s, respectively. Electrocardiogram-triggered sequential acquisitions were performed in the spectral mode (QuantumPlus). Virtual monoenergetic images (VMIs) were reconstructed from 40 to 190 keV in 1 keV increments. Blooming artifacts and percentage error stenoses from calcified plaques were quantified, and attenuation characteristics of both contrast media were recorded. Results: Blooming artifacts from calcified plaques were most pronounced at 40 keV (78%) and least pronounced at 190 keV (58%). Similarly, percentage error stenoses were highest at 40 keV (48%) and lowest at 190 keV (2%), respectively. Attenuation of iodine decreased monotonically in VMIs from low to high keV, with the strongest decrease from 40 keV to 100 keV (IDR of 2.5 g/s: 1279 HU at 40 keV, 187 HU at 100 kV, and 35 HU at 190 keV). The attenuation of tungsten, on the other hand, increased monotonically as a function of VMI energy, with the strongest increase between 40 and 100 keV (TDR of 2.5 g/s: 202 HU at 40 keV, 661 HU at 100 kV, and 717 HU at 190 keV). For each keV level, the relationship between attenuation and IDR/TDR could be described by linear regressions (R ² ≥ 0.88, P < 0.001). Specifically, attenuation increased linearly when increasing the delivery rate irrespective of keV level or contrast medium. Iodine exhibited the highest relative increase in attenuation values at lower keV levels when increasing the IDR. Conversely, for tungsten, the greatest relative increase in attenuation values occurred at higher keV levels when increasing the TDR. When high keV imaging is desirable to reduce blooming artifacts from calcified plaques, IDR has to be increased at higher keV levels to maintain diagnostic vessel attenuation (ie, 300 HU), whereas for tungsten, TDR can be kept constant or can be even reduced at high keV energy levels. Conclusions: Tungsten's attenuation characteristics in relation to VMI energy levels are reversed to those of iodine, with tungsten exhibiting high attenuation values at high keV levels and vice versa. Thus, tungsten shows promise for high keV imaging CCTA with PCD-CT as—in distinction to iodine—both high vessel attenuation and low blooming artifacts from calcified plaques can be achieved.

Background: Coronary artery calcification (CAC) is associated with poor outcome in critically ill patients. A deterioration in cardiac conduction and loss of myocardial tissue could be an underlying cause. Vectorcardiography (VCG) and cardiac biomarkers provide insight into these underlying causes. The aim of this study was to investigate whether a high degree of CAC is associated with VCG-derived variables and biomarkers, including high-sensitivity troponin-T (hs-cTnT) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Methods: Mechanically ventilated coronavirus-19 (COVID-19) patients with an available chest computed tomography (CT) and 12-lead electrocardiogram (ECG) were studied. CAC scores were determined using chest CT scans. Patients were categorized into 3 sex-specific tertiles: low, intermediate, and high CAC. Daily 12 leads-ECGs were converted to VCGs. Daily hs-cTnT and NT-proBNP levels were determined. Linear mixed-effects regression models examined the associations between CAC tertiles and VCG variables, and between CAC tertiles and hs-cTnT or NT-proBNP levels. Results: In this study, 205 patients (73.2% men, median age 65 years [IQR 57.0; 71.0]) were included. Compared to the lowest CAC tertile, the highest CAC tertile had a larger QRS area at baseline (6.65 µVs larger [1.50; 11.81], p = 0.012), which decreased during admission (− 0.27 µVs per day [− 0.43; − 0.11], p = 0.001). Patients with the highest CAC tertile also had a longer QRS duration (12.02 ms longer [4.74; 19.30], p = 0.001), higher levels of log hs-cTnT (0.79 ng/L higher [0.40; 1.19], p < 0.001) and log NT-proBNP (0.83 pmol/L higher [0.30; 1.37], p = 0.002). Conclusion: Patients with a high degree of CAC had the largest QRS area and higher QRS amplitude, which decreased more over time when compared to patients with a low degree of CAC. These results suggest that CAC might contribute to loss of myocardial tissue during critical illness. These insights could improve risk stratification and prognostication of patients with critical illness.