N-butyl-2-cyanoacrylate Packing of a Gastroduodenal Artery Pseudoaneurysm due to Distal Pancreatectomy After Subtotal Esophagectomy.

We describe the successful n-butyl cyanoacrylate (NBCA) packing of a large gastroduodenal artery pseudoaneurysm after distal pancreatectomy in a patient with a history of subtotal esophagectomy and gastric tube reconstruction. The pseudoaneurysm was considered to be caused by direct injury to the gastroduodenal artery (GDA). However, embolization of the GDA was not possible in this case because due to prior esophageal surgery, the main blood vessel supplying the gastric tube was the right epigastric artery from the GDA. Packing a pseudoaneurysm with NBCA is a treatment option when preservation of the parent artery is required.

Computer-aided detection improves brain metastasis identification on non-enhanced CT in less experienced radiologists.

BACKGROUND: Brain metastases (BMs) are the most common intracranial tumors causing neurological complications associated with significant morbidity and mortality. PURPOSE: To evaluate the effect of computer-aided detection (CAD) on the performance of observers in detecting BMs on non-enhanced computed tomography (NECT). MATERIAL AND METHODS: Three less experienced and three experienced radiologists interpreted 30 NECT scans with 89 BMs in 25 cases to detect BMs with and without the assistance of CAD. The observers' sensitivity, number of false positives (FPs), positive predictive value (PPV), and reading time with and without CAD were compared using paired t-tests. The sensitivity of CAD and the observers were compared using a one-sample t-test. RESULTS: With CAD, less experienced radiologists' sensitivity significantly increased from 27.7% ± 4.6% to 32.6% ± 4.8% (P = 0.007), while the experienced radiologists' sensitivity did not show a significant difference (from 33.3% ± 3.5% to 31.9% ± 3.7%; P = 0.54). There was no significant difference between conditions with CAD and without CAD for FPs (less experienced radiologists: 23.0 ± 10.4 and 25.0 ± 9.3; P = 0.32; experienced radiologists: 18.3 ± 7.4 and 17.3 ± 6.7; P = 0.76) and PPVs (less experienced radiologists: 57.9% ± 8.3% and 50.9% ± 7.0%; P = 0.14; experienced radiologists: 61.8% ± 12.7% and 64.0% ± 12.1%; P = 0.69). There were no significant differences in reading time with and without CAD (85.0 ± 45.6 s and 73.7 ± 36.7 s; P = 0.09). The sensitivity of CAD was 47.2% (with a PPV of 8.9%), which was significantly higher than that of any radiologist (P < 0.001). CONCLUSION: CAD improved BM detection sensitivity on NECT without increasing FPs or reading time among less experienced radiologists, but this was not the case among experienced radiologists.

Reliability and sensitivity to altered hemodynamics measured with resting-state fMRI metrics: Comparison with 123I-IMP SPECT.

Blood oxygenation level-dependent (BOLD) contrast is sensitive to local hemodynamic changes and thus is applicable to imaging perfusion or vascular reactivity. However, knowledge about its measurement characteristics compared to reference standard perfusion imaging is limited. This study longitudinally evaluated perfusion in patients with steno-occlusive disease using resting-state functional MRI (rsfMRI) acquired before and within nine days of anterior circulation revascularization in patients with large cerebral artery steno-occlusive diseases. The reliability and sensitivity to longitudinal changes of rsfMRI temporal correlation (Rc) and time delay (TDc) relative to the cerebellar signal were examined voxel-wise in comparison with single-photon emission CT (SPECT) cerebral blood flow (CBF) using the within-subject standard deviation (Sw) and intraclass correlation coefficients (ICCs). For statistical comparisons, the standard deviation (SD) of longitudinal changes within the cerebellum, the number of voxels with significant changes in the left middle cerebral artery territory ipsilateral to surgery, and their average changes relative to the cerebellar SD were evaluated. The test-retest reliability of the fMRI metrics was also similarly evaluated using the human connectome project (HCP) healthy young adult dataset. The test-retest time interval was 31 ± 18 days. Test-retest reliability was significantly higher for SPECT (cerebellar SD: -2.59 ± 0.20) than for fMRI metrics (cerebellar SD: Rc, -2.34 ± 0.24, p = 0.04; TDc, -2.19 ± 0.21, p = 0.003). Sensitivity to postoperative changes, which was evaluated as the number of voxels, was significantly higher for fMRI TDc (8.78 ± 0.72) than for Rc (7.42 ± 1.48, p = 0.03) or SPECT CBF (6.88 ± 0.67, p < 0.001). The ratio between the average Rc, TDc, and SPECT CBF changes within the left MCA target region and cerebellar SD was also significantly higher for fMRI TDc (1.21 ± 0.79) than Rc (0.48 ± 0.94, p = 0.006) or SPECT CBF (0.23 ± 0.57, p = 0.001). The measurement variability of time delay was also larger than that of temporal correlation in HCP data within the cerebellum (t = -8.7, p < 0.001) or in the whole-brain (t = -27.4, p < 0.001) gray matter. These data suggest that fMRI time delay is more sensitive to the hemodynamic changes than SPECT CBF, although the reliability is lower. The implication for fMRI connectivity studies is that temporal correlation can be significantly decreased due to altered hemodynamics, even in cases with normal CBF.

The Usefulness of Computer-Aided Detection of Brain Metastases on Contrast-Enhanced Computed Tomography Using Single-Shot Multibox Detector: Observer Performance Study.

OBJECTIVE: This study aimed to test the usefulness of computer-aided detection (CAD) for the detection of brain metastasis (BM) on contrast-enhanced computed tomography. METHODS: The test data set included whole-brain axial contrast-enhanced computed tomography images of 25 cases with 62 BMs and 5 cases without BM. Six radiologists from 3 institutions with 2 to 4 years of experience independently reviewed the cases, both in conditions with and without CAD assistance. Sensitivity, positive predictive value, number of false positives, and reading time were compared between the conditions using paired t tests. Subanalysis was also performed for groups of lesions divided according to size. A P value <0.05 was considered statistically significant. RESULTS: With CAD, sensitivity significantly increased from 80.4% to 83.9% ( P = 0.04), whereas positive predictive value significantly decreased from 88.7% to 84.8% ( P = 0.03). Reading time with and without CAD was 112 and 107 seconds, respectively ( P = 0.38), and the number of false positives was 10.5 with CAD and 7.0 without CAD ( P = 0.053). Sensitivity significantly improved for 6- to 12-mm lesions, from 71.2% without CAD to 80.3% with CAD ( P = 0.02). The sensitivity of the CAD (95.2%) was significantly higher than that of any reader (with CAD: P = 0.01; without CAD: P = 0.005). CONCLUSIONS: Computer-aided detection significantly improved BM detection sensitivity without prolonging reading time while marginally increased the false positives.

Preoperative portal vein embolization: a comparison of ethanol and coils versus ethanol alone.

PURPOSE: To compare the efficacy and safety of preoperative portal vein embolization (PVE) with ethanol and coils versus ethanol alone. MATERIAL AND METHODS: Between April 2014 and May 2019, 45 patients underwent right preoperative PVE with ethanol and coils (n = 19; EthCo group) or ethanol alone (n = 26; Eth group). RESULTS: The change in % future liver remnant (FLR) was not significantly different between the EthCo and Eth groups (11.2 ± 4.3% versus 11.3 ± 4.1%, p = .98). Less ethanol was used in the EthCo group (9.7 ± 3.5 mL versus 11.9 ± 4.4 mL, p = .02). Recanalization was observed in eight patients only in the Eth group (p < .01). There were no differences in the pre-/post-PVE laboratory data between the two groups, except for post-PVE albumin. The volume of ethanol used was positively correlated with the post-PVE total bilirubin (p = .01), aspartate aminotransferase (AST) (p < .01) and alanine aminotransferase (ALT) (p < .01) levels. CONCLUSION: The efficacy of PVE did not differ between the EthCo and Eth groups. The use of ethanol and coils was associated with less recanalization and liver damage compared with ethanol alone.

Deep-learning 2.5-dimensional single-shot detector improves the performance of automated detection of brain metastases on contrast-enhanced CT.

PURPOSE: This study aims to develop a 2.5-dimensional (2.5D) deep-learning, object detection model for the automated detection of brain metastases, into which three consecutive slices were fed as the input for the prediction in the central slice, and to compare its performance with that of an ordinary 2-dimensional (2D) model. METHODS: We analyzed 696 brain metastases on 127 contrast-enhanced computed tomography (CT) scans from 127 patients with brain metastases. The scans were randomly divided into training (n = 79), validation (n = 18), and test (n = 30) datasets. Single-shot detector (SSD) models with a feature fusion module were constructed, trained, and compared using the lesion-based sensitivity, positive predictive value (PPV), and the number of false positives per patient at a confidence threshold of 50%. RESULTS: The 2.5D SSD model had a significantly higher PPV (t test, p < 0.001) and a significantly smaller number of false positives (t test, p < 0.001). The sensitivities of the 2D and 2.5D models were 88.1% (95% confidence interval [CI], 86.6-89.6%) and 88.7% (95% CI, 87.3-90.1%), respectively. The corresponding PPVs were 39.0% (95% CI, 36.5-41.4%) and 58.9% (95% CI, 55.2-62.7%), respectively. The numbers of false positives per patient were 11.9 (95% CI, 10.7-13.2) and 4.9 (95% CI, 4.2-5.7), respectively. CONCLUSION: Our results indicate that 2.5D deep-learning, object detection models, which use information about the continuity between adjacent slices, may reduce false positives and improve the performance of automated detection of brain metastases compared with ordinary 2D models.

Reliability and Sensitivity to Longitudinal CBF Changes in Steno-Occlusive Diseases: ASL Versus 123 I-IMP-SPECT.

BACKGROUND: Noninvasive cerebral blood flow (CBF) monitoring using arterial spin labeling (ASL) magnetic resonance imaging is useful for managing large cerebral artery steno-occlusive diseases. However, knowledge about its measurement characteristics in comparison with reference standard perfusion imaging is limited. PURPOSE: To evaluate perfusion in a longitudinal manner in patients with steno-occlusive disease using ASL and compare with single-photon emission computed tomography (SPECT). STUDY TYPE: Prospective. POPULATION: Moyamoya (n = 10, eight females) and atherosclerotic diseases (n = 2, two males). FIELD STRENGTH/SEQUENCE: 3.0 T; gradient-echo three-dimensional T1 -weighted and spin-echo ASL. ASSESSMENT: Multi-delay ASL and [123 I]-iodoamphetamine SPECT CBF measurements were performed both before and within 9 days of anterior-circulation revascularization. Reliability and sensitivity to whole-brain voxel-wise CBF changes (ΔCBF) and their postlabeling delay (PLD) dependency with varied PLDs (in milliseconds) of 1000, 2333, and 3666 were examined. STATISTICAL TESTS: Reliability and sensitivity to ΔCBF were examined using within-subject standard deviation (Sw) and intraclass correlation coefficients (ICCs). For statistical comparisons, standard deviation of longitudinal ΔCBF within the hemisphere contralateral to surgery, and the ratio between it and average ΔCBF within the ipsilateral regions of interest were subjected to paired t tests, respectively. P < 0.05 was considered statistically significant. RESULTS: ASL test-retest time interval was 31 ± 18 days. Test-retest reliability was significantly lower for SPECT (0.16 ± 0.02) than ASL (0.13 ± 0.04). Sensitivity to postoperative changes was significantly higher for ASL (2.71 ± 2.79) than SPECT (0.27 ± 0.62). Test-retest reliability was significantly higher for a PLD of 2333 (0.13 ± 0.04) than 3666 (0.19 ± 0.05), and sensitivity to ΔCBF was significantly higher for PLDs of 1000 (2.53 ± 2.50) and 2333 than 3666 (0.79 ± 1.88). ICC maps also showed higher reliability for ASL than SPECT. DATA CONCLUSION: Higher test-retest reliability led to better ASL sensitivity than SPECT for postoperative ΔCBF. ASL test-retest reliability and sensitivity to ΔCBF were higher with a PLD of 2333. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Feature-fusion improves MRI single-shot deep learning detection of small brain metastases.

BACKGROUND AND PURPOSE: To examine whether feature-fusion (FF) method improves single-shot detector's (SSD's) detection of small brain metastases on contrast-enhanced (CE) T1-weighted MRI. METHODS: The study included 234 MRI scans from 234 patients (64.3 years±12.0; 126 men). The ground-truth annotation was performed semiautomatically. SSDs with and without an FF module were developed and trained using 178 scans. The detection performance was evaluated at the SSDs' 50% confidence threshold using sensitivity, positive-predictive value (PPV), and the false-positive (FP) per scan with the remaining 56 scans. RESULTS: FF-SSD achieved an overall sensitivity of 86.0% (95% confidence interval [CI]: [83.0%, 85.6%]; 196/228) and 46.8% PPV (95% CI: [42.0%, 46.3%]; 196/434), with 4.3 FP (95% CI: [4.3, 4.9]). Lesions smaller than 3 mm had 45.8% sensitivity (95% CI: [36.1%, 45.5%]; 22/48) with 2.0 FP (95% CI: [1.9, 2.1]). Lesions measuring 3-6 mm had 92.3% sensitivity (95% CI: [86.5%, 92.0%]; 48/52) with 1.8 FP (95% CI: [1.7, 2.2]). Lesions larger than 6 mm had 98.4% sensitivity (95% CI: [97.8%, 99.4%]; 126/128) 0.5 FP (95% CI: [0.5, 0.8]) per scan. FF-SSD had a significantly higher sensitivity for lesions < 3 mm (p = 0.008, t = 3.53) than the baseline SSD, while the overall PPV was similar (p = 0.06, t = -2.16). A similar trend was observed even when the detector's confidence threshold was varied as low as 0.2, for which the FF-SSD's sensitivity was 91.2% and the FP was 9.5. CONCLUSIONS: The FF-SSD algorithm identified brain metastases on CE T1-weighted MRI with high accuracy.

Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images.

PURPOSE: To develop a deep-learning object detection model for automatic detection of brain metastases that simultaneously uses contrast-enhanced and non-enhanced images as inputs, and to compare its performance with that of a model that uses only contrast-enhanced images. METHOD: A total of 116 computed tomography (CT) scans of 116 patients with brain metastases were included in this study. They showed a total of 659 metastases, 428 of which were used for training and validation (mean size, 11.3 ± 9.9 mm) and 231 were used for testing (mean size, 9.0 ± 7.0 mm). Single-shot detector (SSD) models were constructed with a feature fusion module, and their results were compared per lesion at a confidence threshold of 50%. RESULTS: The sensitivity was 88.7% for the model that used both contrast-enhanced and non-enhanced CT images (the CE + NECT model) and 87.6% for the model that used only contrast-enhanced CT images (the CECT model). The positive predictive value (PPV) was 44.0% for the CE + NECT model and 37.2% for the CECT model. The number of false positives per patient was 9.9 for the CE + NECT model and 13.6 for the CECT model. The CE + NECT model had a significantly higher PPV (t test, p < 0.001), significantly fewer false positives (t test, p < 0.001), and a tendency to be more sensitive (t test, p = 0.14). CONCLUSIONS: The results indicate that the information on true contrast enhancement obtained by comparing the contrast-enhanced and non-enhanced images may prevent the detection of pseudolesions, suppress false positives, and improve the performance of deep-learning object detection models.

Automated detection of brain metastases on non-enhanced CT using single-shot detectors.

PURPOSE: To develop and investigate deep learning-based detectors for brain metastases detection on non-enhanced (NE) CT. METHODS: The study included 116 NECTs from 116 patients (81 men, age 66.5 ± 10.6 years) to train and test single-shot detector (SSD) models using 89 and 27 cases, respectively. The annotation was performed by three radiologists using bounding-boxes defined on contrast-enhanced CT (CECT) images. NECTs were coregistered and resliced to CECTs. The detection performance was evaluated at the SSD's 50% confidence threshold using sensitivity, positive-predictive value (PPV), and the false-positive rate per scan (FPR). For false negatives and true positives, binary logistic regression was used to examine the possible contributing factors. RESULTS: For lesions 6 mm or larger, the SSD achieved a sensitivity of 35.4% (95% confidence interval (CI): [32.3%, 33.5%]); 51/144) with an FPR of 14.9 (95% CI [12.4, 13.9]). The overall sensitivity was 23.8% (95% CI: [21.3%, 22.8%]; 55/231) and PPV was 19.1% (95% CI: [18.5%, 20.4%]; 98/ of 513), with an FPR of 15.4 (95% CI [12.9, 14.5]). Ninety-five percent of the lesions that SSD failed to detect were also undetectable to radiologists (168/176). Twenty-four percent of the lesions (13/50) detected by the SSD were undetectable to radiologists. Logistic regression analysis indicated that density, necrosis, and size contributed to the lesions' visibility for radiologists, while for the SSD, the surrounding edema also enhanced the detection performance. CONCLUSION: The SSD model we developed could detect brain metastases larger than 6 mm to some extent, a quarter of which were even retrospectively unrecognizable to radiologists.

Automatic detection of brain metastases on contrast-enhanced CT with deep-learning feature-fused single-shot detectors.

PURPOSE: Despite the potential usefulness, no automatic detector is available for brain metastases on contrast-enhanced CT (CECT). The study aims to develop and investigate deep learning-based detectors for brain metastases detection on CECT. METHOD: The study included 127 CECTs from 127 patients (65.5 years±11.1; 87 men). The ground-truth annotation was performed semi-automatically by applying connected-component analysis to the binarized dataset by three radiologists. Single-shot detector (SSD) algorithms, with and without a feature-fusion module, were developed and trained using 97 scans. The performance was evaluated at the detector's 50 % confidence threshold with the remaining 30 scans using sensitivity, positive-predictive value (PPV), and the false-positive rate per scan (FPR). RESULTS: Feature-fused SSD achieved an overall sensitivity of 88.1 % (95 % confidence interval [CI]: [85.2 %,88.6 %]; 214/243) and PPV of 36.0 % (95 % CI: [33.7 %,37.1 %]; 233/648), with 13.8 FPR (95 % CI: [12.7,15.0]). Lesions < 3 mm had a sensitivity of 23.1 % (95 % CI: [21.2 %,40.0 %]; 3/13), with 0.2 FPR (95 % CI: [0.23,0.65]). Lesions measuring 3-6 mm had a sensitivity of 80.0 % (95 % CI: [76.0 %,79.8 %]); 60/75) with 5.8 FPR (95 % CI: [5.0,6.2]). Lesions > 6 mm had a sensitivity of 97.4 % (95 % CI: [94.1 %,97.4 %]); 151/155) with 7.9 FPR (95 % CI: [7.2,8.5]). Feature-fused SSD had a significantly higher overall sensitivity (p = 0.03, t = 2.75) or sensitivity for lesions < 3 mm (p = 0.002, t = 4.49) than baseline SSD, while the overall PPV was similar (p = 0.96, t = -0.02). CONCLUSIONS: The SSD algorithm identified brain metastases on CECT with reasonable accuracy for lesions > 3 mm without pre/post-processing.

Association of volume of self-directed versus assigned interpretive work with diagnostic performance of radiologists: an observational study.

OBJECTIVES: To understand the sources of variability in diagnostic performance among experienced radiologists. DESIGN: All prostate MRI examinations performed between 2016 and 2018 were retrospectively reviewed. SETTING: University hospital in Japan. PARTICIPANTS: Data derived from 334 pathology-proven cases (male, mean age: 70 years; range: 35-90 years) that were interpreted by 10 experienced radiologists were subjected to the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Diagnostic performance measures of the radiologists were compared with candidate factors, including interpretive volume of prostate MRIs, volume of self-directed and assigned total annual interpretive work, and years of experience. The potential influence of fatigue was also evaluated by examining the effect of the report's issue time. RESULTS: There were 186 prostate cancer cases. Performance was based on accuracy, sensitivity and specificity (86%, 85% and 84%, respectively). While performance was not correlated with the volume of prostate MRIs, per se (ρ=-0.15, p=0.69; ρ=-0.01, p=0.99; ρ=-0.33, p=0.36) or the total MRIs assigned for each radiologist (p>0.6) or years of experience (p>0.4), all measures were strongly correlated with voluntary work represented by the interpretive volume of abdominal CTs (r=0.79, p<0.01; r=0.80, p<0.01; r=0.64, p=0.048). The performance did not differ based on the issue time of the report (morning, afternoon and evening) (χ2(2)=3.65, p=0.16). CONCLUSIONS: Greater autonomy, represented as enhanced self-directed interpretive work, was most significantly correlated with the performance of prostate MRI interpretation. The lack of a correlation between the performance and assigned volume confirms the complexity of human learning. Together, these findings support the hypothesis that successful promotion of internal drivers could have a pervasive positive impact on improving diagnostic performance.

Stent placement for benign portal vein stenosis following pancreaticoduodenectomy in a hybrid operating room.

Benign portal vein stenosis is a rare complication following pancreaticoduodenectomy. Because a direct surgical approach to the portal vein is difficult due to severe adhesions following pancreaticoduodenectomy, portal vein stent placement is considered a good treatment option. Herein, we report 3 cases of severe portal vein stenosis following pancreaticoduodenectomy that were treated with portal venous stent placement in a hybrid operating room, combining a conventional operating room with an angiography suite. High-resolution images on digital subtraction angiography provide better contrast and support accurate stent placement compared to using a mobile C-arm.

Proximal total splenic artery embolization for refractory hepatic encephalopathy.

A Japanese woman with a history of Kasai operation for biliary atresia had living-donor liver transplantation at the age of 22. The first episode of refractory HE and late cellular rejection was treated by a high dose of methylprednisolone. The second episode of refractory HE was treated by balloon-occluded retrograde transvenous obliteration for a spleno-renal shunt. However, the third episode of refractory HE occurred 11 years after liver transplantation. The liver cirrhosis and hypersplenism were present with a Child-Pugh score of C-10. Although portal vein flow was hepatopetal, superior mesenteric vein flow regurgitated. We performed proximal total splenic artery embolization (TSAE). Superior mesenteric vein flow changed to a hepatopetal direction and she became clear. At a year after proximal TSAE, her spleen volume had decreased to 589 mL (20% decrease) on computed tomography. She is well and has a Child-Pugh score of 8 without overt HE. We report the first case of refractory HE treated by proximal TSAE that is a possible less invasive treatment option for a selected patient.

Double-Balloon-Assisted n-Butyl-2-Cyanoacrylate Embolization of Intrahepatic Arterioportal Shunt Prior to Chemoembolization of Hepatocellular Carcinoma.

A case of multiple hepatocellular carcinomas with a severe intrahepatic arterioportal shunt that was successfully embolized with n-butyl-2-cyanoacrylate with coaxial double-balloon occlusion prior to transcatheter arterial chemoembolization is presented. A proximal balloon positioned at the proper hepatic artery was used for flow control, and a coaxial microballoon, positioned in the closest of three arterial feeding branches to the arterioportal shunt, was used to control the delivery of n-butyl-2-cyanoacrylate. This coaxial double-balloon technique can prevent proximal embolization and distal migration of n-butyl-2-cyanoacrylate and enable precise control of the distribution of n-butyl-2-cyanoacrylate. It could also be applicable to n-butyl-2-cyanoacrylate embolization for other than intrahepatic arterioportal shunt.

Association between iron content and gray matter missegmentation with voxel-based morphometry in basal ganglia.

PURPOSE: To show an association between T2-weighted signal intensity (T2-SI) variation and missegmentation in the putamen of healthy adults, using 3.0-tesla magnetic resonance scanner and voxel-based morphomery (VBM). MATERIALS AND METHODS: Contiguous sagittal T1-weighted images and axial T2-weighted images of the brain were obtained from 1380 healthy participants using a 3.0 Tesla (T) MR scanner. After image preprocessing with Statistical Parametric Mapping 5, the association between T2-SI ratio (= A/B, where A is the mean of the T2-SI in the putamen, and B is that in the thalamus) variation and gray matter missegmentation was assessed using VBM. RESULTS: A significant positive correlation was revealed between T2-SI ratio and bilateral putamen volume on the gray matter images. In addition, we found a significant negative correlation between T2-SI ratio and bilateral putamen volume on the white matter images. We consider that these results show the influence of missegmentation. CONCLUSION: To the best of our knowledge, this is the first VBM study to demonstrate an association between T2-SI variation and gray matter missegmentation. These results indicate the possibility that VBM may be more affected by individual differences in iron content levels than by individual differences in tissue volumes if detected-regions with VBM contained substantial iron deposition.

Detection of liver metastasis: is diffusion-weighted imaging needed in Gd-EOB-DTPA-enhanced MR imaging for evaluation of colorectal liver metastases?

PURPOSE: We compared diagnostic ability for detecting hepatic metastases between gadolinium ethoxy benzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) on a 1.5-T system, and determined whether DWI is necessary in Gd-EOB-DTPA-enhanced MRI for diagnosing colorectal liver metastases. MATERIALS AND METHODS: We assessed 29 consecutive prospectively enrolled patients with suspected metachronous colorectal liver metastases; all patients underwent surgery and had preoperative Gd-EOB-DTPA-enhanced MRI. Overall detection rate, sensitivity for detecting metastases and benign lesions, positive predictive value, and diagnostic accuracy (Az value) were compared among three image sets [unenhanced MRI (DWI set), Gd-EOB-DTPA-enhanced MRI excluding DWI (EOB set), and combined set]. RESULTS: Gd-EOB-DTPA-enhanced MRI yielded better overall detection rate (77.8-79.0 %) and sensitivity (87.1-89.4 %) for detecting metastases than the DWI set (55.9 % and 64.7 %, respectively) for one observer (P < 0.001). No statistically significant difference was seen between the EOB and combined sets, although several metastases were newly detected on additional DWI. CONCLUSIONS: Gd-EOB-DTPA-enhanced MRI yielded a better overall detection rate and higher sensitivity for detecting metastases compared with unenhanced MRI. Additional DWI may be able to reduce oversight of lesions in Gd-EOB-DTPA-enhanced 1.5-T MRI for detecting colorectal liver metastases.

Fate of hypointense lesions on Gd-EOB-DTPA-enhanced magnetic resonance imaging.

PURPOSE: To investigate the natural outcome and clinical implication of hypointense lesions in the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI. MATERIALS AND METHODS: Forty patients underwent Gd-EOB-DTPA-enhanced MRI for preoperative evaluation of HCC. Hypointense lesions in the hepatobiliary phase that were hypovascular 5mm of more were extracted for follow-up. We performed a longitudinal study retrospectively for these lesions regardless of whether classical HCC developed or emerged in a different area from that of the lesions being followed. RESULTS: Thirty one patients displayed 130 hypointense lesions on MRI and only nine showed no hypointense lesions. In total, 17 (13.1%) of 130 hypointense lesions on MRI developed into classical HCC. The cumulative rates for these lesions to develop into classical HCC were 3.2% at 1 year, 11.1% at 2 years and 15.9% at 3 years. The total occurrence rates of classical HCC (25.8% at 1 year, 52.6% at 2 years and 76.4% at 3 years) were higher compared to those regarding only occurrence of classical HCC from hypointense lesions on MRI (10.0% at 1 year, 35.6% at 2 years and 44.6% at 3 years), although no significant difference was observed (p=0.073). CONCLUSIONS: Hypointense lesions that are detected in the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI have some malignant potential, although treating these lesions aggressively in patients who already have HCC may be too severe.

Comparison of CT findings of biliary tract changes with autoimmune pancreatitis and extrahepatic bile duct cholangiocarcinoma.

PURPOSE: To retrospectively evaluate criteria for differentiating biliary tract changes in autoimmune pancreatitis (AIP-BTC) from extrahepatic cholangiocarcinoma (ECCA) based on CT findings and to determine predictors for differentiation between the two disorders. MATERIALS AND METHODS: CT findings of 22 patients with AIP-BTC and 45 patients with ECCA, both with positive CT findings in the biliary system, were retrospectively assessed. The images were assessed for presence of biliary obstruction, diameter of the maximally dilated biliary duct, maximum thickness of the involved duct, presence of masses inside or around the involved ducts, lengths of the biliary lesions, concentricity of wall thickening, multifocality of the lesion, and degree of lesion enhancement. RESULTS: Compared with AIP-BTC, ECCA was significantly more frequently associated with biliary obstruction (p = 0.0037), shorter lengths of the biliary lesions (p = 0.0036), and masses (p < 0.001). No significant differences were found for other items. CONCLUSION: Presence of obstructive dilatation of the bile ducts and intraluminal or peri-ductal masses and length of the thickened wall may help differentiate between AIP-BTC and ECCA.