Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction.

PURPOSE: We investigated whether the quality of high-resolution computed tomography (CT) images of the temporal bone improves with deep learning reconstruction (DLR) compared with hybrid iterative reconstruction (HIR). METHODS: This retrospective study enrolled 36 patients (15 men, 21 women; age, 53.9 ± 19.5 years) who had undergone high-resolution CT of the temporal bone. Axial and coronal images were reconstructed using DLR, HIR, and filtered back projection (FBP). In qualitative image analyses, two radiologists independently compared the DLR and HIR images with FBP in terms of depiction of structures, image noise, and overall quality, using a 5-point scale (5 = better than FBP, 1 = poorer than FBP) to evaluate image quality. The other two radiologists placed regions of interest on the tympanic cavity and measured the standard deviation of CT attenuation (i.e., quantitative image noise). Scores from the qualitative and quantitative analyses of the DLR and HIR images were compared using, respectively, the Wilcoxon signed-rank test and the paired t-test. RESULTS: Qualitative and quantitative image noise was significantly reduced in DLR images compared with HIR images (all comparisons, p ≤ 0.016). Depiction of the otic capsule, auditory ossicles, and tympanic membrane was significantly improved in DLR images compared with HIR images (both readers, p ≤ 0.003). Overall image quality was significantly superior in DLR images compared with HIR images (both readers, p < 0.001). CONCLUSION: Compared with HIR, DLR provided significantly better-quality high-resolution CT images of the temporal bone.

Deep learning reconstruction for improving the visualization of acute brain infarct on computed tomography.

PURPOSE: This study aimed to investigate the impact of deep learning reconstruction (DLR) on acute infarct depiction compared with hybrid iterative reconstruction (Hybrid IR). METHODS: This retrospective study included 29 (75.8 ± 13.2 years, 20 males) and 26 (64.4 ± 12.4 years, 18 males) patients with and without acute infarction, respectively. Unenhanced head CT images were reconstructed with DLR and Hybrid IR. In qualitative analyses, three readers evaluated the conspicuity of lesions based on five regions and image quality. A radiologist placed regions of interest on the lateral ventricle, putamen, and white matter in quantitative analyses, and the standard deviation of CT attenuation (i.e., quantitative image noise) was recorded. RESULTS: Conspicuity of acute infarct in DLR was superior to that in Hybrid IR, and a statistically significant difference was observed for two readers (p ≤ 0.038). Conspicuity of acute infarct with time from onset to CT imaging at < 24 h in DLR was significantly improved compared with Hybrid IR for all readers (p ≤ 0.020). Image noise in DLR was significantly reduced compared with Hybrid IR with both the qualitative and quantitative analyses (p < 0.001 for all). CONCLUSION: DLR in head CT helped improve acute infarct depiction, especially those with time from onset to CT imaging at < 24 h.

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal canal stenosis using computed tomography (CT) compared with hybrid iterative reconstruction (hybrid IR). METHODS: This retrospective study included 33 patients (16 male patients; mean age, 57.7 ± 18.4 years) who underwent cervical spine CT. Images were reconstructed using DLR and hybrid IR. In the quantitative analyses, noise was recorded by placing the regions of interest on the trapezius muscle. In the qualitative analyses, 2 radiologists evaluated the depiction of structures, image noise, overall image quality, and degree of cervical canal stenosis. We additionally evaluated the agreement between MRI and CT in 15 patients for whom preoperative cervical MRI was available. RESULTS: Image noise was less with DLR than hybrid IR in the quantitative ( P ≤ 0.0395) and subjective analyses ( P ≤ 0.0023), and the depiction of most structures was improved ( P ≤ 0.0052), which resulted in better overall quality ( P ≤ 0.0118). Interobserver agreement in the assessment of spinal canal stenosis with DLR (0.7390; 95% confidence interval [CI], 0.7189-0.7592) was superior to that with hybrid IR (0.7038; 96% CI, 0.6846-0.7229). As for the agreement between MRI and CT, significant improvement was observed for 1 reader with DLR (0.7910; 96% CI, 0.7762-0.8057) than hybrid IR (0.7536; 96% CI, 0.7383-0.7688). CONCLUSIONS: Deep learning reconstruction provided better quality cervical spine CT images in the evaluation of cervical spinal stenosis than hybrid IR.

Detection of Vertebral Mass and Diagnosis of Spinal Cord Compression in Computed Tomography With Deep Learning Reconstruction: Comparison With Hybrid Iterative Reconstruction.

PURPOSE: To compare the impact of deep learning reconstruction (DLR) and hybrid-iterative reconstruction (hybrid-IR) on vertebral mass depiction, detection, and diagnosis of spinal cord compression on computed tomography (CT). METHODS: This retrospective study included 29 and 20 patients with and without vertebral masses. CT images were reconstructed using DLR and hybrid-IR. Three readers performed vertebral mass detection tests and evaluated the presence of spinal cord compression, the depiction of vertebral masses, and image noise. Quantitative image noise was measured by placing regions of interest on the aorta and spinal cord. RESULTS: Deep learning reconstruction tended to improve the performance of readers with less diagnostic imaging experience in detecting vertebral masses (area under the receiver operating characteristic curve [AUC] = .892-.966) compared with hybrid-IR (AUC = .839-.917). Diagnostic performance in evaluating spinal cord compression in DLR (AUC = .887-.995) also improved compared with that in hybrid-IR (AUC = .866-.942) for some readers. The depiction of vertebral masses and subjective image noise in DLR were significantly improved compared with those in hybrid-IR (P < .041). Quantitative image noise in DLR was also significantly reduced compared with that in hybrid-IR (P < .001). CONCLUSION: Deep learning reconstruction improved the depiction of vertebral masses, which resulted in a tendency to improve the performance of CT compared to hybrid-IR in detecting vertebral masses and diagnosing spinal cord compression for some readers.

An automated screening model for aortic emergencies using convolutional neural networks and cropped computed tomography angiography images of the aorta.

PURPOSE: Patients with aortic emergencies, such as aortic dissection and rupture, are at risk of rapid deterioration, necessitating prompt diagnosis. This study introduces a novel automated screening model for computed tomography angiography (CTA) of patients with aortic emergencies, utilizing deep convolutional neural network (DCNN) algorithms. METHODS: Our model (Model A) initially predicted the positions of the aorta in the original axial CTA images and extracted the sections containing the aorta from these images. Subsequently, it predicted whether the cropped images showed aortic lesions. To compare the predictive performance of Model A in identifying aortic emergencies, we also developed Model B, which directly predicted the presence or absence of aortic lesions in the original images. Ultimately, these models categorized patients based on the presence or absence of aortic emergencies, as determined by the number of consecutive images expected to show the lesion. RESULTS: The models were trained with 216 CTA scans and tested with 220 CTA scans. Model A demonstrated a higher area under the curve (AUC) for patient-level classification of aortic emergencies than Model B (0.995; 95% confidence interval [CI], 0.990-1.000 vs. 0.972; 95% CI, 0.950-0.994, respectively; p = 0.013). Among patients with aortic emergencies, the AUC of Model A for patient-level classification of aortic emergencies involving the ascending aorta was 0.971 (95% CI, 0.931-1.000). CONCLUSION: The model utilizing DCNNs and cropped CTA images of the aorta effectively screened CTA scans of patients with aortic emergencies. This study would help develop a computer-aided triage system for CT scans, prioritizing the reading for patients requiring urgent care and ultimately promoting rapid responses to patients with aortic emergencies.

Effects of the dipeptides comprising leucine and lysine on lifespan and age-related stress in Caenorhabditis elegans.

The aging process is affected by various stressors. An increase in oxidative stress is related to the impairment of physiological functions and enhancement of glycative stress. Food-derived bioactive peptides have various physiological functions, including antioxidant activities. Dipeptides comprising Leu and Lys (LK and KL, respectively) have been isolated from foods; however, their physiological properties remain unclear. In this study, we investigated the antioxidant/antiglycation activity of dipeptides and their antiaging effects using Caenorhabditis elegans (C. elegans). Both dipeptides showed antioxidant activities against several reactive oxygen species (ROS) in vitro. In particular, the scavenging activity of LK against superoxide radicals was higher than KL did. Moreover, dipeptides suppressed advanced glycation end products (AGEs) formation in the BSA-glucose model. In the lifespan assays using wild-type C. elegans, both LK and KL significantly prolonged the mean lifespan by 20.9% and 11.7%, respectively. In addition, LK decreased intracellular ROS and superoxide radical levels in C. elegans. Blue autofluorescence, an indicator of glycation in C. elegans with age, was also suppressed by LK. These results suggest that dipeptides, notably LK, show an antiaging effect by suppressing oxidative and glycative stress. Our findings suggest that such dipeptides can be used as a novel functional food ingredient. Food-derived dipeptide Leu-Lys (LK) and Lys-Leu (KL) exert antioxidant and antiglycation activity in vitro. Treatment with LK prolonged the mean lifespan and maximum lifespan of C. elegans more than that of KL. Intracellular ROS and blue autofluorescence levels (indicator of aging) were suppressed by LK.

Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

Purpose: To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). Methods: In this retrospective study, axial images of 26 patients who underwent CT without arm elevation were reconstructed using DLR, Hybrid-IR, and FBP. Streak artifact index (SAI) was calculated by dividing the standard deviation of CT attenuation in the liver or spleen by that in fat. Two other blinded radiologists evaluated streak artifacts on images (in the liver, spleen, and kidney), depiction of liver vessels, subjective image noise, and overall quality. They were also asked to detect space-occupying lesions other than cysts in the liver, spleen, and kidney. Results: The SAI (liver/spleen) in DLR images was significantly reduced compared with Hybrid-IR and FBP. Regarding qualitative image analysis, streak artifacts in the 3 organs, qualitative image noise, and overall quality in DLR images were rated by both readers as significantly improved compared with Hybrid-IR (P ≤ .012) and FBP (P < .001). Both blinded readers detected more lesions on DLR images than on Hybrid-IR and FBP ones. Conclusion: DLR resulted in significantly better-quality abdominal CT images in patients scanned without elevating their arms with reducing streak artifacts compared with Hybrid-IR and FBP.

Localization of the central sulcus using the distinctive high signal intensity of the paracentral lobule on T1-weighted images.

PURPOSE: The central sulcus is an important landmark in the brain. This study aimed to investigate the distinctive signal of the paracentral lobule (PL) on T1-weighted images (T1WIs; the white PL sign) and evaluate its usefulness as a new method of identifying the central sulcus. METHODS: T1WIs of the brain of 96 participants (age, 58.9 ± 17.9 years; range, 8-87 years) scanned at 3-T MR system were retrospectively reviewed. First, we qualitatively analyzed the signal of the cortex of the PL by comparing it with that of the ipsilateral superior frontal gyrus on a 4-point grading score. Second, we compared the cortical signal intensity and gray/white-matter contrast between the PL and superior frontal gyrus. Third, we evaluated the usefulness of the PL signal for identifying the central sulcus. RESULTS: The PL cortex was either mildly hyperintense (grade 2) or definitely hyperintense (grade 3) in comparison with that of superior frontal cortex in all participants. The signal intensity of the PL cortex was significantly higher than that of the superior frontal cortex (p < 0.001), whereas the gray/white-matter contrast of the PL was weaker than that of the superior frontal gyrus (p < 0.001). The central sulci were identified with 94.3% accuracy (181/192) using the new method. CONCLUSION: The white PL sign may be helpful in identifying the central sulcus, and this approach can be recognized as a new method for identification of the central sulcus.

Differential diagnosis of thymic epithelial neoplasms on computed tomography using the diameter of the thymic vein.

ABSTRACT: Although differentiating benign and malignant thymic epithelial lesions is important to avoid unnecessary treatment and predict prognosis, it is challenging because of overlaps in the chest computed tomography (CT) findings. In this study, we investigated whether the diameter of the thymic vein and other CT findings could differentiate between benign (thymoma and thymic cysts) and malignant (thymic carcinoma, [TCa]) lesions.We conducted a retrospective study across two tertiary referral hospitals in Japan between November 2009 and June 2018. We included 12 patients with TCa, 34 patients with thymomas, and 17 patients with thymic cysts. We analyzed the receiver operating characteristic (ROC) curve to determine the best cut-off values and performed univariate and multivariate analyses of CT findings to distinguish TCa from other benign lesions. Post-hoc analysis was performed for the maximum short axis of the thymic vein using the Mann-Whitney U test, and the number of the maximum short axis of the thymic vein ≥ the cutoff was determined using the Fisher exact test with a family-wise error-correction using Bonferroni's method.ROC analysis showed that a maximum short axis of the thymic vein ≥2 mm was considerably more frequent in TCa than in the other lesions (P < .001 for both), with 83% sensitivity and 86% specificity. Univariate and multivariate analyses revealed the association with TCa of the number of the maximum short axis of the thymic vein ≥2 mm (P = .005, multivariate generalized linear model analysis), ill-defined margin (P = .001), and mediastinal lymphadenopathy (P < .001). Thymic vein diameter was in descendimg order of TCa > thymoma > thymic cysts with statistically significant differences between the groups (Ps < .05).Thymic vein diameter was significantly longer in TCa than in thymoma and thymic cysts. Measurement of the maximum short axis of the thymic vein could be a powerful diagnostic tool to differentiate TCa from thymoma and thymic cysts.

Physiological 2-deoxy-2-[fluorine-18] fluoro-D-glucose accumulation in the thenar eminence in adults: a single-center retrospective study.

OBJECTIVE: This study evaluated the frequency, and effect of physiological 2-deoxy-2-[fluorine-18] fluoro-D-glucose (FDG) tracer injection and its association with the penetration rates of mobile devices. METHODS: This retrospective analysis included 213 patients (mean age ± standard deviation, 66.2 ± 14.1 years; range 23-93 years; 125 men) who underwent FDG-positron emission tomography examination. Elevated FDG activity in the thenar eminence with maximum standardized uptake value (SUVmax) ≥ 2.5 was considered positive. Differences according to age, sex, laterality, and tracer injection side were evaluated using Fisher's exact test. Associations were assessed using Pearson's correlation coefficient. RESULTS: Twenty-three percent (49/213) of the patients had elevated FDG activity in the thenar eminence (mean SUVmax, 3.50 ± 1.04; range 2.5-6.3), including 18 with bilateral findings. No significant difference existed according to age (< 50 years vs. 50-69 years vs. ≥ 70 years), sex, laterality, or tracer injection side. No significant correlation existed between penetration rates of mobile devices and the findings (p = 0.08). CONCLUSION: Elevated FDG activity in the thenar eminence occurs in adults, regardless of age, sex, laterality, or tracer injection side. This should be considered a common physiological change that does not warrant any further investigation.

Patient with penile metastasis from prostate cancer and survival over 5 years: A case report with longitudinal evaluation using computed tomography and magnetic resonance imaging.

Penile metastasis of malignant tumors is a very rare condition, often occurring as a part of systemic metastases, and is therefore associated with a poor prognosis. Although there have been reports of magnetic resonance imaging findings of penile metastasis, longitudinal imaging changes have not been presented previously. We report a case of a 80-year-old male patient with penile metastasis from prostate adenocarcinoma. First magnetic resonance imaging demonstrated multiple penile nodules in the left corpus cavernosum corpora cavernosa, and these nodules were fused and across the septum of the penis, forming an enlarged, diffusely spreading mass on the follow-up exam 5 years later. In this case, a longitudinal evaluation of magnetic resonance imaging demonstrated the course of the extension of the rare penile metastasis.

CT imaging findings of lenvatinib-induced enteritis.

OBJECTIVES: To evaluate the relationship between abnormal findings on abdomino-pelvic CT and adverse events in oncologic patients treated with lenvatinib, and their relationship with treatment planning. METHODS: This single institutional retrospective study included 58 patients with unresectable hepatocellular carcinoma or unresectable thyroid carcinoma (mean age ± standard deviation 69.6 ± 10.0 years; range 39-84 years; 48 men) who underwent CT between October 2016 and July 2020. Two radiologists who were blinded to clinical information including the presence or absence of diarrhea evaluated the imaging findings, including the presence/absence of enteritis in each intestinal segment. Gastrointestinal adverse events (diarrhea, decreased appetite, nausea, and vomiting) and other drug-induced adverse events requiring treatment or follow-up during lenvatinib treatment were also investigated. The frequency of these adverse events was compared between the patients with and without enteritis using Fisher's exact test or the Mann-Whitney U test. RESULTS: Enteritis was found on CT in the majority (33/58 [56.9%]) of the patients, and most of them (25/33 [75.8%]) showed duodenojejunitis. The frequency of gastrointestinal adverse events (28/33 [84.8%] vs. 13/25 [56.0%], p = 0.009), diarrhea (20/33 [60.6%] vs. 3/25 [12.0%], p < 0.001), and drug interruptions (25/33 [75.8%] vs. 10/25 [40.0%], p = 0.008) and the number of other adverse events (3.9 ± 1.7 vs. 2.3 ± 1.3, p < 0.001) were significantly higher in the patients with enteritis on CT than in those without. CONCLUSIONS: Lenvatinib-induced enteritis frequently involved the duodenum and jejunum and was related to a significantly higher frequency of treatment interruptions and gastrointestinal adverse events.

Imatinib-induced pancreatic hypertrophy in patients with gastrointestinal stromal tumor: Association with overall survival.

OBJECTIVES: To investigate the frequency of imatinib-induced pancreatic complications and determine whether these are survival prognostic factors in patients with gastrointestinal stromal tumor (GIST). METHODS: This retrospective multicenter study included patients with histopathologically diagnosed GIST treated with imatinib who underwent computed tomography (CT) within 100 days before (pretreatment CT) and 500 days after (post-treatment CT) imatinib initiation (January 2004-December 2019). Forty-eight patients (63.0 ± 12.1 years, 30 men) were included. Two blinded radiologists independently measured pancreatic volumes. Pancreatic volume on pretreatment CT was compared with that of the control (within 1 year prior to pretreatment CT) and the first two post-treatment CTs using paired t-tests. Thresholds for pancreatic hypertrophy and atrophy were defined using a log-rank test. The prognostic importance of pancreatic hypertrophy was further analyzed using multivariate Cox proportional hazard regression models. RESULTS: Pancreatic volume was significantly higher for the first post-treatment CT than pretreatment CT (71.5 cm3 vs. 67.4 cm3, P = .027), whereas no significant difference was observed between the pretreatment and control CTs. Optimal thresholds for pancreatic hypertrophy and atrophy were defined as an 22% increase and 30% decrease and found in 20 and three patients, respectively. Pancreatic hypertrophy was significantly associated with reduced survival [hazard ratio = 2.9 (95% confidence interval, 1.3-6.5), P = .0088]. No patients showed serum lipase elevation, nor were they suspected of having acute pancreatitis. CONCLUSION: There was frequent asymptomatic pancreatic swelling in patients with GIST after imatinib treatment, and a ≥22% increase in pancreatic volume was a predictor of reduced survival.