[Usefulness of Electron Density Calculated from Dual Energy CT in Differential Diagnosis between Hepatocellular Carcinoma and Hepatic Hemangioma].

PURPOSE: The aim of this study were to compare electron density (ED), obtained by dual energy computed tomography (DECT), between hepatocellular carcinoma (HCC) and hemangioma, and to assess the differential diagnostic performance of ED between HCC and hemangioma. METHODS: A total of 46 patients (27 men and 19 women; mean age, 65.7±14.0 years) diagnosed with HCC or hemangioma who underwent upper abdominal DECT between October 2021 and December 2022 were included. ED of each lesion was measured. Relative ED (rED), which is normalized by the ED of background liver parenchyma, was calculated. ED and rED of HCC and hemangioma were statistically analyzed. RESULTS: The HCC group showed significantly higher ED (48.1±5.2) and rED (80.0±7.3) than the hemangioma group (43.7±4.1, 69.7±7.2, respectively) (p<0.01). The area under the curve of rED was greater than that of ED, but no significant difference was found (p=0.153). CONCLUSION: ED may help in the differential diagnosis between HCC and hemangioma.

[Usefulness of Breath-hold DWI Focused on the Hepatic Dome in EOB-MRI].

PURPOSE: Respiratory-triggered-diffusion-weighted imaging (R-DWI) of the liver often results in poor image quality under the diaphragmatic dome on the cephalic side of the liver (hepatic dome) secondary to magnetic field inhomogeneity in liver magnetic resonance imaging (MRI). Hence, the usefulness of additional breath-hold-DWI (B-DWI) focusing on the hepatic dome was investigated. METHODS: A total of 22 patients (14 men and 8 women; mean age 69.0±11.7 years) who underwent ethoxybenzyl (EOB)-MRI at our hospital between July and August, 2022 using a 3.0 T MRI system were included. One radiologist and three radiology technologists visually assessed the visibility of R-DWI and B-DWI in the hepatic dome on a 4-point scale (1 to 4). Additionally, the apparent diffusion coefficient (ADC) values of the hepatic parenchyma on each DWI were compared. RESULTS: B-DWI improved visibility in the hepatic dome compared to R-DWI (2.67±0.71 vs. 3.25±0.43, p<0.05). No significant difference was found in the ADC values for each DWI. CONCLUSION: B-DWI has excellent visibility in the hepatic dome and is expected to complement R-DWI. Therefore, B-DWI is very useful as an additional imaging in EOB-MRI.

Specific Binding Ratio Estimation of [123I]-FP-CIT SPECT Using Frontal Projection Image and Machine Learning.

This study aimed to develop a new convolutional neural network (CNN) method for estimating the specific binding ratio (SBR) from only frontal projection images in single-photon emission-computed tomography using [123I]ioflupane. We created five datasets to train two CNNs, LeNet and AlexNet: (1) 128FOV used a 0° projection image without preprocessing, (2) 40FOV used 0° projection images cropped to 40 × 40 pixels centered on the striatum, (3) 40FOV training data doubled by data augmentation (40FOV_DA, left-right reversal only), (4) 40FOVhalf, and (5) 40FOV_DAhalf, split into left and right (20 × 40) images of 40FOV and 40FOV_DA to separately evaluate the left and right SBR. The accuracy of the SBR estimation was assessed using the mean absolute error, root mean squared error, correlation coefficient, and slope. The 128FOV dataset had significantly larger absolute errors compared to all other datasets (p < 0. 05). The best correlation coefficient between the SBRs using SPECT images and those estimated from frontal projection images alone was 0.87. Clinical use of the new CNN method in this study was feasible for estimating the SBR with a small error rate using only the frontal projection images collected in a short time.

Separating spin compartments in arterial spin labeling using delays alternating with nutation for tailored excitation (DANTE) pulse: A validation study using T2 -relaxometry and application to arterial cerebral blood volume imaging.

PURPOSE: To clarify the type of spin compartment in arterial spin labeling (ASL) that is eliminated by delays alternating with nutation for tailored excitation (DANTE) pulse using T2 -relaxometry, and to demonstrate the feasibility of arterial cerebral blood volume (CBVa ) imaging using DANTE-ASL in combination with a simplified two-compartment model. METHOD: The DANTE and T2 -preparation modules were combined into a single ASL sequence. T2 values under the application of DANTE were determined to evaluate changes in T2 , along with the post-labeling delay (PLD) and the relationship between transit time without DANTE (TTnoVS ) and T2 . The reference tissue T2 (T2_ref ) was also obtained. Subsequently, the DANTE module was embedded into the Hadamard-encoded ASL. Cerebral blood flow (CBF) and CBVa were computed using two Hadamard-encoding datasets (with and without DANTE) in a rest and breath-holding (BH) task. RESULTS: While T2 without DANTE (T2_noVS ) decreased as the PLD increased, T2 with DANTE (T2_DANTE ) was equivalent to T2_ref and did not change with the PLD. Although there was a significant positive correlation between TTnoVS and T2_noVS with short PLD, T2_DANTE was not correlated with TTnoVS nor PLD. Baseline CBVa values obtained at rest were 0.64 ± 0.12, 0.64 ± 0.11, and 0.58 ± 0.15 mL/100 g for anterior, middle, and posterior cerebral arteries, respectively. Significant CBF and CBVa elevations were observed in the BH task. CONCLUSION: Microvascular compartment signals were eliminated from the total ASL signals by DANTE. CBVa can be measured using Hadamard-encoded DANTE-ASL in combination with a simplified two-compartment model.

Acquisition count dependence of the specific binding ratio in 123I-FP-CIT SPECT.

OBJECTIVE: In the [123I]FP-CIT single-photon emission computed tomography (SPECT) examination, the specific binding ratio (SBR), calculated from the ratio of the striatal specific to extra-striatal background non-specific binding in the brain, is now commonly used as a quantitative index of parkinsonian syndrome. The purpose of this study was to examine the influence of count reduction on the SBR and to clarify the reliability of SBR values in patients with shorter scan times. METHODS: A striatum phantom was used in a phantom study, with the radioactivity concentration adjusted so that the right striatum:left striatum:brain parenchyma ratio was 8:4:1. Changes in SBR values and image quality, expressed as the % coefficient of variation (%CV) and normalized mean squared error (NMSE), with decreasing acquisition counts were evaluated. In the clinical study, 106 patients (73.1 ± 9.6 years) with suspected parkinsonian syndrome underwent [123I]FP-CIT SPECT, and SBR values from normal 30 min acquisitions (fullSBR) and half-count acquisitions (halfSBR) were compared. SBR values were calculated using the Tossici-Bolt (SBRTB) and a fully automatic count-based (SBRcb) methods. RESULTS: In the phantom study, image quality decreased with a reduction of acquisition counts. The %CV and NMSE decreased by up to 52.5% and 81.5%, respectively. SBR values decreased slightly as acquisition counts decreased. In the clinical study, the mean values of halfSBR were lower than those of fullSBR, and they were significantly different except for SBRTB without attenuation correction. halfSBR and fullSBR values correlated well, with halfSBR values 1-8% lower than fullSBR. The accuracy of diagnosis did not decrease even after acquisition counts were reduced by half. CONCLUSION: This study demonstrated that SBR values decrease as a function of reduced acquisition counts. Since halfSBR and fullSBR showed excellent correlation, it is suggested that fullSBR can be estimated from halfSBR using a calibration formula when scan times are reduced.

Examining electrometer performance checks with direct-current generator in a clinic: Assessment of generated charges and implementation of electrometer checks.

PURPOSE: Medical physicists use a suitable detector connected to an electrometer to measure radiotherapy beams. Each detector and electrometer has a lifetime (due to physical deterioration of detector components and electrical characteristic deterioration in electronic electrometer components), long-term stability [according to IEC 60731:2011, ≤0.5% (reference-class dosimeter)], and calibration frequency [according to Muir et al. (J Appl Clin Med Phys. 2017; 18:182-190), generally 2 years]; thus, physicists should check the electrometer and detector separately. However, to the best of our knowledge, only one study (Blad et al., Phys Med Biol. 1998; 43:2385-2391) has reported checking the electrometer independently from the detector. The present study conducts performance checks on electrometers separately from the detector in clinical settings, using an electrometer equipped with a direct current (DC) generator (EMF 521R) capable of injecting DC (effective range: ±20 pA to ±20 nA) into itself or another electrometer. METHODS: First, to check the nonlinearity of the generated currents from ±20 pA to ±20 nA, charges generated from the DC generator were measured with the EMF 521R electrometer. Next, six reference-class electrometers classified according to IEC 60731:2011 were checked for repeatability at a current of ±20 pA or a minimum effective indicated value meeting IEC 60731:2011, as well as for nonlinearity within the current range from ±20 pA to ±20 nA. RESULTS: The nonlinearities for the measured currents were less than ±0.05%. The repeatability for the six electrometers was < 0.1%. While the nonlinearity of one electrometer reached up to 0.22% at a current of -20 pA, all six electrometers displayed nonlinearities of less than ±0.1% at currents of ±100 pA or higher. CONCLUSIONS: This work suggests that it is possible to check the nonlinearity and repeatability of clinical electrometers with DCs above the ±30 pA level using a DC generator in a clinic.

Robust arterial transit time and cerebral blood flow estimation using combined acquisition of Hadamard-encoded multi-delay and long-labeled long-delay pseudo-continuous arterial spin labeling: a simulation and in vivo study.

Arterial transit time (ATT) prolongation causes an error of cerebral blood flow (CBF) measurement during arterial spin labeling (ASL). To improve the accuracy of ATT and CBF in patients with prolonged ATT, we propose a robust ATT and CBF estimation method for clinical practice. The proposed method consists of a three-delay Hadamard-encoded pseudo-continuous ASL (H-pCASL) with an additional-encoding and single-delay with long-labeled long-delay (1dLLLD) acquisition. The additional-encoding allows for the reconstruction of a single-delay image with long-labeled short-delay (1dLLSD) in addition to the normal Hadamard sub-bolus images. Five different images (normal Hadamard 3 delay, 1dLLSD, 1dLLLD) were reconstructed to calculate ATT and CBF. A Monte Carlo simulation and an in vivo study were performed to access the accuracy of the proposed method in comparison to normal 7-delay (7d) H-pCASL with equally divided sub-bolus labeling duration (LD). The simulation showed that the accuracy of CBF is strongly affected by ATT. It was also demonstrated that underestimation of ATT and CBF by 7d H-pCASL was higher with longer ATT than with the proposed method. Consistent with the simulation, the 7d H-pCASL significantly underestimated the ATT compared to that of the proposed method. This underestimation was evident in the distal anterior cerebral artery (ACA; P = 0.0394) and the distal posterior cerebral artery (PCA; 2 P = 0.0255). Similar to the ATT, the CBF was underestimated with 7d H-pCASL in the distal ACA (P = 0.0099), distal middle cerebral artery (P = 0.0109), and distal PCA (P = 0.0319) compared to the proposed method. Improving the SNR of each delay image (even though the number of delays is small) is crucial for ATT estimation. This is opposed to acquiring many delays with short LD. The proposed method confers accurate ATT and CBF estimation within a practical acquisition time in a clinical setting.

Optimizing scan timing of hepatic arterial phase by physiologic pharmacokinetic analysis in bolus-tracking technique by multi-detector row computed tomography.

Our aim in this study was to determine an optimal delay time of hepatic arterial phase (HAP) imaging of hypervascular hepatocellular carcinomas (HCCs) in dynamic contrast-enhanced MDCT (DCE-CT) by use of the bolus-tracking method. The time-enhancement curves (TECs) of the aorta and the contrast of the hepatic arterial and portal system (APC) in the pharmacokinetic analysis were calculated. The clinical study included 41 patients with known or suspected HCC who underwent DCE-CT. The TECs of the aorta and the tumor-liver contrast (TLC) in the clinical study were calculated. On pharmacokinetic analysis, the peak aortic enhancement and the peak APC simulated under conditions of an injection duration of 30 s and an iodine load of 500 mg I/kg body weight were observed 18.5 and 22.5 s, respectively, after the trigger threshold (increased CT value 100 Hounsfield units), respectively. In the clinical study, the peak aortic enhancement and the peak TLC were observed 17.2 and 24.8 s after the trigger threshold, respectively. The optimal delay times until peak aortic enhancement and peak HAP were 15-17 and 19-21 s after the trigger threshold, respectively, under the following conditions: injection dose, 500 mg I/kg body weight; injection duration, 30 s; acquisition time, 5 s; and the trigger threshold. In addition, the peak TLC was achieved 4-7 s after the time to peak aortic enhancement.

Evaluation of required saline volume in dynamic contrast-enhanced computed tomography using saline flush technique.

The present study was performed to find the required volume of physiological saline for flushing that will allow the most efficient use of contrast medium during the early phase of dynamic CT. We calculated contrast medium aortic arrival time (AT), time to peak aortic enhancement (TPAE) and the elapsed time to TPAE from AT (rise time) from the TECs of pharmacokinetic analysis and clinical study. The rise time determined in the clinical study was 6.2s, which was shorter than that in the simulation study. In the present study, an appropriate volume for saline flush was estimated to be about 18 ml.

Operation of bolus tracking system for prediction of aortic peak enhancement at multidetector row computed tomography: pharmacokinetic analysis and clinical study.

PURPOSE: The present study was performed to identify the theoretical background for optimal use of the bolus tracking system by analyzing the changes in the initial slope of the aortic time-enhancement curve (TEC). MATERIALS AND METHODS: We calculated the contrast medium aortic arrival time (TAR), the time to reach the trigger threshold (effective TAR), the slope of the linear equation of the enhancement unit (enhancement rate), and the time to peak aortic enhancement from the TECs of the pharmacokinetic analysis and retrospective clinical study. RESULTS: In the pharmacokinetic analysis, the enhancement rate-simulated under conditions of injection duration 30 s and iodine load per body weight 500 mg/kg-was 27.1 HU/s. In the clinical study, the enhancement rate was 27.9 +/- 3.0 HU/s. A correlation was found between the TAR and the enhancement rate, indicating that enhancement rates decrease with increasing TAR. It took 22.7 +/- 0.5 s to reach maximum enhancement of the aorta from the trigger threshold of an increase of 100 HU and injection duration at 30 s. CONCLUSION: We found that cardiac output differences are strongly dependent on the TAR and that most of the differences disappeared during the phase until effective TAR.

[Estimation of aortic time-enhancement curve in pharmacokinetic analysis: dynamic study by multi-detector row computed tomography].

This paper presents an introduction to the development of software that provides a physiologic model of contrast medium enhancement by incorporating available physiologic data and contrast medium pharmacokinetics to predict an organ-specific aortic time-enhancement curve(TEC)in computed tomography(CT)with various contrast medium injection protocols in patients of various heights, weights, cardiac output levels, and so on. The physiologic model of contrast medium enhancement was composed of six compartments for early contrast enhancement pharmacokinetics. Contrast medium is injected via the antecubital vein and distributed to the right side of the heart, the pulmonary compartment, the left side of the heart, and the aorta. It then circulates back to the right side of the heart via the systemic circulation. A computer-based, compartmental model of the aortic system was generated using human physiologic parameters and six differential equations to describe the transport of contrast medium. Aortic TEC generated by the computer-based physiologic model of contrast medium enhancement showed validity and agreement with clinical data and findings published previously. A computer-based physiologic model that may help predict organ-specific CT contrast medium enhancement for different injection protocols was developed. Such a physiologic model may have multiple clinical applications.

[Method for determining scan timing based on analysis of formation process of the time-density curve].

A strict determination of scan timing is needed for dynamic multi-phase scanning and 3D-CT angiography (3D-CTA) by multi-detector row CT (MDCT) . In the present study, contrast media arrival time (T(AR)) was measured in the abdominal aorta at the bifurcation of the celiac artery for confirmation of circulatory differences in patients. In addition, we analyzed the process of formation of the time-density curve (TDC) and examined factors that affect the time to peak aortic enhancement (T(PA)). Mean T(AR) was 15.57+/-3.75 s. TDCs were plotted for each duration of injection. The rising portions of TDCs were superimposed on one another. TDCs with longer injection durations were piled up upon one another. Rise angle was approximately constant in response to each flow rate. Rise time (T(R)) showed a good correlation with injection duration (T(ID)). T(R) was 1.01 TID (R(2)=0.994) in the phantom study and 0.94 T(ID)-0.60 (R(2)=0.988) in the clinical study. In conclusion, for the selection of optimal scan timing it is useful to determine T(R) at a given point and to determine the time from T(AR).