Diagnostic yield of contrast-enhanced abdominal staging CT in patients with initially diagnosed breast cancer.

PURPOSE: To estimate the diagnostic yield (DY) of abdominal staging CT for detecting breast cancer liver metastasis (BCLM) in patients with initially diagnosed breast cancer and to determine the indications for abdominal staging CT. METHODS: Patients with newly diagnosed breast cancer who underwent abdominal CT as an initial staging work-up between January 2019 and December 2020 were retrospectively analyzed. DY was calculated and analyzed according to patient age, type of treatments, histologic type, histologic grade, lymphovascular invasion, Ki-67 status, hormone receptor status, subtype, and the American Joint Committee on Cancer anatomical staging. RESULTS: A total of 2056 patients (mean age, 51 ± 11 years) were included. The DY of abdominal staging CT for detecting BCLM was 1.1 % (22 of 2056). DY was significantly higher in stage III than in stage I or II cancers (3.9 % [18 of 467] vs. 0 % [0 of 412] or 0.4 % [4 of 1158], respectively, p < .001), and in human epidermal growth factor receptor-2 (HER2)-enriched cancers than in luminal or triple negative cancers (2.9 % [16 of 560] vs. 0.4 % [4 of 1090] or 0.5 % [2 of 406], respectively, p < .001). CONCLUSIONS: The DY of abdominal staging CT for detecting BCLM was low among all patients with initially diagnosed breast cancer. However, although abdominal staging CT for detecting BCLM is probably unnecessary in all patients, it can be clinically useful in patients with stage III or human epidermal growth factor receptor-2-enriched breast cancers.

Long-term prognostic value of the GenesWell BCT score in Asian women with hormone receptor-positive/HER2-negative early breast cancer.

BACKGROUND: Accurate prediction of the risk of recurrence is crucial for optimal treatment decisions in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. The GenesWell BCT is a molecular assay to predict the 10-year risk of distant metastasis. In this study, we evaluated the long-term prognostic value of the GenesWell BCT assay. METHODS: The BCT score was assessed in patients with HR-positive/HER2-negative early breast cancer who did not receive chemotherapy. We compared the 15-year distant metastasis-free survival (DMFS) between risk groups classified based on the BCT score. The risk of early (0-5 years) and late (5-15 years) recurrence was evaluated based on the BCT score classification. RESULTS: According to the BCT score, 366 patients from Japan and Korea were categorized as BCT low risk (83.6%) and high risk (16.4%) for distant metastasis. Median follow-up time was 17.4 years. The 15-year DMFS rate was significantly lower in the BCT high-risk group (63.3%) than in the BCT low-risk group (93.6%) (P < 0.001). The BCT risk group was an independent prognostic factor for 15-year DMFS (hazard ratio, 4.59; 95% confidence interval 2.13-9.88; P < 0.001). Furthermore, the BCT score was a significant predictor of late recurrence (5-15 years) in patients aged ≤ 50 years and those aged > 50 years, and added prognostic information to traditional clinical prognostic factors. CONCLUSION: The BCT score can identify patients at low risk for recurrence who may not require adjuvant chemotherapy or extended endocrine therapy, regardless of age.

Survey of clinicians on the use of adjuvant therapy for premenopausal women with breast cancer.

PURPOSE: Considering prognostic and anatomic stages in early-stage premenopausal patients with breast cancer, clinicians decide on performing the multigene assay, adjuvant chemotherapy, or ovarian function suppression (OFS). This decision is also based on genetic information related to hormone receptor-positive and human epidermal growth factor receptor 2 negative results. We aimed to determine the tendency to use adjuvant therapy in clinical practice. METHODS: From April to May 2022, clinicians of the Korean Breast Cancer Society responded to a web-based survey. The survey included 62 multiple-choice questions mainly on decision-making under different pathologic conditions. RESULTS: Among 92 responding clinicians, 91.3% were breast surgeons. For 35-year-old patients (pT2N0 and Ki-67 50% profile), 96.8% of clinicians selected chemotherapy, whereas 50.7% selected chemotherapy for patients with pT1N0, Ki-67 10%, and without Oncotype Dx (ODX). Only 35.6% selected chemotherapy for 47-year-old patients with the same profiles, while 84.3% and 49.1% chose chemotherapy with ODX recurrence score 21 and 16, respectively. More clinicians selected tamoxifen (TMX) plus OFS than aromatase inhibitor (AI) plus OFS for 5 years of endocrine therapy in patients with adjuvant chemotherapy regardless of genomic and clinical risks. However, for the same patients without adjuvant chemotherapy, more clinicians selected AI plus OFS. A longer duration of additional OFS and TMX was selected in patients with high clinical and genomic risks, and the duration of OFS was relatively shorter in older patients. CONCLUSION: The decision regarding adjuvant therapy should be made considering clinical and genomic risks and age, and clinicians should consult with patients about adverse effects and compliance.

Deep Features Aggregation-Based Joint Segmentation of Cytoplasm and Nuclei in White Blood Cells.

White blood cells (WBCs), also known as leukocytes, are one of the valuable parts of the blood and immune system. Typically, pathologists use microscope for the manual inspection of blood smears which is a time-consuming, error-prone, and labor-intensive procedure. To address these issues, we present two novel shallow networks: a leukocyte deep segmentation network (LDS-Net) and leukocyte deep aggregation segmentation network (LDAS-Net) for the joint segmentation of cytoplasm and nuclei in WBC images. LDS-Net is a shallow architecture with three downsampling stages and seven convolution layers. LDAS-Net is an extended version of LDS-Net that utilizes a novel pool-less low-level information transfer bridge to transfer low-level information to the deep layers of the network. This information is aggregated with deep features in a dense feature concatenation block to achieve accurate cytoplasm and nuclei joint segmentation. We evaluated our developed architectures on four WBC publicly available datasets. For cytoplasmic segmentation in WBCs, the proposed method achieved the dice coefficients of 98.97%, 99.0%, 96.05%, and 98.79% on Datasets 1, 2, 3, and 4, respectively. For nuclei segmentation, the dice coefficients of 96.35% and 98.09% are achieved for Datasets 1 and 2, respectively. Proposed method outperforms state-of-the-art methods with superior computational efficiency and requires only 6.5 million trainable parameters.

Multilevel Deep-Aggregated Boosted Network to Recognize COVID-19 Infection from Large-Scale Heterogeneous Radiographic Data.

In the present epidemic of the coronavirus disease 2019 (COVID-19), radiological imaging modalities, such as X-ray and computed tomography (CT), have been identified as effective diagnostic tools. However, the subjective assessment of radiographic examination is a time-consuming task and demands expert radiologists. Recent advancements in artificial intelligence have enhanced the diagnostic power of computer-aided diagnosis (CAD) tools and assisted medical specialists in making efficient diagnostic decisions. In this work, we propose an optimal multilevel deep-aggregated boosted network to recognize COVID-19 infection from heterogeneous radiographic data, including X-ray and CT images. Our method leverages multilevel deep-aggregated features and multistage training via a mutually beneficial approach to maximize the overall CAD performance. To improve the interpretation of CAD predictions, these multilevel deep features are visualized as additional outputs that can assist radiologists in validating the CAD results. A total of six publicly available datasets were fused to build a single large-scale heterogeneous radiographic collection that was used to analyze the performance of the proposed technique and other baseline methods. To preserve generality of our method, we selected different patient data for training, validation, and testing, and consequently, the data of same patient were not included in training, validation, and testing subsets. In addition, fivefold cross-validation was performed in all the experiments for a fair evaluation. Our method exhibits promising performance values of 95.38%, 95.57%, 92.53%, 98.14%, 93.16%, and 98.55% in terms of average accuracy, F-measure, specificity, sensitivity, precision, and area under the curve, respectively and outperforms various state-of-the-art methods.

SlimDeblurGAN-Based Motion Deblurring and Marker Detection for Autonomous Drone Landing.

Deep learning-based marker detection for autonomous drone landing is widely studied, due to its superior detection performance. However, no study was reported to address non-uniform motion-blurred input images, and most of the previous handcrafted and deep learning-based methods failed to operate with these challenging inputs. To solve this problem, we propose a deep learning-based marker detection method for autonomous drone landing, by (1) introducing a two-phase framework of deblurring and object detection, by adopting a slimmed version of deblur generative adversarial network (DeblurGAN) model and a You only look once version 2 (YOLOv2) detector, respectively, and (2) considering the balance between the processing time and accuracy of the system. To this end, we propose a channel-pruning framework for slimming the DeblurGAN model called SlimDeblurGAN, without significant accuracy degradation. The experimental results on the two datasets showed that our proposed method exhibited higher performance and greater robustness than the previous methods, in both deburring and marker detection.

Deep Residual CNN-Based Ocular Recognition Based on Rough Pupil Detection in the Images by NIR Camera Sensor.

Accurate segmentation of the iris area in input images has a significant effect on the accuracy of iris recognition and is a very important preprocessing step in the overall iris recognition process. In previous studies on iris recognition, however, the accuracy of iris segmentation was reduced when the images of captured irises were of low quality due to problems such as optical and motion blurring, thick eyelashes, and light reflected from eyeglasses. Deep learning-based iris segmentation has been proposed to improve accuracy, but its disadvantage is that it requires a long processing time. To resolve this problem, this study proposes a new method that quickly finds a rough iris box area without accurately segmenting the iris region in the input images and performs ocular recognition based on this. To address this problem of reduced accuracy, the recognition is performed using the ocular area, which is a little larger than the iris area, and a deep residual network (ResNet) is used to resolve the problem of reduced recognition rates due to misalignment between the enrolled and recognition iris images. Experiments were performed using three databases: Institute of Automation Chinese Academy of Sciences (CASIA)-Iris-Distance, CASIA-Iris-Lamp, and CASIA-Iris-Thousand. They confirmed that the method proposed in this study had a higher recognition accuracy than existing methods.

Deep RetinaNet-Based Detection and Classification of Road Markings by Visible Light Camera Sensors.

Detection and classification of road markings are a prerequisite for operating autonomous vehicles. Although most studies have focused on the detection of road lane markings, the detection and classification of other road markings, such as arrows and bike markings, have not received much attention. Therefore, we propose a detection and classification method for various types of arrow markings and bike markings on the road in various complex environments using a one-stage deep convolutional neural network (CNN), called RetinaNet. We tested the proposed method in complex road scenarios with three open datasets captured by visible light camera sensors, namely the Malaga urban dataset, the Cambridge dataset, and the Daimler dataset on both a desktop computer and an NVIDIA Jetson TX2 embedded system. Experimental results obtained using the three open databases showed that the proposed RetinaNet-based method outperformed other methods for detection and classification of road markings in terms of both accuracy and processing time.

Risk Factors for Gallbladder Stone Formation after Gastric Cancer Surgery.

PURPOSE: Although an increased incidence of gallbladder (GB) stone formation after gastrectomy has been reported, its etiology remains uncertain. The goal of this study was to explore the incidence of gallstone formation after gastrectomy in gastric cancer patients and investigate the risk factors therein. MATERIALS AND METHODS: Medical records of patients who underwent curative gastrectomy, performed by a single surgeon between August 2012 and December 2015 at the Asan Medical Center, were retrospectively reviewed. Baseline characteristics and surgical outcomes, including GB stone gallstone formation after gastrectomy, were analyzed. RESULTS: Of 561 patients included in the study, 36 presented with GB stone formation after gastrectomy for gastric cancer. The incidence of gallstone formation was 6.4%. The mean interval between gallstone formation and gastrectomy was 21.9 months. In multivariate analyses, the incidence of gallstone formation increased in patients 63 years or older, with greater than 6.2 kg weight loss in the first 6 months after the procedure, a preoperative serum total bilirubin level greater than 0.5 mg/dL, and in patients who did not receive adjuvant chemotherapy. CONCLUSIONS: This study presented risk factors for GB stone formation after gastric cancer surgery, and special attention should be afforded to patients with such risk factors.

Deep Learning-Based Enhanced Presentation Attack Detection for Iris Recognition by Combining Features from Local and Global Regions Based on NIR Camera Sensor.

Iris recognition systems have been used in high-security-level applications because of their high recognition rate and the distinctiveness of iris patterns. However, as reported by recent studies, an iris recognition system can be fooled by the use of artificial iris patterns and lead to a reduction in its security level. The accuracies of previous presentation attack detection research are limited because they used only features extracted from global iris region image. To overcome this problem, we propose a new presentation attack detection method for iris recognition by combining features extracted from both local and global iris regions, using convolutional neural networks and support vector machines based on a near-infrared (NIR) light camera sensor. The detection results using each kind of image features are fused, based on two fusion methods of feature level and score level to enhance the detection ability of each kind of image features. Through extensive experiments using two popular public datasets (LivDet-Iris-2017 Warsaw and Notre Dame Contact Lens Detection 2015) and their fusion, we validate the efficiency of our proposed method by providing smaller detection errors than those produced by previous studies.

Evaluation of gallbladder and common bile duct size and appearance by computed tomography in dogs.

The feasibility of using computed tomography (CT) to identify the common bile duct (CBD) and comparison with ultrasonography (US) results were evaluated in normal beagle dogs and dogs without hepatobiliary and pancreatic diseases. In addition, CBD diameters were obtained from CT at the level of the porta hepatis and the duodenal papilla level in dogs with underlying diseases that may cause cholestasis. US is a useful modality in the estimation of gallbladder volume because ejection fraction and CBD diameter from US were not significantly different from those of CT. The normal biliary tract was visible on CT images in 68% of the normal dog group. CBD diameter was not over 3 mm and 3.5 mm at the porta hepatis and duodenal papilla levels, respectively in normal dogs weighing less than 15 kg. Dogs suspected to have cholestasis associated with hepatobiliary or pancreatic diseases had significantly larger CBD than that in normal dogs.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

Imaging characteristics of persistent left cranial vena cava incidentally diagnosed with computed tomography in dogs.

Persistent left cranial vena cava (PLCVC) is an uncommon congenital thoracic venous anomaly in dogs. This study examines the clinical and CT findings of dogs diagnosed with PLCVC incidentally. In this study, complete type of PLCVC was diagnosed in 26 dogs with CT angiography. Shih tzu (17 cases) and Pekingese dogs (3 cases) were overrepresented. There was no gender predisposition, and the average age at presentation was 10.3 years. Of 26 dogs, one dog had a bridging vein connecting right and left cranial vena cavae, and another dog showed azygos vein terminating PLCVC. On the thoracic CT images in the third dog, the right cranial vena cava was absent so that right brachiocephalic vein ended to PLCVC. However, the right costocervical vein drained another vein coursing caudally to the right atrium with azygos vein. In conclusion, CT angiography is a very useful method to diagnose PLCVC and variations of related thoracic vein anomalies in dogs.

In vivo gastric residence and gastroprotective effect of floating gastroretentive tablet of DA-9601, an extract of Artemisia asiatica, in beagle dogs.

OBJECTIVE: DA-9601, an extract of Artemisia asiatica containing eupatilin and jaceosidin as active compounds, has been prescribed to treat gastritis in Asia. In recent times, sustained-release, floating gastroretentive (GR) tablets of DA-9601 are available on the market. In the present study, the physical properties and in vitro drug release profile, in vivo gastric residence time, and gastroprotective effect of GR tablet were compared to those of immediate release (IR) tablets of DA-9601. METHOD: In vitro buoyancy behavior (floating lag time and duration) and release profile of eupatilin were assessed in acidic medium. The in vivo intragastric behaviors of the barium sulfate-loaded IR and GR tablets were evaluated in beagle dogs by radiographic studies. Local gastroprotective effect was compared in an experimentally induced gastric lesion in beagle dogs after oral administration of IR (three times per day) or GR (twice daily) tablets for 15 days. RESULTS: Upon contact with gastric juice, a low-density floating tablet (apparent density of 0.93 g/cm(3)) was buoyant on the medium and was upheld for 14 hours, providing sustained drug release profile, whereas the IR tablet disintegrated within 10 minutes, showing complete drug release within 2 hours. In vivo radiographic studies showed that the GR tablet was retained for >4 hours in the stomach. Both DA-9601 formulations remarkably alleviated gastric mucosal injury compared to placebo group, when observed by gastric endoscopy. CONCLUSION: Twice-daily GR tablets exhibited a prolonged gastric residence time and a remarkable mucosal restoration effect in animal models. Therefore, the GR system of DA-9601 could be a substitute dosage form for the treatment of gastritis, while reducing the dosing frequency and thus improving patient compliance.

Optimal scan delay depending on contrast material injection duration in abdominal multi-phase computed tomography of pancreas and liver in normal Beagle dogs.

This study was conducted to establish the values for optimal fixed scan delays and diagnostic scan delays associated with the bolus-tracking technique using various contrast material injection durations in canine abdominal multi-phase computed tomography (CT). This study consisted of two experiments employing the crossover method. In experiment 1, three dynamic scans at the porta hepatis were performed using 5, 10 and 15 sec injection durations. In experiment 2, two CT scans consisting of five multi-phase series with different scan delays of 5 sec intervals for bolus-tracking were performed using 5, 10 and 15 sec injection duration. Mean arrival times to aortic enhancement peak (12.0, 15.6, and 18.6 sec for 5, 10, and 15 sec, respectively) and pancreatic parenchymal peak (17.8, 25.1, and 29.5 sec) differed among injection durations. The maximum mean attenuation values of aortas and pancreases were shown at the scan section with 0 and 5, 0 and 10 and 5 and 10 sec diagnostic scan delays during each injection duration, respectively. The optimal scan delays of the arterial and pancreatic parenchymal phase in multi-phase CT scan using fixed scan delay or bolus-tracking should be determined with consideration of the injection duration.

Contrast enhanced ultrasonography of kidney in conscious and anesthetized beagle dogs.

Contrast enhanced ultrasound (CEUS) is useful to evaluate tissue perfusion in the kidney. In veterinary medicine, sedation or anesthesia may be required in uncooperative or panting patients. The aim of this study was to evaluate and compare the normal kidney perfusion patterns in conscious and anesthetized dogs using CEUS. Eight healthy beagles were used in this study. Scanning was performed in conscious dogs using manual restraint (conscious group), or under general anesthesia using tiletamine-zolazepam and medetomidine (TZM group) or medetomidine (M group). The contrast agent (Sonovue(®)) was administered as an IV bolus. The peak intensity (PI), time to peak enhancement from injection (TTP0) and the time to peak enhancement from the initial rise (TTPup), upslope, downslope and area under the curve (AUC) were analyzed. Compared to the cortical values in the conscious group, TTP0 was significantly delayed in the TZM group, and upslope, TTP0 and TTPup were significantly different in the M group. The AUCs in the TZM and M groups were not different from those in the conscious group. The upslope of renal medullary perfusion was significantly decreased in the TZM and M groups. TTP0 and TTPup were also significantly delayed in these groups. The AUC of the medulla was significantly decreased in the M group. Therefore, TZM is useful as an anesthetic protocol when performing CEUS, and the obtained data may serve as reference values in the evaluation of renal perfusion using CEUS in dogs under anesthesia.

Establishment of optimal scan delay for multi-phase computed tomography using bolus-tracking technique in canine pancreas.

To establish a protocol for a multi-phase computed tomography (CT) of the canine pancreas using the bolus-tracking technique, dynamic scan and multi-phase CT were performed in six normal beagle dogs. The dynamic scan was performed for 60 sec at 1-sec intervals after the injection (4 ml/sec) of a contrast medium, and intervals from aortic enhancement appearance to aortic, pancreatic parenchymal and portal vein peaks were measured. The multi-phase CT with 3 phases was performed three times using a bolus-tracking technique. Scan delays were 0, 15 and 30 in first multi-phase scan; 5, 20 and 35 in second multi-phase scan; and 10, 25 and 40 sec in third multi-phase scan, respectively. Attenuation values and contrast enhancement pattern were analyzed from the aorta, pancreas and portal vein. The intervals from aortic enhancement appearance to aortic, pancreatic parenchymal and portal vein peaks were 3.8 ± 0.7, 8.7 ± 0.9 and 13.3 ± 1.5 sec, respectively. The maximum attenuation values of the aorta, pancreatic parenchyma and portal vein were present at scan sections with no scan delay, a 5-sec delay and a 10-sec delay, respectively. When a multi-phase CT of the canine pancreas is triggered at aortic enhancement appearance using a bolus-tracking technique, the recommended optimal delay times of the arterial and pancreatic parenchymal phases are no scan delay and 5 sec, respectively.

Assessment of experimental saccular aneurysm using selective angiography in common carotid artery of rabbits.

In order to study the treatment of aneurysms, the technique of making experimental aneurysms in laboratory animals must be established. In our study, to examine the feasibility of making experimental aneurysm and selective angiography on the common carotid artery in rabbits and to determine the size of experimental aneurysm after surgery, saccular aneurysms were fashioned on the right common carotid artery in 17 rabbits using a vein pouch technique. Selective angiography of the common carotid artery was performed immediately after surgery, and at 1 week, 4 weeks, and 8 weeks after surgery. Also, histological changes in the aneurysms were observed. In 16 rabbits with established successful experimental aneurysm, no differences were found in diet intake and behavior before and after surgery. The patency of the carotid artery was confirmed by selective angiography. The average size of the aneurysm immediately after surgery was similar to that of 1 week postoperatively in selective angiography, however it increased with time at 4weeks and 8 weeks. Histologically, infiltration of inflammatory cells and hemorrhage were found at the junction of the carotid artery and the vein pouch at 1 week, which disappeared at 4 weeks and 8 weeks. This study suggests experimental saccular aneurysm using the vein pouch technique might form aneurysms similar to that of the human in its properties such as increment of size, and selective angiography might be suitable for assessment of experimental aneurysm. Therefore, this animal model may be suitable for investigating new treatment methodologies for human aneurysms.

Computed tomographic evaluation of cerebral ventricular size in clinically normal calves.

OBJECTIVE: To evaluate lateral ventricular size in clinically normal calves by use of computed tomography and to examine the relationships between ventricular height (Vh), ventricular area (VA), and ventricular volume (VV). ANIMALS: 14 Holstein calves. Procedures-14 calves underwent computed tomography of the head with transverse images acquired from the rostral aspect of the frontal lobe continuing caudally to the level of the foramen magnum. Hemispheric height, Vh, VA, and hemispheric area were measured on images obtained at the level of the interventricular foramen. Ventricular volume was calculated by multiplying the sum of VAs measured on each transverse image by the total slice thickness. The left Vh-to-right Vh ratio was calculated to determine the degree of ventricular asymmetry, which was categorized as normal (ie, symmetric) to minimally asymmetric, mildly asymmetric, or severely asymmetric. RESULTS: Mean +/- SD values for Vh and the Vh-to-hemispheric height ratio were 4.96 +/- 1.56 mm and 7.47%, respectively. The mean VA was 114.29 +/- 47.68 mm(2), and the mean VV was 2,443.50 +/- 1,351.50 mm3. Normal to minimally asymmetric ventricles were identified in 13 calves, and mildly asymmetric ventricles were identified in 1 calf. Significant correlations were found between Vh and VA and between Vh and VV. CONCLUSIONS AND CLINICAL RELEVANCE: These results establish reference values for ventricular size in clinically normal calves and suggest that Vh measurement may be a simple and useful technique for examining size of the cerebral ventricles in calves.

Functional recovery and neural differentiation after transplantation of allogenic adipose-derived stem cells in a canine model of acute spinal cord injury.

In this study, we evaluated if the implantation of allogenic adipose-derived stem cells (ASCs) improved neurological function in a canine spinal cord injury model. Eleven adult dogs were assigned to three groups according to treatment after spinal cord injury by epidural balloon compression: C group (no ASCs treatment as control), V group (vehicle treatment with PBS), and ASC group (ASCs treatment). ASCs or vehicle were injected directly into the injured site 1 week after spinal cord injury. Pelvic limb function after transplantation was evaluated by Olby score. Magnetic resonance imaging, somatosensory evoked potential (SEP), histopathologic and immunohistichemical examinations were also performed. Olby scores in the ASC group increased from 2 weeks after transplantation and were significantly higher than C and V groups until 8 weeks (p < 0.05). However, there were no significant differences between the C and V groups. Nerve conduction velocity based on SEP was significantly improved in the ASC group compared to C and V groups (p < 0.05). Positive areas for Luxol fast blue staining were located at the injured site in the ASC group. Also, GFAP, Tuj-1 and NF160 were observed immunohistochemically in cells derived from implanted ASCs. These results suggested that improvement in neurological function by the transplantation of ASCs in dogs with spinal cord injury may be partially due to the neural differentiation of implanted stem cells.