Ferumoxtran-10-enhanced MRI for pre-operative metastatic lymph node detection in pancreatic, duodenal, or periampullary adenocarcinoma.

OBJECTIVES: To assess 3-Tesla (3-T) ultra-small superparamagnetic iron oxide (USPIO)-enhanced MRI in detecting lymph node (LN) metastases for resectable adenocarcinomas of the pancreas, duodenum, or periampullary region in a node-to-node validation against histopathology. METHODS: Twenty-seven consecutive patients with a resectable pancreatic, duodenal, or periampullary adenocarcinoma were enrolled in this prospective single expert centre study. Ferumoxtran-10-enhanced 3-T MRI was performed pre-surgery. LNs found on MRI were scored for suspicion of metastasis by two expert radiologists using a dedicated scoring system. Node-to-node matching from in vivo MRI to histopathology was performed using a post-operative ex vivo 7-T MRI of the resection specimen. Sensitivity and specificity were calculated using crosstabs. RESULTS: Eighteen out of 27 patients (median age 65 years, 11 men) were included in the final analysis (pre-surgery withdrawal n = 4, not resected because of unexpected metastases peroperatively n = 2, and excluded because of inadequate contrast-agent uptake n = 3). On MRI 453 LNs with a median size of 4.0 mm were detected, of which 58 (13%) were classified as suspicious. At histopathology 385 LNs with a median size of 5.0 mm were found, of which 45 (12%) were metastatic. For 55 LNs node-to-node matching was possible. Analysis of these 55 matched LNs, resulted in a sensitivity and specificity of 83% (95% CI: 36-100%) and 92% (95% CI: 80-98%), respectively. CONCLUSION: USPIO-enhanced MRI is a promising technique to preoperatively detect and localise LN metastases in patients with pancreatic, duodenal, or periampullary adenocarcinoma. CLINICAL RELEVANCE STATEMENT: Detection of (distant) LN metastases with USPIO-enhanced MRI could be used to determine a personalised treatment strategy that could involve neoadjuvant or palliative chemotherapy, guided resection of distant LNs, or targeted radiotherapy. REGISTRATION: The study was registered on clinicaltrials.gov NCT04311047. https://clinicaltrials.gov/ct2/show/NCT04311047?term=lymph+node&cond=Pancreatic+Cancer&cntry=NL&draw=2&rank=1 . KEY POINTS: LN metastases of pancreatic, duodenal, or periampullary adenocarcinoma cannot be reliably detected with current imaging. This technique detected LN metastases with a sensitivity and specificity of 83% and 92%, respectively. MRI with ferumoxtran-10 is a promising technique to improve preoperative staging in these cancers.

Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.

OBJECTIVE: To evaluate the image quality and lesion detectability of pancreatic phase thin-slice computed tomography (CT) images reconstructed with a deep learning-based reconstruction (DLR) algorithm compared with filtered-back projection (FBP) and hybrid iterative reconstruction (IR) algorithms. METHODS: Fifty-three patients who underwent dynamic contrast-enhanced CT including pancreatic phase were enrolled in this retrospective study. Pancreatic phase thin-slice (0.625 mm) images were reconstructed with each FBP, hybrid IR, and DLR. Objective image quality and signal-to-noise ratio of the pancreatic parenchyma, and contrast-to-noise ratio of pancreatic lesions were compared between the 3 reconstruction algorithms. Two radiologists independently assessed the image quality of all images. The diagnostic performance for the detection of pancreatic lesions was compared among the reconstruction algorithms using jackknife alternative free-response receiver operating characteristic analysis. RESULTS: Deep learning-based reconstruction resulted in significantly lower image noise and higher signal-to-noise ratio and contrast-to-noise ratio than hybrid IR and FBP ( P < 0.001). Deep learning-based reconstruction also yielded significantly higher visual scores than hybrid IR and FBP ( P < 0.01). The diagnostic performance of DLR for detecting pancreatic lesions was highest for both readers, although a significant difference was found only between DLR and FBP in one reader ( P = 0.02). CONCLUSIONS: Deep learning-based reconstruction showed improved objective and subjective image quality of pancreatic phase thin-slice CT relative to other reconstruction algorithms and has potential for improving lesion detectability.

Ultrafast lumbar spine MRI protocol using deep learning-based reconstruction: diagnostic equivalence to a conventional protocol.

OBJECTIVE: To evaluate the diagnostic equivalency between an ultrafast (1 min 53 s) lumbar MRI protocol using deep learning-based reconstruction and a conventional lumbar MRI protocol (12 min 31 s). MATERIALS AND METHODS: This study included 58 patients who underwent lumbar MRI using both conventional and ultrafast protocols, including sagittal T1-weighted, T2-weighted, short-TI inversion recovery, and axial T2-weighted sequences. Compared with the conventional protocol, the ultrafast protocol shortened the acquisition time to approximately one-sixth. To compensate for the decreased signal-to-noise ratio caused by the acceleration, deep learning-based reconstruction was applied. Three neuroradiologists graded degenerative changes and analyzed for presence of other pathologies. For the grading of degenerative changes, interprotocol intrareader agreement was assessed using kappa statics. Interchangeability between the two protocols was also tested by calculating the individual equivalence index between the intraprotocol interreader agreement and interprotocol interreader agreement. For the detection of other pathologies, interprotocol intrareader agreement was assessed. RESULTS: For the grading of degenerative changes, the kappa values for interprotocol intrareader agreement of all three readers ranged from 0.707 to 0.804, indicating substantial to almost perfect agreement. Except for foraminal stenosis and disc contour on axial images, the 95% confidence interval of the individual equivalence index was < 5%, indicating the two protocols were interchangeable. For the detection of other pathologies, the interprotocol intrareader agreement rates were > 98% for each individual pathology. CONCLUSIONS: Our proposed ultrafast lumbar spine MRI protocol provided almost equivalent diagnostic results to that of the conventional protocol, except for some degenerative changes.

Simultaneous spatial and temporal regularization in low-dose dynamic contrast-enhanced CT cerebral perfusion studies.

PURPOSE: To apply total generalized variation (TGV) and its combination with low-rank and sparse decomposition (LRSD) (LTGV) to cerebral perfusion studies using low-dose dynamic contrast-enhanced (DCE) CT and to quantitatively evaluate their performances through comparisons with those without any regularizers and those of total variation (TV) and its combination with LRSD (LTV) using simulation and clinical data. METHODS: The simulation study used a realistic digital brain phantom. Low-dose DCE-CT images were reconstructed using the regularizers and primal-dual algorithm. Subsequently, cerebral perfusion parameter (CPP) images were generated from them. Thereafter, their quality was evaluated based on the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Further, the accuracy of CPP estimation was evaluated through a linear regression analysis between the CPP values obtained by the above regularizers and those obtained from the noise-free DCE-CT images. In addition, the mean and standard deviation of the CPP were calculated (region analysis). In the clinical study, low-dose DCE-CT images were generated using normal-dose images acquired from a patient, and CPP images were generated from them similar to that in the simulation study. RESULTS: When using LTV and LTGV, both PSNR and SSIM were higher than those of the other methods with increasing regularization parameter values. The results of the linear regression and region analyses demonstrated that TGV generally exhibited the best performance, followed by LTGV, and finally that of TV was significantly different from those of the other regularizers. Despite an overall consistency between the simulation and clinical results, certain inconsistencies appeared owing to the difference in generating low-dose DCE-CT images. CONCLUSIONS: The results implied that TGV and LTGV were useful in improving the accuracy of CPP estimation using low-dose DCE-CT. This study provides an improved understanding of the performance of regularizers and is expected to aid in the selection of a suitable regularizer for low-dose DCE-CT perfusion studies.

Diagnostic accuracy of MRI for evaluating myometrial invasion in endometrial cancer: a comparison of MUSE-DWI, rFOV-DWI, and DCE-MRI.

OBJECTIVES: To compare the image quality of high-resolution diffusion-weighted imaging (DWI) using multiplexed sensitivity encoding (MUSE) versus reduced field-of-view (rFOV) techniques in endometrial cancer (EC) and to compare the diagnostic performance of these techniques with that of dynamic contrast-enhanced (DCE) MRI for assessing myometrial invasion of EC. METHODS: MUSE-DWI and rFOV-DWI were obtained preoperatively in 58 women with EC. Three radiologists assessed the image quality of MUSE-DWI and rFOV-DWI. For 55 women who underwent DCE-MRI, the same radiologists assessed the superficial and deep myometrial invasion using MUSE-DWI, rFOV-DWI, and DCE-MRI. Qualitative scores were compared using the Wilcoxon signed-rank test. Receiver operating characteristic analysis was performed to compare the diagnostic performance. RESULTS: Artifacts, sharpness, lesion conspicuity, and overall quality were significantly better with MUSE-DWI than with rFOV-DWI (p < 0.05). The area under the curve (AUC) of MUSE-DWI, rFOV-DWI, and DCE-MRI for the assessment of myometrial invasion were not significantly different except for significantly higher AUC of MUSE-DWI than that of DCE-MRI for superficial myometrial invasion (0.76 for MUSE-DWI and 0.64 for DCE-MRI, p = 0.049) and for deep myometrial invasion (0.92 for MUSE-DWI and 0.80 for DCE-MRI, p = 0.022) in one observer, and that of rFOV-DWI for deep myometrial invasion in another observer (0.96 for MUSE-DWI and 0.89 for rFOV-MRI, p = 0.048). CONCLUSION: MUSE-DWI exhibits better image quality than rFOV-DWI. MUSE-DWI and rFOV-DWI shows almost equivalent diagnostic performance compared to DCE-MRI for assessing superficial and deep myometrial invasion in EC although MUSE-DWI may be helpful for some radiologists.

MRI of Borderline Epithelial Ovarian Tumors: Pathologic Correlation and Diagnostic Challenges.

Borderline epithelial ovarian tumors are a distinct pathologic entity characterized by increased epithelial proliferation and nuclear atypia, but without frank stromal invasion. Borderline tumor (BT) is now considered to represent an intermediate phase in the stepwise progression from benign to malignant ovarian epithelial tumor. Since BTs commonly manifest at early stages in women of reproductive age and are associated with a good prognosis, making the correct diagnosis is important in determining whether a patient is a candidate for fertility-sparing surgery. There are six histologic BT subtypes (serous, mucinous, seromucinous, endometrioid, clear cell, and Brenner), and each has different MRI features, reflecting their unique histologic architectures. Radiologists should be aware of the MRI features that can suggest BTs. These features include a hyperintense papillary architecture with hypointense internal branching, which can be observed with serous and seromucinous BTs on T2-weighted images; aggregates of microcysts that have hypointensity on T2-weighted images and reticular enhancement on contrast-enhanced T2-weighted images, which can be seen with mucinous BTs; and moderately high signal intensity on diffusion-weighted images along with relatively high apparent diffusion coefficient values, which can be observed regardless of the histologic subtype. Nevertheless, because the imaging features of BTs overlap with those of many benign lesions (eg, cystadenoma and cystadenofibroma, decidualized endometriosis, and polypoid endometriosis) and malignant tumors (ovarian cancers and metastases), histologic confirmation is required for the final diagnosis. Special emphasis is placed on the MRI features of BTs, pathologic correlation, and the challenges related to diagnosis. ©RSNA, 2022.

Phantom Study of In-Stent Restenosis at High-Spatial-Resolution CT.

Purpose To examine the diagnostic performance of high-spatial-resolution (HSR) CT with 0.25-mm section thickness for evaluating renal artery in-stent restenosis. Materials and Methods A 0.05-mm wire phantom and vessel phantoms with renal stents with in-stent stenotic sections of varying diameters were scanned with both an HSR CT scanner equipped with 160-section multi-detector rows (0.25-mm section thickness) and a conventional CT scanner. The wire phantom was used to analyze modulation transfer function (MTF). With the vessel phantoms, the error rates were calculated as the absolute difference between the measured diameters and true diameters divided by the true diameters at the narrowing sections. For qualitative evaluation, overall image quality and diagnostic accuracy for evaluating stenosis in three stages were assessed by two radiologists. Statistical analyses included the paired t test, Wilcoxon signed-rank test, and McNemar test. Results HSR CT achieved 24.3 line pairs per centimeter ± 0.5 (standard deviation) and 29.1 line pairs per centimeter ± 0.4 at 10% and 2% MTF, respectively; and conventional CT was 12.5 line pairs per centimeter ± 0.1 and 14.3 line pairs per centimeter ± 0.1 at 10% and 2% MTF, respectively. The mean error rate of the measured diameter at HSR CT (8.0% ± 5.8) was significantly lower than that at at conventional CT (16.9% ± 9.3; P < .001). Image quality at HSR CT was significantly better than that at conventional CT (P < .001), but HSR CT was not significantly superior to conventional CT in terms of diagnostic accuracy. Conclusion Compared with conventional CT, high-spatial-resolution CT achieved spatial resolutions of up to 29 line pairs per centimeter at 2% modulation transfer function and yielded improved measurement accuracy for the evaluation of in-stent restenosis in a phantom study of renal artery stents. Published under a CC BY 4.0 license.

Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.

OBJECTIVES: To investigate the diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction (IR) algorithm for the detection of hypervascular liver lesions. METHODS: Thirty liver phantoms with or without simulated hypervascular lesions were scanned with a 320-slice CT scanner with control-dose (40 mAs) and reduced-dose (30 and 20 mAs) settings. Control-dose images were reconstructed with filtered back projection (FBP), and reduced-dose images were reconstructed with FBP and a hybrid IR algorithm. Objective image noise and the lesion to liver contrast-to-noise ratio (CNR) were evaluated quantitatively. Images were interpreted independently by 2 blinded radiologists, and jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. RESULTS: Hybrid IR images with reduced-dose settings (both 30 and 20 mAs) yielded significantly lower objective image noise and higher CNR than control-dose FBP images (P < .05). However, hybrid IR images with reduced-dose settings had lower JAFROC1 figure of merit than control-dose FBP images, although only the difference between 20 mAs images and control-dose FBP images was significant for both readers (P < .01). CONCLUSIONS: An aggressive reduction of the radiation dose would impair the detectability of hypervascular liver lesions, although objective image noise and CNR would be preserved by a hybrid IR algorithm. KEY POINTS: • A half-dose scan with a hybrid iterative reconstruction preserves objective image quality. • A hybrid iterative reconstruction algorithm does not improve diagnostic performance. • An aggressive dose reduction would impair the detectability of low-contrast lesions.

Preoperative staging of endometrial cancer using reduced field-of-view diffusion-weighted imaging: a preliminary study.

OBJECTIVES: To compare the image quality and diagnostic performance of reduced field-of-view (rFOV) versus conventional full field-of-view (fFOV) diffusion-weighted (DW) imaging of endometrial cancer. METHODS: Fifty women with endometrial cancer underwent preoperative rFOV and fFOV DW imaging. Two radiologists compared the image qualities of both techniques, and five radiologists assessed superficial and deep myometrial invasion using both techniques. The statistical analysis included the Wilcoxon signed-rank test and paired t-test for comparisons of image quality and mean diagnostic values. RESULTS: Distortion, tumour delineation, and overall image quality were significantly better with rFOV DW imaging, compared to fFOV DW imaging (P < 0.05); however, the former was inferior in noise (P < 0.05). Regarding superficial invasion, the mean accuracies of the techniques did not differ statistically (rFOV, 58.0% versus fFOV, 56.0%; P = 0.30). Regarding deep myometrial invasion, rFOV DW imaging yielded significantly better mean accuracy, specificity, and positive predictive values (88.4%, 97.8%, and 91.7%, respectively), compared with fFOV DW imaging (84.8%, 94.1%, and 77.4%, respectively; P = 0.009, 0.005, and 0.011, respectively). CONCLUSIONS: Compared with fFOV DW imaging, rFOV DW imaging yielded less distortion, improved image quality and, consequently, better diagnostic performance for deep myometrial invasion of endometrial cancer. KEY POINTS: • rFOV DWI yields better assessment of deep myometrial invasion in endometrial cancer. • rFOV DWI could not sufficiently evaluate superficial invasion in endometrial cancer. • Distortion, tumour delineation, and overall image quality were improved with rFOV DWI.

The Optimal Body Size Index with Which to Determine Iodine Dose for Hepatic Dynamic CT: A Prospective Multicenter Study.

PURPOSE: To identify the body size parameter that exhibits the best correlation with aortic and hepatic enhancement at hepatic dynamic computed tomography (CT) in a large patient population enrolled in a multicenter study. MATERIALS AND METHODS: This prospective study was approved by the ethics committee of each of the 31 participating institutions where 1342 patients were enrolled between April 2012 and September 2013. All patients provided either written or oral informed consent. All patients underwent hepatic dynamic CT, which included preenhanced, hepatic arterial phase (HAP), and portal venous phase (PVP) scanning, performed with the routine scanning protocol of each institution. Changes in CT number (in Hounsfield units) per gram of iodine in the aorta (eA/I) and liver (eL/I) during HAP and PVP scanning were recorded for each patient. Hierarchical multivariate linear regression analysis was performed in which the outcome variable was either eA/I or eL/I; the independent variables were age, sex, one body size parameter (height, body weight, body mass index, lean body weight [LBW], or body surface area), and liver function (aspartate aminotransferase, albumin, and total bilirubin levels). A two-level hierarchical model in which patients were level 1 and the institution was level 2 was used. RESULTS: Hierarchical multivariate linear regression analysis revealed that in the population not stratified by sex, body size was significantly correlated with eA/I and eL/I (P < .001) and that LBW exhibited the strongest correlation with eA/I and eL/I (r = -0.561 and r = -0.601, respectively). Sex-stratified analysis showed that LBW was more strongly correlated with eA/I and eL/I in women (r = -0.779 and r = -0.948, respectively) than in men (r = -0.500 and r = -0.494, respectively) or in the nonstratified total population. CONCLUSION: Among body size parameters, LBW exhibited the strongest correlation with aortic and hepatic enhancement, especially in women.

Low-Dose Pelvic Computed Tomography Using Adaptive Iterative Dose Reduction 3-Dimensional Algorithm: A Phantom Study.

OBJECTIVE: To evaluate the image quality and radiation dose reduction in pelvic computed tomography (CT) achieved with an adaptive iterative dose reduction 3-dimensional (AIDR 3D) algorithm using a phantom model. METHODS: Two phantoms were scanned using a 320-detector row CT scanner with 8 tube current levels, and the images were reconstructed with a standard filtered back projection (FBP) algorithm and with an AIDR 3D algorithm. RESULTS: Compared with FBP, AIDR 3D reduced image noise and improved contrast-to-noise ratios. The diagnostic performance for detection of low-contrast targets of AIDR 3D images obtained with 100 mA at 120 kVp was almost as good as that of the FBP images obtained with 200 mA. CONCLUSIONS: The AIDR 3D algorithm substantially reduced image noise and improved the image quality of pelvic CT images compared with those obtained with the FBP algorithm and can thus be considered a promising technique for low-dose pelvic CT examinations.

Correlation between apparent diffusion coefficients on diffusion-weighted MRI and standardized uptake value on FDG-PET/CT in pancreatic adenocarcinoma.

BACKGROUND: Diffusion-weighted magnetic resonance imaging (DW-MRI) and 2-deoxy-2-[18F]fluoro-D-glucose-positron emission tomography/computed tomography (PET/CT) is increasingly recognized as important for assessing tumor malignancy in oncology. Apparent diffusion coefficient (ADC) and standardized uptake value (SUV) are negatively correlated in some types of cancer based on tumor aggressiveness. PURPOSE: To evaluate relationships between ADC of magnetic resonance imaging and SUV of PET/CT in pancreatic adenocarcinomas. MATERIAL AND METHODS: Twenty-nine patients histopathologically diagnosed with pancreatic adenocarcinomas were evaluated. ADC maps were generated from 3 T-MRI using b values (b = 0, 800 s/mm(2)). PET/CT was performed 60 min after intravenous injection of FDG (3.7 MBq/kg). The margins of tumors on DW-MRI and PET/CT were assessed to measure ADC and SUV of tumor appropriately. For tumors considered well-marginated, minimal and mean ADC as well as maximal and mean SUV were measured. The correlation of ADC and SUV were statistically evaluated and survival period stratified on ADC and SUV also evaluated. RESULTS: Twenty-two tumors on DW-MRI and 25 on PET/CT were deemed well-marginated. Minimal ADC was significantly and negatively correlated with maximal and mean SUV (r = -0.61, P = 0.0040; r = -0.66, P = 0.0015), and mean ADC also showed significantly and negatively correlation with maximal and mean SUV (r = -0.50, P = 0.024; r = -0.54, P = 0.012). There was no significant difference on overall survival stratified on ADC and SUV. CONCLUSION: ADC and SUV were significantly correlated in pancreatic adenocarcinomas, although no significant findings were observed in overall survival.

Hepatic and pancreatic extracellular volume fraction analysis using contrast-enhanced CT in patients with diabetes mellitus and pre-diabetes.

PURPOSE: Liver and pancreatic fibrosis is associated with diabetes mellitus (DM), and liver fibrosis is associated with pancreatic fibrosis. This study aimed to investigate the relationship between the hepatic and pancreatic extracellular volume fractions (fECVs), which correlate with tissue fibrosis, and their relationships with DM and pre-DM (pDM). MATERIAL AND METHODS: We included 100 consecutive patients with known or suspected liver and/or pancreatic diseases who underwent contrast-enhanced CT. Patients were classified as nondiabetes, pDM, and DM with hemoglobin A1c (HbA1c) levels of < 5.7%, 5.7%-6.5%, and ≥ 6.5% or fasting plasma glucose (FPG) levels of < 100, 100-125 mg/dL, and ≥ 126 mg/dL, respectively. Subtraction images between unenhanced and equilibrium-phase images were prepared. The liver and the pancreas were automatically extracted using a high-speed, three-dimensional image analysis system, and their respective mean CT values were calculated. The enhancement degree of the aorta (Δaorta) was measured. fECV was calculated using the following equation: fECV = (100 - hematocrit) * Δliver or pancreas/Δaorta. Differences were investigated in hepatic and pancreatic fECVs among the three groups, and the correlation between each two in hepatic fECV, pancreatic fECV, and HbA1c was determined. RESULTS: The pancreatic fECV, which was positively correlated with the hepatic fECV and HbA1c (r = 0.51, P < 0.001, and r = 0.51, P < 0.001, respectively), significantly differed among the three groups (P < 0.001) and was significantly greater in DM than in pDM or nondiabetes and in pDM with nondiabetes (P < 0.001). Hepatic fECV was significantly greater in DM than in nondiabetes (P < 0.05). CONCLUSION: The pancreatic fECV and pDM/DM are closely related.

Effect of Deep Learning Reconstruction on Respiratory-triggered T2-weighted MR Imaging of the Liver: A Comparison between the Single-shot Fast Spin-echo and Fast Spin-echo Sequences.

PURPOSE: To compare the effects of deep learning reconstruction (DLR) on respiratory-triggered T2-weighted MRI of the liver between single-shot fast spin-echo (SSFSE) and fast spin-echo (FSE) sequences. METHODS: Respiratory-triggered fat-suppressed liver T2-weighted MRI was obtained with the FSE and SSFSE sequences at the same spatial resolution in 55 patients. Conventional reconstruction (CR) and DLR were applied to each sequence, and the SNR and liver-to-lesion contrast were measured on FSE-CR, FSE-DLR, SSFSE-CR, and SSFSE-DLR images. Image quality was independently assessed by three radiologists. The results of the qualitative and quantitative analyses were compared among the four types of images using repeated-measures analysis of variance or Friedman's test for normally and non-normally distributed data, respectively, and a visual grading characteristics (VGC) analysis was performed to evaluate the image quality improvement by DLR on the FSE and SSFSE sequences. RESULTS: The liver SNR was lowest on SSFSE-CR and highest on FSE-DLR and SSFSE-DLR (P < 0.01). The liver-to-lesion contrast did not differ significantly among the four types of images. Qualitatively, noise scores were worst on SSFSE-CR but best on SSFSE-DLR because DLR significantly reduced noise (P < 0.01). In contrast, artifact scores were worst both on FSE-CR and FSE-DLR (P < 0.01) because DLR did not reduce the artifacts. Lesion conspicuity was significantly improved by DLR compared with CR in the SSFSE (P < 0.01) but not in FSE sequences for all readers. Overall image quality was significantly improved by DLR compared with CR for all readers in the SSFSE (P < 0.01) but only one reader in the FSE (P < 0.01). The mean area under the VGC curve values for the FSE-DLR and SSFSE-DLR sequences were 0.65 and 0.94, respectively. CONCLUSION: In liver T2-weighted MRI, DLR produced more marked improvements in image quality in SSFSE than in FSE.

Photon-counting CT: technical features and clinical impact on abdominal imaging.

Photon-counting CT has a completely different detector mechanism than conventional energy-integrating CT. In the photon-counting detector, X-rays are directly converted into electrons and received as electrical signals. Photon-counting CT provides virtual monochromatic images with a high contrast-to-noise ratio for abdominal CT imaging and may improve the ability to visualize small or low-contrast lesions. In addition, photon-counting CT may offer the possibility of reducing radiation dose. This review provides an overview of the actual clinical operation of photon-counting CT and its diagnostic utility in abdominal imaging. We also describe the clinical implications of photon-counting CT including imaging of hepatocellular carcinoma, liver metastases, hepatic steatosis, pancreatic cancer, intraductal mucinous neoplasm of the pancreas, and thrombus.

Endometrial cancer: preoperative staging using three-dimensional T2-weighted turbo spin-echo and diffusion-weighted MR imaging at 3.0 T: a prospective comparative study.

OBJECTIVES: To prospectively assess the efficacy of 3-T magnetic resonance (MR) imaging using the three-dimensional turbo spin-echo T2-weighted and diffusion-weighted technique (3D-TSE/DW) compared with that of conventional imaging using the two-dimensional turbo spin-echo T2-weighted and dynamic contrast-enhanced technique (2D-TSE/DCE) for the preoperative staging of endometrial cancer, with pathological analysis as the reference standard. METHODS: Seventy-one women with endometrial cancer underwent MR imaging using 3D-TSE/DW (b = 1,000 s/mm(2)) and 2D-TSE/DCE. Two radiologists independently assessed the two imaging sets. Accuracy, sensitivity, and specificity for staging were analysed with the McNemar test; the areas under the receiver operating characteristic curve (Az) were compared with a univariate z-score test. RESULTS: The results for assessing deep myometrial invasion, accuracy, sensitivity, specificity and Az, respectively, were as follows: 3D-TSE/DW-observer 1, 87 %, 95 %, 85 % and 0.96; observer 2, 92 %, 84 %, 94 % and 0.95; 2D-TSE/DCE-observer 1, 80 %, 79 %, 81 % and 0.89; observer 2, 86 %, 84 %, 87 % and 0.86. Most of the values were higher with 3D-TSE/DW without significant differences (P > 0.12). For assessing cervical stromal invasion, there were no significant differences in those values for both observers (P > 0.6). CONCLUSIONS: Accuracy of 3D-TSE/DW was at least equivalent to that of the conventional technique for the preoperative assessment of endometrial cancer. KEY POINTS: • New techniques in MR imaging help assess patients with endometrial cancer. • A 3D T2-weighted TSE sequence seems equally as accurate as conventional techniques. • Three-dimensional TSE/DW imaging does not require intravenous contrast material and is relatively quick. • Tumour extent of endometrial cancer can be clearly shown on diffusion-weighted images. • Junctional zone can be visualised well on 3D-TSE T2-weighted images.

High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques.

PURPOSE: To compare objective and subjective image quality, lesion conspicuity, and apparent diffusion coefficient (ADC) of high-resolution multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) with conventional DWI (c-DWI) and reduced FOV DWI (rFOV-DWI) in prostate MRI. METHODS: Forty-seven patients who underwent prostate MRI, including c-DWI, rFOV-DWI, and MUSE-DWI, were retrospectively evaluated. SNR and ADC of normal prostate tissue and contrast-to-noise ratio (CNR) and ADC of prostate cancer (PCa) were measured and compared between the three sequences. Image quality and lesion conspicuity were independently graded by two radiologists using a 5-point scale and compared between the three sequences. RESULTS: The SNR of normal prostate tissue was significantly higher with rFOV-DWI than with the other two DWI techniques (P ≤ 0.01). The CNR of the PCa was significantly higher with rFOV-DWI than with MUSE-DWI (P < 0.05). The ADC of normal prostate tissue measured by rFOV-DWI was lower than that measured by MUSE-DWI and c-DWI (P < 0.01), while there was no difference in the ADC of cancers. In the qualitative analysis, MUSE-DWI showed significantly higher scores than rFOV-DWI and c-DWI for visibility of anatomy and overall image quality in both readers, and significantly higher scores for distortion in one of the two readers (P < 0.001). There was no difference in lesion conspicuity between the three sequences. CONCLUSION: High-resolution MUSE-DWI showed higher image quality and reduced distortion compared to c-DWI, while maintaining a wide FOV and similar ADC quantification, although no difference in lesion conspicuity was observed.

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance.

OBJECTIVE: The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) imaging of the rectum. MATERIALS AND METHODS: This prospective study included 34 patients who underwent magnetic resonance imaging (MRI) for initial staging or restaging of rectal tumors. The following 4 types of oblique axial PROPELLER images perpendicular to the tumor were obtained: a standard 3-mm slice thickness with conventional reconstruction (3-CR) and DLR (3-DLR), and 1.2-mm slice thickness with CR (1.2-CR) and DLR (1.2-DLR). Three radiologists independently evaluated the image quality and tumor extent by using a 5-point scoring system. Diagnostic accuracy was evaluated in 22 patients with rectal cancer who underwent surgery after MRI without additional neoadjuvant therapy (median interval between MRI and surgery, 22 days). The signal-to-noise ratio and tissue contrast were measured on the 4 types of PROPELLER imaging. RESULTS: 1.2-DLR imaging showed the best sharpness, overall image quality, and rectal and lesion conspicuity for all readers (P < 0.01). Of the assigned scores for tumor extent, extramural venous invasion (EMVI) scores showed moderate agreement across the 4 types of PROPELLER sequences in all readers (intraclass correlation coefficient, 0.60-0.71). Compared with 3-CR imaging, the number of cases with MRI-detected extramural tumor spread was significantly higher with 1.2-DLR imaging (19.0 ± 2.9 vs 23.3 ± 0.9, P = 0.03), and the number of cases with MRI-detected EMVI was significantly increased with 1.2-CR, 3-DLR, and 1.2-DLR imaging (8.0 ± 0.0 vs 9.7 ± 0.5, 11.0 ± 2.2, and 12.3 ± 1.7, respectively; P = 0.02). For the diagnosis of histopathologic extramural tumor spread, 3-CR and 1.2-CR had significantly higher specificity than 3-DLR and 1.2-DLR imaging (0.75 and 0.78 vs 0.64 and 0.58, respectively; P = 0.02), and only 1.2-CR had significantly higher accuracy than 3-CR imaging (0.83 vs 0.79, P = 0.01). The accuracy of MRI-detected EMVI with reference to pathological EMVI was significantly lower for 3-CR and 3-DLR compared with 1.2-CR (0.77 and 0.74 vs 0.85, respectively; P < 0.01), and was not significantly different between 1.2-CR and 1.2-DLR (0.85 vs 0.80). Using any pathological venous invasion as the reference standard, the accuracy of MRI-detected EMVI was significantly the highest with 1.2-DLR, followed by 1.2-CR, 3-CR, and 3-DLR (0.71 vs 0.67 vs 0.59 vs 0.56, respectively; P < 0.01). The signal-to-noise ratio was significantly highest with 3-DLR imaging (P < 0.05). There were no significant differences in tumor-to-muscle contrast between the 4 types of PROPELLER imaging. CONCLUSIONS: Ultra-high-resolution PROPELLER T2-weighted imaging of the rectum combined with DLR improved image quality, increased the number of cases with MRI-detected extramural tumor spread and EMVI, but did not improve diagnostic accuracy with respect to pathology in rectal cancer, possibly because of false-positive MRI findings or false-negative pathologic findings.

Diagnostic accuracy of C-arm CT during selective transcatheter angiography for hepatocellular carcinoma: comparison with intravenous contrast-enhanced, biphasic, dynamic MDCT.

PURPOSE: This study was aimed to compare the accuracy, sensitivity, and positive predictive value of C-arm CT (CACT) during selective transcatheter angiography with those of multidetector CT (MDCT) in the detection of hepatocellular carcinoma (HCC). MATERIAL AND METHODS: In this prospective study, 30 patients (mean age, 73 years) with unresectable HCC were examined with CACT before chemoembolisation. Images of a combination of CACT during arterial portography (CACTAP) and dual-phase CACT during hepatic arteriography (CACTHA) was obtained and images of intravenous contrast-enhanced, biphasic, dynamic, MDCT was also obtained beforehand. Three blinded observers independently reviewed CACT and MDCT. Diagnostic accuracy was evaluated by the alternative free-response receiver operating characteristic (AFROC) method. Sensitivities and positive predictive values (PPV) were analyzed with the paired t-test. RESULTS: In the mean area under the AFROC curve (Az), there was no significant difference between MDCT and CACT (MDCT, mean Az value, 0.83; CACT, 0.85, respectively) (P = 0.32). There was also no significant difference between the two techniques in sensitivity (MDCT, mean 0.65; CACT, 0.60) and PPV (MDCT, mean 0.98; CACT, 0.97) (P = 0.40, P = 0.68, respectively). CONCLUSION: The diagnostic accuracy of CACT was equivalent to that of biphasic CT in the diagnosis of HCC. KEY POINTS: C-arm CT helps detection of hepatocellular carcinoma (HCC) during interventional (TACE) treatment. C-arm CT for HCC seemed just as accurate as biphasic CT. TACE can be performed with greater confidence using C-arm CT.

Hypervascular hepatocellular carcinomas: detection with gadoxetate disodium-enhanced MR imaging and multiphasic multidetector CT.

OBJECTIVES: To retrospectively compare the accuracy of detection of hypervascular hepatocellular carcinoma (HCC) by multiphasic multidetector CT and by gadoxetate disodium-enhanced MR imaging. METHODS: After ethical approval, we analysed a total of 73 hypervascular HCC lesions from 31 patients suspected of having HCC, who underwent both gadoxetate disodium-enhanced MR imaging and multiphasic multidetector CT. Five blinded observers independently reviewed CT images, as well as dynamic MR images alone and combined with hepatobiliary phase MR images. Diagnostic accuracy (Az values), sensitivities and positive predictive values were compared by using the Scheffe post hoc test. RESULTS: The mean Az value for dynamic and hepatobiliary phase MR combined (0.81) or dynamic MR images alone (0.78) was significantly higher than that for CT images (0.67, P < 0.001, 0.005, respectively). The mean sensitivity of the combined MR images (0.67) was significantly higher than that of dynamic MR alone (0.52, P < 0.05) or CT images (0.44, P < 0.05). The mean positive predictive values were 0.96, 0.95 and 0.94, for CT, dynamic MR alone and combined MR images, respectively. CONCLUSIONS: Compared with multiphasic multidetector CT, gadoxetate disodium-enhanced MR imaging combining dynamic and hepatobiliary phase images results in significantly improved sensitivity and diagnostic accuracy for detection of hypervascular HCC. KEY POINTS: Gadoxetate disodium is a new liver-specific MR imaging contrast agent. Gadoxetate disodium-enhanced MRI helps the assessment of patients with liver disease. It showed high diagnostic accuracy for the detection of hepatocellular carcinoma.