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.

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.

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.

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.

Radiological Arterial Anatomy in Mature Microminipigs as a Pre-clinical Research Model in Interventional Radiology.

PURPOSE: To define the radiological arterial anatomy in mature microminipigs as a pre-clinical research animal model in interventional radiology. MATERIALS AND METHODS: Five female microminipigs (weighing 20.9 ± 2.9 kg) were used in this study. Under general anesthesia, computed tomography (CT) angiography was performed using a 16-slice CT scanner. CT was performed 12 s after initiation of an intravenous injection of 40 ml of nonionic contrast media at 3.0 ml/second using a power injector. The transverse CT angiography images were evaluated using a digital imaging and communication in medicine viewer, and the diameters of the following 41 arteries were measured.: ascending aorta, descending aorta, thoracoabdominal aorta, abdominal aorta, pulmonary artery trunk, both pulmonary, brachiocephalic artery, short common bicarotid, both common carotid artery, subclavian, bronchial, internal mammary, celiac, common hepatic, left lateral hepatic, middle hepatic, left hepatic, gastroduodenal, cranial duodenopancreatic, splenic, left gastric, cranial mesenteric, ileocolic , bilateral colic artery, caudal mesenteric, cranial rectal, renal, both external iliac arteries, internal iliac common trunk, and both internal iliac and femoral arteries. RESULTS: The microminipigs' vascular anatomy was the same as domestic pig anatomy and similar to human anatomy. The diameter of the aorta (ascending to abdominal) was 17.1-7.0 mm, iliac and femoral arteries (internal iliac common trunk to femoral artery): 5.5-3.8 mm, pulmonary arteries: 9.3-14.7 mm, and major first aortic branches (e.g., celiac or brachiocephalic artery): 2.2-9.2 mm. CONCLUSION: This study defined the microminipig arterial anatomy in the trunk.

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.

OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images reconstructed using hybrid iterative reconstruction (IR). METHODS: The local institutional review board approved this prospective study. Written informed consent was obtained from all participants. Thirty consecutive participants with pancreatic cancer (PC) underwent pancreatic protocol DECT for initial evaluation. DECT data were reconstructed at 70 keV using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The diagnostic acceptability and conspicuity of PC were qualitatively assessed using a 5-point scale. IC values of the abdominal aorta, pancreas, PC, liver, and portal vein; standard deviation (SD); and coefficient of variation (CV) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H groups. RESULTS: The diagnostic acceptability and conspicuity of PC were significantly better in the DLIR-M group compared with those in the other groups (p < .001-.001). The IC values of the anatomical structures were almost comparable between the three groups (p = .001-.9). The SD of IC values was significantly lower in the DLIR-H group (p < .001) and resulted in the lowest CV (p < .001-.002) compared with those in the hybrid-IR and DLIR-M groups. CONCLUSIONS: DLIR could significantly improve image quality and reduce the variability of IC values than could hybrid-IR. KEY POINTS: Image quality and conspicuity of pancreatic cancer were the best in DLIR-M. DLIR significantly reduced background noise and improved SNR and CNR. The variability of iodine concentration was reduced in DLIR.

Optimized Bolus Threshold for Dual-Energy CT Angiography with Monoenergetic Images: A Randomized Clinical Trial.

Background The bolus-tracking technique from single-energy CT has been applied to dual-energy CT (DECT) without optimization or validation. Further optimization is imperative because of a paucity of literature and differences in the attenuation profile of virtual monoenergetic images (VMIs). Purpose To determine the optimal trigger threshold with bolus-tracking technique for DECT angiography (DECTA) in a phantom study and assess the feasibility of an optimized threshold for bolus-tracking technique in DECTA at 40 keV with a 50% reduced iodine dose in human participants. Materials and Methods A phantom study with rapid kilovoltage-switching DECT was performed to determine the optimal threshold for each kiloelectron-volt VMI. In a prospective study, consecutive participants who underwent whole-body CT angiography (CTA) from August 2018 to July 2019 were randomized into three groups: single-energy CTA (SECTA) with standard iodine dose (600 mg of iodine per kilogram), DECTA with 50% reduced iodine dose (300 mg of iodine per kilogram) by using a conventional threshold, and DECTA with 300 mg of iodine per kilogram by using an optimized threshold. A trigger threshold of 100 HU at 120 kVp was used as a reference for comparison. Injected iodine doses and aortic CT numbers were compared among the three groups using Kruskal-Wallis test. Results Ninety-six participants (mean age ± standard deviation, 72 years ± 9; 80 men) were evaluated (32 participants in each group). The optimized threshold for VMIs at 40 keV was 30 HU. The median iodine dose was lower in the optimized DECTA group (13 g) compared with conventional DECTA (19 g) and SECTA (26 g) groups (P < .017 for each comparison). The median aortic CT numbers were higher in the order corresponding to conventional DECTA (655-769 HU), optimized DECTA (543-610 HU), and SECTA (343-359 HU) groups (P < .001). Conclusion The optimized trigger threshold of 30 HU for bolus-tracking technique during dual-energy CT angiography at 40 keV achieved lower iodine load while maintaining aortic enhancement. ©RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Malayeri in this issue.

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.

Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction.

PURPOSE: To evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography (LDCT) reconstructed using deep learning image reconstruction (DLIR) and compare with those of images reconstructed using hybrid iterative reconstruction (IR). METHODS: Our institutional review board approved this prospective study. Written informed consent was obtained from all patients. Twenty-eight consecutive patients with PDAC undergoing chemotherapy (14 men and 14 women; mean age, 68.4 years) underwent pancreatic LDCT for therapy evaluation. The LDCT images were reconstructed using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H). The image noise, diagnostic acceptability, and conspicuity of PDAC were qualitatively assessed using a 5-point scale. CT numbers of the abdominal aorta, portal vein, pancreas, PDAC, background noise, signal-to-noise ratio (SNR) of the anatomical structures, and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H images. RESULTS: CT dose-index volumes and dose-length product in pancreatic LDCT were 2.3 ± 1.0 mGy and 74.9 ± 37.0 mGy•cm, respectively. The image noise, diagnostic acceptability, and conspicuity of PDAC were significantly better in DLIR-H than those in hybrid-IR and DLIR-M (all P < 0.001). The background noise was significantly lower in the DLIR-H images (P < 0.001) and resulted in improved SNRs (P < 0.001) and CNR (P < 0.001) compared with those in the hybrid-IR and DLIR-M images. CONCLUSION: DLIR significantly reduced image noise and improved image quality in pancreatic LDCT images compared with hybrid-IR.

Advantages and disadvantages of single-source dual-energy whole-body CT angiography with 50% reduced iodine dose at 40 keV reconstruction.

OBJECTIVES: To assess the feasibility of whole-body dual-energy computed tomographic angiography (DECTA) at 40 keV with 50% reduced iodine dose protocol. METHODS: Whole-body CTA was performed in 65 patients; 31 of these patients underwent 120 kVp single-energy computed tomographic angiography (SECTA) with standard iodine dose (600 mgI/kg) and 34 with 40 keV DECTA with 50% reduced iodine dose (300 mgI/kg). SECTA data were reconstructed with adaptive statistical iterative reconstruction of 40% (SECTA group), and DECTA data were reconstructed with adaptive statistical iterative reconstruction of 40% (DECTA-40% group) and 80% (DECTA-80% group). CT numbers of the thoracic and abdominal aorta, iliac artery, background noise, signal-to-noise ratio (SNR), and arterial depiction were compared among the three groups. The CT dose index volumes (CTDIvol) for the thorax, abdomen, and pelvis were compared between SECTA and DECTA protocols. RESULTS: The vascular CT numbers and background noise were found to be significantly higher in DECTA groups than in the SECTA group (p < 0.001). SNR was significantly higher in the order corresponding to DECTA-80%, SECTA, and DECTA-40% (p < 0.001). The arterial depiction was comparable in almost all arteries; however, intrapelvic arterial depiction was significantly worse in DECTA groups than in the SECTA group (p < 0.0001-0.017). Unlike the pelvic region (p = 0.055), CTDIvol for the thorax (p < 0.0001) and abdomen (p = 0.0031) were significantly higher in the DECTA protocol than in the SECTA protocol. CONCLUSION: DECTA at 40 keV with 50% reduced iodine dose provided higher vascular CT numbers and SNR than SECTA, and almost comparable arterial depiction, but had a degraded intrapelvic arterial depiction and required a larger radiation dose. ADVANCES IN KNOWLEDGE: DECTA enables 50% reduction of iodine dose while maintaining image quality, arterial depiction in almost all arteries, vascular CT numbers, and SNR; however, it does not allow clear visualization of intrapelvic arteries, requiring a slightly larger radiation dose compared with SECTA with standard iodine dose.

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.

Iodine dose optimization in portal venous phase virtual monochromatic images of the abdomen: Prospective study on rapid kVp switching dual energy CT.

PURPOSE: To investigate iodine dose concentration required for adequate hepatic parenchymal enhancement on fast-kilovoltage-switching dual-energy computed tomography (DECT) of the abdomen based on patient body weight. MATERIALS AND METHODS: The protocol of this prospective study was approved by the local Institutional Review Board and written informed consent for study participation was obtained from all patients. The study cohort of 204 consecutive patients who underwent whole body single-source DECT to screen for tumor metastases and/or recurrence after surgical resection of malignant tumors were randomly assigned to one of three protocols according to the iodine dose (400, 500, and 600 mgI/kg). For each case, two radiologists quantitatively and qualitatively reviewed three energy levels (65, 70, and 75 kilo electron volt [keV]) of the portal venous phase virtual monochromatic images (VMIs). CT numbers of the liver and the qualitative hepatic parenchymal enhancement were compared among the VMIs with the three protocols and three energy levels. RESULTS: Hepatic enhancement (ΔHU > 50HU) was achieved at 65 keV with 400, 500, and 600 mgI/kg, at 70 keV with 500 and 600 mgI/kg, and at 75 keV with 600 mgI/kg. The hepatic parenchymal enhancement was graded as sufficient hepatic enhancement in 97%, 100%, and 99% at 65 keV with 400, 500, and 600 mgI/kg, 88% and 97% at 70 keV with 500 and 600 mgI/kg, and 84% at 75 keV with 600 mgI/kg, respectively. CONCLUSION: The iodine dose can be reduced to 400 mgI/kg at 65 keV or 500 mgI/kg at 70 keV in DECT without compromising hepatic parenchymal enhancement.

Nuclear Accumulation of ß-Catenin in Cancer Stem Cell Radioresistance and Stemness in Human Colon Cancer.

BACKGROUND/AIM: The aim of this study was to examine whether the Wnt/ß-catenin signal activation is a cause of radioresistance in colon cancer by assessing the ß-catenin localization and its correlation with cancer stem cells (CSCs). MATERIALS AND METHODS: The nuclear levels of ß-catenin, the hallmark of Wnt activation, were analyzed in HCT116 and SW480 cells by immunohistochemistry, before and after irradiation. Further, we assessed CSC populations by staining for aldehyde dehydrogenase-1 (ALDH1) and CD44. RESULTS: ß-catenin was localized predominantly in the nucleus and plasma membrane in SW480 and HCT116 cells, respectively. Compared to HCT116 cells, SW480 cells displayed higher Wnt activation. At 24 h after irradiation, most of the DSBs in SW480 cells were repaired, but were still present in HCT116 cells. Additionally, compared to HCT116 cells, a significantly higher proportion of SW480 cells were ALDH1- and CD44-positive. CONCLUSION: Colon cancers with nuclear ß-catenin accumulation demonstrated greater radio-resistance with a higher number of CSCs.

Optimal window settings in single-source dual-energy computed tomography of the abdomen.

PURPOSE: To determine the optimal window settings for monochromatic images with various energy levels in single-source dual-energy computed tomography (DECT) of the abdomen. MATERIALS AND METHODS: Two hundred consecutive patients underwent contrast-enhanced DECT to screen tumor metastases and/or recurrences after surgery for malignant tumors. Two independent radiologists reviewed eight energy levels (40, 45, 50, 55, 60, 65, 70, and 75 kilo-electron volts [keV]) of the portal venous phase monochromatic images. For each keV image, the radiologists adjusted the window level (WL) and width (WW) using settings of 40 HU of WL and 350 HU of WW on 65 keV images as a reference and recorded these values. After removing the top and bottom 5% of the data, the optimal WL and WW in each energy levels were obtained by rounding the median values. In 7 of 200 patients with a total of 23 liver metastases, the tumor-to-liver contrast-to-noise ratio (CNR) was calculated and compared among the energy levels. RESULTS: The optimal WLs and WWs at each energy level were as follows: 40 keV, 140 and 680 HU; 45 keV, 110 and 570 HU; 50 keV, 90 and 490 HU; 55 keV, 70 and 440 HU; 60 keV, 60 and 390 HU; 65 keV, 40 and 350 HU; 70 keV, 30 and 320 HU; and 75 keV, and 20 and 300 HU. The best CNR was obtained using 65 keV images (P < 0.001). CONCLUSION: We clarified the optimal WL and WW available for the preset window settings in abdominal DECT.

Assessing Chemotherapeutic Response in Pancreatic Ductal Adenocarcinoma: Histogram Analysis of Iodine Concentration and CT Number in Single-Source Dual-Energy CT.

OBJECTIVE: The objective of this study was to evaluate the feasibility of histographic analysis of iodine concentration (IC) and CT number on single-source dual-energy CT (DECT) to assess response to first-line chemotherapy in patients with pancreatic ductal adenocarcinoma (PDAC) who received first-line chemotherapy but not radiation therapy. SUBJECTS AND METHODS: This prospective study was approved by our institutional review board, and patients gave written informed consent. Sixty consecutive patients with PDAC undergoing first-line chemotherapy underwent DECT during the pancreatic parenchymatous phase (PPP) and the equilibrium phase (EP). The IC and CT number of PDAC were measured using PPP and EP iodine-based material decomposition and monochromatic images (65 keV), respectively. Histographic parameters for the IC and CT number of PDACs were obtained, and differences in mean IC (ΔIC) and CT number (ΔHU) between the PPP and the EP were calculated. These parameters were then compared between the response (partial response or stable disease) and nonresponse (progressive disease) groups. RESULTS: Among the histographic parameters, the kurtosis of IC during the PPP (p = 0.018) and ΔIC (p = 0.0004) were identified as significant for differentiating between the two groups. IC diagnostic factor was calculated using the following coefficients of logistic regression analysis: 0.52 - (1.45 × kurtosis of IC during PPP) + (0.69 × ΔIC). The sensitivity, specificity, and area under the ROC curve for differentiating between the two groups were 97.7%, 70.6%, and 0.889, respectively. CONCLUSION: The IC diagnostic factor is a potential biomarker for assessing chemotherapeutic response in patients with PDAC.

Modified National Comprehensive Cancer Network Criteria for Assessing Resectability of Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: The objective of our study was to assess the preoperative resectability of pancreatic ductal adenocarcinoma (PDAC) using the National Comprehensive Cancer Network (NCCN) guideline, the general rules of the Japan Pancreas Society (JPS), and both of them combined. MATERIALS AND METHODS: Eighty-six consecutive patients with PDAC (50 men and 36 women; mean age ± SD, 70.8 ± 9.0 years; age range, 49-86 years) underwent dynamic contrast-enhanced CT. Following the NCCN guideline, the degree of vascular invasion was evaluated to determine the NCCN score: 0 points for absence of vascular invasion, 1 point for tumor contact ≤ 180°, and 2 points for tumor contact > 180°. Direct invasion to adjacent structures was rated according to the general rules of JPS to determine the JPS score: 0 points for absence and 1 point for presence. The NCCN score, JPS score, and sum of the two scores, which we refer to as the "combined score," were compared with histopathologic or intraoperative findings as well as for the differentiation of R0 resection (negative resection margins) from R1 (microscopic tumor infiltration) and R2 (macroscopic residual tumor) using ROC curve analysis. RESULTS: The sensitivities, specificities, and areas under the ROC curves (AUCs) for the differentiation of R0 from R1 and R2 were 100.0%, 40.0%, and 0.725, respectively, with the NCCN score; 63.9%, 84.0%, and 0.824 with the JPS score; and 86.9%, 68.0%, and 0.874 with the combined score. The AUC of the combined score was significantly greater than that of the NCCN score (p = 0.0059). CONCLUSION: The assessment of resectability of PDAC based on the combined criteria of the NCCN guideline and general rules of JPS was superior to that based on either criterion alone.

[Plain X-ray or Computed Tomography Image of Epidural Catheters with Various Materials].

BACKGROUND: Although breakage of the epidural catheter inside patients is a rare complication, plain X-ray or computed tomography (CT) image is useful for diagnosis of catheter remnant However, it is not well known whether the catheter materials are visible in these images. METHODS: We examined 3 types of X-ray permeabil- ity catheters and 6 types of X-ray impermeability cath- eters available in Japan. We obtained plain X-ray images of catheters alone, plain X-ray images of cathe- ters with bone dummy and CT images of catheters in the model of epidural space. RESULTS: On plain X-ray images of catheters alone, we could confirm all 6 types of X-ray impermeability catheters. However, on plain X-ray images of catheters with bone dummy, we could confirm only 3 types of catheters among 6 X-ray impermeability catheters. On CT images, we could confirm all 6 types of X-ray impermeability catheters, but not X-ray permeability catheters. CONCLUSIONS: Plain X-ray image can not provide the detection for some X-ray impermeability catheters. CT image is useful- for diagnosis of X-ray impermeability catheters.