Discrepancy in the Location of Prostate Cancer Indicated on Biparametric Magnetic Resonance Imaging and Pathologically Diagnosed Using Surgical Specimens.

Accurate diagnosis of the localization of prostate cancer (PCa) on magnetic resonance imaging (MRI) remains a challenge. We aimed to assess discrepancy between the location of PCa pathologically diagnosed using surgical specimens and lesions indicated as possible PCa by the Prostate Imaging Reporting and Data System on MRI. The primary endpoint was the concordance rate between the site of probable clinically significant PCa (csPCa) identified using biparametric MRI (bpMRI) and location of PCa in the surgical specimen obtained using robot-assisted total prostatectomy. Among 85 lesions identified in 30 patients; 42 (49.4%) were identified as possible PCa on MRI. The 85 PCa lesions were divided into positive and negative groups based on the bpMRI results. None of the patients had missed csPCa. Although the diagnostic accuracy of bpMRI was relatively high for PCas located in the middle of the prostate (p = 0.029), it was relatively low for PCa located at the base of the prostate, all of which were csPCas. Although current modalities can accurately diagnose PCa, the possibility that PCa is present with multiple lesions in the prostate should be considered, even if MRI does not detect PCa.

Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images.

PURPOSE: To compare the diagnostic performance of 40 keV and 70 keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer. METHODS: This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11 years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70 keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40 keV and 70 keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations. RESULTS: Overall, 137 patients (median age, 71 years; interquartile range, 63-78 years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40 keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70 keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs. CONCLUSIONS: The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70 keV VMIs, along with higher reader confidence.

Radiomics Features Using Dual-energy CT for Lymph Nodes After Preoperative Chemotherapy for Esophageal Cancer.

BACKGROUND/AIM: Progress has been made in a triplet preoperative chemotherapy regimen for advanced esophageal cancer. We performed a preliminary investigation of the radiomics features of pathological lymph node metastasis after neoadjuvant chemotherapy using dual-energy computed tomography (DECT). PATIENTS AND METHODS: From January to December 2022, 36 lymph nodes from 10 patients with advanced esophageal cancer who underwent contrast-enhanced DECT after neoadjuvant chemotherapy and radical surgery in our department were studied. Radiomics features were extracted from iodine-based material decomposition images at the portal venous phase constructed by DECT using MATLAB analysis software. Receiver operating characteristic (ROC) analysis and cut-off values were determined for the presence or absence of pathological metastasis. RESULTS: ROC for the short axis of the pathologically positive lymph nodes showed an AUC of 0.713. Long run emphasis (LRE) within gray-level run-length matrix (GLRLM) was confirmed with a high AUC of 0.812. Sensitivity and specificity for lymph nodes with a short axis >10 mm were 0.222 and 1, respectively. Sensitivity and specificity for LRE within GLRLM were 0.722 and 0.833, respectively. Sensitivity and specificity for small zone emphasis (SZE) within gray-level size zone matrix (GLSZM) were 0.889 and 0.667, and zone percentage (ZP) values within GLSZM were 0.722 and 0.778, respectively. Discrimination of existing metastases using radiomics showed significantly higher sensitivity compared to lymph node short axis >10 mm (odds ratios of LRE, SZE, and ZP: 9.1, 28, and 9.1, respectively). CONCLUSION: Evaluation of radiomics analysis using DECT may enable a more detailed evaluation of lymph node metastasis after neoadjuvant chemotherapy.

Appropriate pancreatic phase image acquisition by free-breathing dynamic contrast-enhanced pancreatic MRI using stack-of-stars radial sampling and Compressed SENSE.

PURPOSE: To evaluate the feasibility of a free-breathing sequence (4D FreeBreathing) combined with Compressed SENSE in dynamic contrast-enhanced pancreatic MRI and compare it with a breath-holding sequence (eTHRIVE). METHOD: Patients who underwent pancreatic MRI, either eTHRIVE or 4D FreeBreathing, from April 2022 to November 2023 were included in this retrospective study. Two radiologists, who were unaware of the scan sequence, independently and randomly reviewed the images at the precontrast, pancreatic, portal venous, and equilibrium phases and assigned confidence scores for motion and streaking artifacts, pancreatic sharpness, and overall image quality using a 5-point scale. Furthermore, the radiologists assessed the appropriateness of the scan timing of the pancreatic phase. Mann-Whitney U and Fisher's exact tests were conducted to compare the confidence scores and adequacy of the pancreatic phase scan timing between eTHRIVE and 4D FreeBreathing. RESULTS: Overall, 48 patients (median age, 71 years; interquartile range, 64-77 years; 24 women) were included. Among them, 20 patients (42%) were scanned using 4D FreeBreathing. The 4D FreeBreathing showed moderate streaking artifact but improved motion artifact (P <.001-.17) at all phases. Pancreatic sharpness and overall image quality were almost comparable between two sequences (P = .17-.96). All 20 examinations in 4D FreeBreathing showed appropriate pancreatic phase images, but only 16 (57%; P <.001 for reviewer 1) and 18 (64%; P = .003 for reviewer 2) examinations showed it in eTHRIVE. CONCLUSION: The use of 4D FreeBreathing combined with Compressed SENSE was feasible in pancreatic MRI and provided appropriate pancreatic phase images in all examinations.

Delayed diagnosis of Lemierre's syndrome in a patient with severe coronavirus disease 2019: importance of comprehensive oral and neck examination - a case report.

BACKGROUND: Given the widespread prevalence of the coronavirus disease 2019 (COVID-19), oral and neck examinations tend to be avoided in patients with suspected or confirmed COVID-19. This might delay the diagnosis of conditions such as Lemierre's syndrome, which involves symptoms resembling COVID-19-related throat manifestations. CASE PRESENTATION: A 24-year-old man without any underlying conditions was diagnosed with COVID-19 7 days before presentation. He was admitted to another hospital 1 day before presentation with severe COVID-19 and suspected bacterial pneumonia; accordingly, he was started on treatment with remdesivir and meropenem. Owing to bacteremic complications, the patient was transferred to our hospital for intensive care. On the sixth day, the patient experienced hemoptysis; further, a computed tomography (CT) scan revealed new pulmonary artery pseudoaneurysms. Successful embolization was performed to achieve hemostasis. In blood cultures conducted at the previous hospital, Fusobacterium nucleatum was isolated, suggesting a cervical origin of the infection. A neck CT scan confirmed a peritonsillar abscess and left internal jugular vein thrombus; accordingly, he was diagnosed with Lemierre's syndrome. The treatment was switched to ampicillin/sulbactam, based on the drug susceptibility results. After 6 weeks of treatment, the patient completely recovered without complications. CONCLUSION: This case highlights the significance of thorough oral and neck examinations in patients with suspected or diagnosed COVID-19 for the detection of throat and neck symptoms caused by other conditions.

Diagnostic ability of diffusion-weighted imaging using echo planar imaging with compressed SENSE (EPICS) for differentiating hepatic hemangioma and liver metastasis.

PURPOSE: To assess the diagnostic abilities of diffusion-weighted imaging (DWI) with parallel imaging (PI-DWI) and that with Compressed SENSE (EPICS-DWI) for differentiating hepatic hemangiomas (HHs) and liver metastases (LMs). METHOD: This prospective study included 30 participants with HH and/or LM who underwent PI-DWI and EPICS-DWI. Two radiologists assessed the DWI images and assigned confidence scores for hepatic lesions conspicuity using 4-point scale. One of the radiologists additionally calculated the contrast-to-noise ratio (CNR) and measured ADC value of the hepatic lesions. The conspicuity, CNR, and ADC values were compared between the two sequences. A receiver operating characteristic (ROC) analysis was performed to assess the diagnostic abilities of the two sequences for differentiating HHs and LMs. RESULTS: The conspicuity of LMs was better in EPICS-DWI than in PI-DWI (P < .05 in both radiologists). The CNR of LMs was higher in EPICS-DWI than in PI-DWI (P = .008). No difference was found in the CNR of HHs (P = .52), ADC values for HHs (P = .79), and LMs (P = .29) between the two sequences. To differentiate between HHs and LMs, the cutoff ADC values were 1.38 × 10-3 mm2/s in PI-DWI and 1.37 × 10-3 mm2/s in EPICS-DWI. The area under the ROC curve (P = .86), sensitivity (P > .99), and specificity (P > .99) did not vary. CONCLUSIONS: The LMs were more visible in EPICS-DWI than in PI-DWI. However, the cutoff ADC values and diagnostic abilities for differentiating HHs and LMs were almost comparable between the two sequences.

Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction.

PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms. METHOD: A total of 56 patients who underwent 80-kVp pancreatic protocol CT for pancreatic disease evaluation from January 2022 to July 2022 were included in this retrospective study. Among them, 20 PDACs were observed. The CT raw data were reconstructed using 40% adaptive statistical IR-Veo (hybrid-IR group) and DLIR at medium- and high-strength levels (DLIR-M and DLIR-H groups, respectively). The CT attenuation of the abdominal aorta, pancreas, and PDAC (if present) at the pancreatic phase and those of the portal vein and liver at the portal venous phase; background noise; signal-to-noise ratio (SNR) of these anatomical structures; and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. The confidence scores for the image noise, overall image quality, and visibility of PDAC were qualitatively assigned using a five-point scale. Quantitative and qualitative parameters were compared among the three groups using Friedman test. RESULTS: The CT attenuation of all anatomical structures were comparable among the three groups (P = .26-.86), except that of the pancreas (P = .001). Background noise was lower (P <.001) and SNRs (P <.001) and tumor-to-pancreas CNR (P <.001) were higher in the DLIR-H group than those in the other two groups. The image noise, overall image quality, and visibility of PDAC were better in the DLIR-H group than in the other two groups (P <.001-.003). CONCLUSION: In 80-kVp pancreatic CT protocol, DLIR at a high-strength level improved image quality and visibility of PDAC.

Comparison of image quality, arterial depiction, and radiation dose between two rapid kVp-switching dual-energy CT scanners in CT angiography at 40-keV.

PURPOSE: To compare the quantitative parameters and qualitative image quality of dual-energy CT angiography (CTA) between two rapid kVp-switching dual-energy CT scanners. MATERIALS AND METHODS: Between May 2021 and March 2022, 79 participants underwent whole-body CTA using either Discovery CT750 HD (Group A, n = 38) or Revolution CT Apex (Group B, n = 41). All data were reconstructed at 40-keV and with adaptive statistical iterative reconstruction-Veo of 40%. The two groups were compared in terms of CT numbers of the thoracic and abdominal aorta, and the iliac artery, background noise, signal-to-noise ratio (SNR) of the artery, CT dose-index volume (CTDIvol), and qualitative scores for image noise, sharpness, diagnostic acceptability, and arterial depictions. RESULTS: The median CT number of the abdominal aorta (p = 0.04) and SNR of the thoracic aorta (p = 0.02) were higher in Group B than in Group A, while no difference was observed in the other CT numbers and SNRs of the artery (p = 0.09-0.23). The background noises at the thoracic (p = 0.11), abdominal (p = 0.85), and pelvic (p = 0.85) regions were comparable between the two groups. CTDIvol was lower in Group B than in Group A (p = 0.006). All qualitative scores were higher in Group B than in Group A (p < 0.001-0.04). The arterial depictions were nearly identical in both two groups (p = 0.005-1.0). CONCLUSION: In dual-energy CTA at 40-keV, Revolution CT Apex improved qualitative image quality and reduced radiation dose.

Determination of arterial invasion in pancreatic ductal adenocarcinoma: what is the best diagnostic criterion on CT?

OBJECTIVES: To investigate the diagnostic performance and interobserver variability in the determination of arterial invasion in pancreatic ductal adenocarcinoma (PDAC) and determine the best CT imaging criterion. METHODS: We retrospectively evaluated 128 patients with PDAC (73 men and 55 women) who underwent preoperative contrast-enhanced CT. Five board-certified radiologists (expert) and four fellows (non-expert]) independently assessed the arterial invasion (celiac, superior mesenteric, splenic, and common hepatic arteries) using a 6-point score: 1, no tumor contact; 2, hazy attenuation ≤ 180°; 3, hazy attenuation > 180°; 4, solid soft tissue contact ≤ 180°; 5, solid soft tissue contact > 180°; and 6, contour irregularity. ROC analysis was performed to evaluate the diagnostic performance and determine the best diagnostic criterion for arterial invasion, with pathological or surgical findings as references. Interobserver variability was assessed using Fleiss's ĸ statistics. RESULTS: Among the 128 patients, 35.2% (n = 45/128) received neoadjuvant treatment (NTx). Solid soft tissue contact ≤ 180° was the best diagnostic criterion for arterial invasion as defined by the Youden Index both in patients who did and did not receive NTx (sensitivity, 100% vs. 100%; specificity, 90% vs. 93%; and AUC, 0.96 vs. 0.98, respectively). Interobserver variability among the non-expert was not inferior to that among the expert (ĸ = 0.61 vs 0.61; p = .39 and ĸ = 0.59 vs 0.51; p < .001 in patients treated with and without NTx, respectively). CONCLUSIONS: Solid soft tissue contact ≤ 180° was the best diagnostic criterion for the determination of arterial invasion in PDAC. Considerable interobserver variability was seen among the radiologists. KEY POINTS: • Solid soft tissue contact ≤ 180° was the best diagnostic criterion for the determination of arterial invasion in pancreatic ductal adenocarcinoma. • Interobserver agreement among non-expert radiologists was almost comparable to that among expert radiologists.

Non-invasive regional cerebral blood flow quantification in the 123I-IMP autoradiography using artificial neural network.

PURPOSE: Regional cerebral blood flow (rCBF) quantification using 123I-N-isopropyl-p-iodoamphetamine (123I-IMP) requires an invasive, one-time-only arterial blood sampling for measuring the 123I-IMP arterial blood radioactivity concentration (Ca10). The purpose of this study was to estimate Ca10 by machine learning (ML) using artificial neural network (ANN) regression analysis and consequently calculating rCBF and cerebral vascular reactivity (CVR) in the dual-table autoradiography (DTARG) method. MATERIALS AND METHODS: This retrospective study included 294 patients who underwent rCBF measurements through the 123I-IMP DTARG. In the ML, the objective variable was defined by the measured Ca10, whereas the explanatory variables included 28 numeric parameters, such as patient characteristic values, total injection 123I-IMP radiation dose, cross-calibration factor, and the distribution of 123I-IMP count in the first scan. ML was performed with training (n = 235) and testing (n = 59) sets. Ca10 was estimated in testing set by our proposing model. Alternatively, the estimated Ca10 was also calculated via the conventional method. Subsequently, rCBF and CVR were calculated using estimated Ca10. Pearson's correlation coefficient (r-value) for the goodness of fit and the Bland-Altman analysis for assessing the potential agreement and bias were performed between the measured and estimated values. RESULTS: The r-value of Ca10 estimated by our proposed model was higher compared with the conventional method (0.81 and 0.66, respectively). In the Bland-Altman analysis, mean differences of 4.7 (95% limits of agreement (LoA): -18-27) and 4.1 (95% LoA: -35-43) were observed using proposed model and the conventional method, respectively. The r-values of rCBF at rest, rCBF after the acetazolamide challenge, and CVR calculated using the Ca10 estimated by our proposed model were 0.83, 0.80 and 0.95, respectively. CONCLUSION: Our proposed ANN-based model could accurately estimate the Ca10, rCBF, and CVR in DTARG. These results would enable non-invasive rCBF quantification in DTARG.

Comparison of image quality and pancreatic ductal adenocarcinoma conspicuity between the low-kVp and dual-energy CT reconstructed with deep-learning image reconstruction algorithm.

PURPOSE: To compare the image quality and conspicuity of pancreatic ductal adenocarcinoma (PDAC) between the low-kVp and dual-energy pancreatic protocol CT reconstructed with deep-learning image reconstruction (DLIR). METHOD: A cohort of 111 consecutive patients (median age, 72 years; 56 men) undergoing a pancreatic protocol CT were retrospectively analyzed. Among them, 58 patients underwent 80-kVp CT (80-kVp group), and 53 patients underwent dual-energy CT and reconstructed at 40-keV (40-keV group). The medium-strength level of DLIR were used in both groups. Quantitative measurements, qualitative image quality, PDAC conspicuity, and dose-length product (DLP) were compared between the two groups using Mann-Whitney U test. RESULTS: A total of 20 and 16 PDACs were found in the 80-kVp and 40-keV groups, respectively. CT numbers of the vasculatures and parenchymal organs (P <.001 for all) and the background noise at both pancreatic and portal venous phases (P <.001) were higher in the 40-keV group than in the 80-kVp group. The signal-to-noise ratio (SNR) of all anatomical structures (P <.001-0.005), except for the liver in reviewer 2 (P =.47), and the tumor-to-pancreas contrast-to-noise ratio (CNR; P <.001-0.01) were higher in the 40-keV group than in the 80-kVp group. No difference was found in the image quality at both phases (P =.30-0.90). PDAC conspicuity was better in the 40-keV group than in the 80-kVp group (P =.007-0.03). DLP at pancreatic (275 vs. 313 mGy*cm; P =.05) and portal venous phases (743 vs. 766 mGy*cm; P =.20) was comparable between the two groups. CONCLUSION: Under the same DLP, virtual monoenergetic images at 40-keV demonstrated higher SNR and tumor-to-pancreas CNR and better PDAC conspicuity compared to the 80-kVp setting.

Vascular involvement and resectability of pancreatic ductal adenocarcinoma on contrast-enhanced MRI: comparison with pancreatic protocol CT.

PURPOSE: To compare the diagnostic performance for detecting vascular involvement and determining resectability differences regarding pancreatic ductal adenocarcinoma (PDAC) between contrast-enhanced CT and MRI. METHODS: This retrospective study evaluated 82 patients (73 years, 46 men) with PDAC who underwent both preoperative contrast-enhanced CT and MRI from January 2008 to March 2021. Two radiologists independently categorized vascular involvements for celiac, superior mesenteric, splenic, and common hepatic arteries, and portal, superior mesenteric, and splenic veins into no tumor contact, solid soft-tissue contact ≤ 180°, or solid soft-tissue contact > 180°. The radiologists also classified resectability into resectable, borderline resectable, or locally advanced. Receiver-operating-characteristic (ROC) analysis was conducted to evaluate the diagnostic performances for detecting vascular involvements which were confirmed by pathological or intraoperative findings. The proportion of resectability classifications was compared between CT and MRI by the Fisher's exact test. RESULTS: No statistical difference was found in the diagnostic performances for detecting vascular involvement in CT (area under the ROC curve [AUC], 0.50-0.89) and MRI (AUC, 0.51-0.75) (P = 0.06-> 0.99). Resectability on CT were 79% and 68%, 20% and 26%, and 1% and 6% for resectable, borderline resectable, and locally advanced tumors for reviewers 1 and 2; those on MRI were 87% and 81%, 12% and 13%, and 1% and 6%, respectively. The proportion of resectability classifications was not different between CT and MRI (P = 0.48 and = 0.15 for reviewers 1 and 2, respectively). CONCLUSION: The diagnostic performance for detecting vascular involvement and determining resectability of PDAC on contrast-enhanced MRI were comparable with pancreatic protocol CT.

Unenhanced abdominal low-dose CT reconstructed with deep learning-based image reconstruction: image quality and anatomical structure depiction.

PURPOSE: To evaluate the utility of deep learning-based image reconstruction (DLIR) algorithm in unenhanced abdominal low-dose CT (LDCT). MATERIALS AND METHODS: Two patient groups were included in this prospective study: 58 consecutive patients who underwent unenhanced abdominal standard-dose CT reconstructed with hybrid iterative reconstruction (SDCT group) and 48 consecutive patients who underwent unenhanced abdominal LDCT reconstructed with high strength level of DLIR (LDCT group). The background noise and signal-to-noise ratio (SNR) of the liver, pancreas, spleen, kidney, abdominal aorta, inferior vena cava, and portal vein were calculated. Two radiologists qualitatively assessed the overall image noise, overall image quality, and abdominal anatomical structures depiction. Quantitative and qualitative parameters and size-specific dose estimates (SSDE) were compared between SDCT and LDCT groups. RESULTS: The background noise was lower in LDCT group than in SDCT group (P = 0.02). SNRs were higher in LDCT group than in SDCT group (P < 0.001-0.004) except for the liver. Overall image noise was superior in LDCT group than in SDCT group (P < 0.001). Overall image quality was not different between SDCT and LDCT groups (P = 0.25-0.26). Depiction of almost all abdominal anatomical structures was equal to or better in LDCT group than in SDCT group (P < 0.001-0.88). The SSDE was lower in LDCT group (4.0 mGy) than in SDCT group (20.6 mGy) (P < 0.001). CONCLUSIONS: DLIR facilitates substantial radiation dose reduction of > 75% and significantly reduces background noise. DLIR can maintain image quality and anatomical structure depiction in unenhanced abdominal LDCT.

Radiation and iodine dose reduced thoraco-abdomino-pelvic dual-energy CT at 40 keV reconstructed with deep learning image reconstruction.

OBJECTIVE: To evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in dual-energy thoraco-abdomino-pelvic CT reconstructed with deep learning image reconstruction (DLIR). METHODS: Thoraco-abdomino-pelvic CT was prospectively performed in 111 participants; 52 participants underwent a standard-dose single-energy CT with a standard iodine dose (600 mgI/kg; SD group), while 59 underwent a low-dose dual-energy CT with a reduced iodine dose [300 mgI/kg; double low-dose (DLD) group]. CT data were reconstructed with a hybrid iterative reconstruction in the SD group and a high-strength level of DLIR at 40 keV in the DLD group. Two radiologists measured the CT numbers of the descending and abdominal aorta, portal vein, hepatic vein, inferior vena cava, liver, pancreas, spleen, and kidney, and background noise. Two other radiologists assessed diagnostic acceptability using a 5-point scale. The CT dose-index volume (CTDIvol), iodine weight, CT numbers of anatomical structures, background noise, and diagnostic acceptability were compared between the two groups using Mann-Whitney U test. RESULTS: The median CTDIvol [10 mGy; interquartile range (IQR), 9-13 mGy vs 4 mGy; IQR, 4-5 mGy] and median iodine weight (35 g; IQR, 31-38 g vs 16 g; IQR, 14-18 g) were lower in the DLD group than in the SD group (p < 0.001 for each). The CT numbers of all anatomical structures and background noise were higher in the DLD group than in the SD group (p < 0.001 for all). The diagnostic image quality was obtained in 100% (52/52) of participants in the SD group and 95% (56/59) of participants in the DLD group. CONCLUSION: Virtual monochromatic images at 40 keV reconstructed with DLIR could achieve half doses of radiation and iodine while maintaining diagnostic image quality. ADVANCES IN KNOWLEDGE: Virtual monochromatic images at 40 keV reconstructed with DLIR algorithm allowed to reduce the doses of radiation and iodine while maintaining diagnostic image quality.

Prediction of overall survival in patients with pancreatic ductal adenocarcinoma: histogram analysis of ADC value and correlation with pathological intratumoral necrosis.

BACKGROUND: To evaluate the utility of histogram analysis (HA) of apparent diffusion coefficient (ADC) values to predict the overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC) and to correlate with pathologically evaluated massive intratumoral necrosis (MITN). MATERIALS AND METHODS: Thirty-nine patients were included in this retrospective study with surgically resected PDAC who underwent preoperative magnetic resonance imaging. Twelve patients received neoadjuvant chemotherapy. HA on the ADC maps were performed to obtain the tumor HA parameters. Using Cox proportional regression analysis adjusted for age, time-dependent receiver-operating-characteristic (ROC) curve analysis, and Kaplan-Meier estimation, we evaluated the association between HA parameters and OS. The association between prognostic factors and pathologically confirmed MITN was assessed by logistic regression analysis. RESULTS: The median OS was 19.9 months. The kurtosis (P < 0.001), entropy (P = 0.013), and energy (P = 0.04) were significantly associated with OS. The kurtosis had the highest area under the ROC curve (AUC) for predicting 3-year survival (AUC 0.824) among these three parameters. Between the kurtosis and MITN, the logistic regression model revealed a positive correlation (P = 0.045). Lower survival rates occurred in patients with high kurtosis (cutoff value > 2.45) than those with low kurtosis (≤ 2.45) (P < 0.001: 1-year survival rate, 75.2% versus 100%: 3-year survival rate, 14.7% versus 100%). CONCLUSIONS: HA derived kurtosis obtained from tumor ADC maps might be a potential imaging biomarker for predicting the presence of MITN and OS in patients with PDAC.

Diffusion-weighted imaging of the abdomen using echo planar imaging with compressed SENSE: Feasibility, image quality, and ADC value evaluation.

OBJECTIVE: To evaluate the feasibility, image quality, and apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with Compressed SENSE (EPICS-DWI) of the abdomen and to compare them with conventional single-shot EPI with parallel imaging (PI) technique (PI-DWI). MATERIALS AND METHODS: This prospective study included 46 participants with known or suspected upper abdominal diseases (19 men and 27 women, mean age, 68 years) who underwent MRI. DWI acquisition was performed using free-breathing two-dimensional fat-suppressed PI-DWI and EPICS-DWI with SENSE or compressed sensing (CS) factor, 3.0. Moreover, image noise and contour of liver and pancreas were qualitatively evaluated using a five-point scale. The mean ADC value and standard deviation (SD) of the liver, pancreas, and spleen were measured, and the coefficient of variation (CV) was calculated. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon test. RESULTS: The mean image quality scores for image noise and contour of liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001). Moreover, the mean ADC values of the liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001), but that of spleen was not significantly different. The mean SD and CV of the liver, pancreas, and spleen were lower in EPICS-DWI compared with PI-DWI (P < 0.0001-0.032). CONCLUSION: EPICS-DWI could be feasible in MRI of the abdomen and significantly improve image quality compared with PI-DWI in aggressive setting. ADC value measurements were higher in EPICS-DWI compared with PI-DWI.

Optimized scan delay for late hepatic arterial or pancreatic parenchymal phase in dynamic contrast-enhanced computed tomography with bolus-tracking method.

OBJECTIVES: To determine the optimal scan delay corresponding to individual hemodynamic status for pancreatic parenchymal phase in dynamic contrast-enhanced CT of the abdomen. METHODS: One hundred and fourteen patients were included in this retrospective study (69 males and 45 females; mean age, 67.9 ± 12.1 years; range, 39-87 years). These patients underwent abdominal dynamic contrast-enhanced CT between November 2019 and May 2020. We calculated and recorded the time from contrast material injection to the bolus-tracking trigger of 100 Hounsfield unit (HU) at the abdominal aorta (s) (TimeTRIG) and scan delay from the bolus-tracking trigger to the initiation of pancreatic parenchymal phase scanning (s) (TimeSD). The scan delay ratio (SDR) was defined by dividing the TimeSD by TimeTRIG. Non-linear regression analysis was conducted to assess the association between CT number of the pancreas and SDR and to reveal the optimal SDR, which was ≥120 HU in pancreatic parenchyma. RESULTS: The non-linear regression analysis showed a significant association between CT number of the pancreas and the SDR (p < 0.001). The mean TimeTRIG and TimeSD were 16.1 s and 16.8 s, respectively. The SDR to peak enhancement of the pancreas (123.5 HU) was 1.00. An SDR between 0.89 and 1.18 shows an appropriate enhancement of the pancreas (≥120 HU). CONCLUSION: The CT number of the pancreas peaked at an SDR of 1.00, which means TimeSD should be approximately the same as TimeTRIG to obtain appropriate pancreatic parenchymal phase images in dynamic contrast-enhanced CT with bolus-tracking method. ADVANCES IN KNOWLEDGE: The hemodynamic state is different in each patient; therefore, scan delay from the bolus-tracking trigger should also vary based on the time from contrast material injection to the bolus-tracking trigger. This is necessary to obtain appropriate late hepatic arterial or pancreatic parenchymal phase images in dynamic contrast-enhanced CT of the abdomen.

Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.

OBJECTIVES: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR). METHODS: The study cohort of 59 consecutive patients (mean age, 67.2 years) who underwent whole-body LD CT and a prior standard-dose (SD) CT reconstructed with hybrid iterative reconstruction (SD-IR) within one year for surveillance of malignancy were assessed. The LD CT images were reconstructed with hybrid iterative reconstruction of 40% (LD-IR) and DLIR (LD-DLIR). The radiologists independently evaluated image quality (5-point scale) and lesion detection. Attenuation values in Hounsfield units (HU) of the liver, pancreas, spleen, abdominal aorta, and portal vein; the background noise and signal-to-noise ratio (SNR) of the liver, pancreas, and spleen were calculated. Qualitative and quantitative parameters were compared between the SD-IR, LD-IR, and LD-DLIR images. The CT dose-index volumes (CTDIvol) and dose-length product (DLP) were compared between SD and LD scans. RESULTS: The image quality and lesion detection rate of the LD-DLIR was comparable to the SD-IR. The image quality was significantly better in SD-IR than in LD-IR (p < 0.017). The attenuation values of all anatomical structures were comparable between the SD-IR and LD-DLIR (p = 0.28-0.96). However, background noise was significantly lower in the LD-DLIR (p < 0.001) and resulted in improved SNRs (p < 0.001) compared to the SD-IR and LD-IR images. The mean CTDIvol and DLP were significantly lower in the LD (2.9 mGy and 216.2 mGy•cm) than in the SD (13.5 mGy and 1011.6 mGy•cm) (p < 0.0001). CONCLUSION: LD CT images reconstructed with DLIR enable radiation dose reduction of >75% while maintaining image quality and lesion detection rate and superior SNR in comparison to SD-IR. ADVANCES IN KNOWLEDGE: Deep learning image reconstruction algorithm enables around 80% reduction in radiation dose while maintaining the image quality and lesion detection compared to standard-dose whole-body CT.

Can MRI features differentiate ovarian mucinous carcinoma from mucinous borderline tumor?

PURPOSE: Our purpose was to determine if MRI could be used to distinguish ovarian mucinous carcinoma (MC) from mucinous borderline tumor (MBT). MATERIALS AND METHODS: This study included 63 consecutive patients with histopathologically proven ovarian mucinous neoplasms (11 MCs and 52 MBTs) who underwent preoperative contrast-enhanced MRI. MRI images were retrospectively reviewed and compared between the 2 pathologies. RESULTS: The maximum tumor diameters (219.7 ±â€¯80.8 mm vs. 177.4 ±â€¯56.5 mm, p <  0.05) and maximum mural nodule (MN) diameters (41.7 ± 33.8 mm vs. 6.6 ± 8.9 mm, p <  0.01) were significantly larger in MCs than in MBTs. MNs larger than 5 mm (82 % vs. 29 %, p <  0.01) and abnormal ascites (45 % vs. 12 %, p <  0.05) were significantly more frequent in MCs than in MBTs. Apparent diffusion coefficient (ADC) values of MN were significantly lower in MCs than in MBTs (1.20 ± 0.25 × 10-3 mm2/s vs. 1.61 ±â€¯0.35 × 10-3 mm2/s, p <  0.05). No significant difference was found in number of loculi, honeycomb sign, stained glass appearance, fluid-fluid level, thickened septa larger than 5 mm, peritoneal dissemination, or T2 hypointense microcysts between MCs and MBTs. T2 hypointense microcysts were observed only in 7 MBTs (13%). CONCLUSION: MRI findings of these 2 pathologies overlapped considerably. Compared with MBTs, MCs exhibited larger tumor size, larger MN size, and lower ADC values of MN, and MCs more frequently had MNs larger than 5 mm and abnormal ascites. T2 hypointense microcysts might be a specific MRI finding in MBTs.