scholarly journals Surgical resection for advanced bisphosphonate-related osteonecrosis of the jaw associated with fibrous dysplasia: a case report

2020 ◽  
Vol 2020 (3) ◽  
Author(s):  
Yurika Murase ◽  
Koji Kishimoto ◽  
Shoko Yoshida ◽  
Yuki Kunisada ◽  
Koichi Kadoya ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Adverse Drug Reaction ◽  
Fibrous Dysplasia ◽  
Surgical Resection ◽  
Osteonecrosis Of The Jaw ◽  
Ct Images ◽  
Osseous Tissue ◽  
Maxillary Bone ◽  
Exposed Bone ◽  
Resistance To Infection

Abstract Bisphosphonate-related osteonecrosis of the jaw (BRONJ) is an adverse drug reaction represented by destruction and/or death of bone. Fibrous dysplasia (FD) is a rare bony disorder characterised by abnormal fibro-osseous tissue that has lowered resistance to infection. Effective treatments for BRONJ that follows FD are unclear. Here, we report that advanced BRONJ associated with FD was successfully treated by surgical resection. A 69-year-old woman, whose left maxillary bone showed a ground glass appearance on computed tomography (CT) images, was taking alendronate. At 1 year after teeth within the abnormal bone were extracted, exposed bone was observed in the extraction sites and CT images revealed separated sequestrums. Under the clinical diagnosis of Stage 2 BRONJ with FD, we performed not only sequestrectomy but also a partial resection of the FD. Thereafter, the healing was uneventful without recurrence. In conclusion, our case suggests that surgical resection is useful for advanced BRONJ associated with FD.

scholarly journals A243 A RETROSPECTIVE REVIEW OF THE RADIOGRAPHIC DIAGNOSIS AND SURGICAL RESECTION RATES OF PANCREATIC SEROUS CYSTS

2021 ◽  
Vol 4 (Supplement_1) ◽  
pp. 300-301
Author(s):  
M Monachese ◽  
S Li ◽  
M Salim ◽  
L Guimaraes ◽  
P D James
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Magnetic Resonance ◽  
Surgical Resection ◽  
Predictive Value ◽  
Resected Specimen ◽  
Cystic Lesions ◽  
Resonance Imaging ◽  
Guided Biopsy ◽  
Magnetic Resonance Imaging Mri

Abstract Background Pancreatic cystic lesions are increasingly identified in persons undergoing abdominal imaging. Serous cystic neoplasms (SCNs) have a very low risk of malignant transformation. Resection of SCNs is not recommended in the absence of related symptoms. The accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) to identify SCNs is not known and may impact clinical care. Aims To evaluate the accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) for the diagnosis of SCN. To see how this can impact the decision to resect suspected SCNs. Methods Retrospective cohort study of patients from the University Health Network with suspected SCNs from 2017–2020 who underwent either a CT or MRI of the abdomen. Reports noting pancreatic cystic lesions were identified and reviewed. Only cases with suspected SCNs were included. Clinical (age, sex, symptoms, treatment) and radiographic (type of imaging, reported cyst characteristics) data was collected. Pathology was reviewed for all cases where the cysts was biopsied or resected during follow-up. The gold standard for the diagnosis for SCN was pathology of resected specimen or EUS-guided biopsy cytopathology showing no evidence of a mucinous lesion, CEA level below 10ug per L and amylase level below 50 U/L. Results 163 patients were included in the study. 99 (61%) were female and 98 (60%) underwent CT scan. EUS-guided biopsy was performed in 24 (15%) of patients and 8 (5%) had surgical resection. Multidisciplinary review was performed in 6 of the 8 cases that went to surgery. Of the resected specimens, 5 (63%) were SCN, 1 was a mucinous cystic lesion, 1 was a neuroendocrine tumor and 1 was a carcinoma. Two patients underwent EUS evaluation prior to surgical resection. In one case SCN was resected when EUS reported an undetermined cyst type. Reasons for surgical resection were: the diagnosis of serous cyst was not definitive (n=5), symptoms (n=2), and high-risk mucinous cystic neoplasm identified on EUS (n=1). Of 30 patients with pathology available, 15 (50%) were confirmed to have a SCN. CT and MRI had a sensitivity, specificity, positive predictive value and negative predictive value of 93%, 25%, 52% and 80%, respectively. Conclusions Surgical resection for SCN lesions is driven by diagnostic uncertainty after cross-sectional imaging. Multidisciplinary review and EUS evaluation may improve diagnostic accuracy and should be considered prior to surgical resection of possible SCN lesions. Funding Agencies None

scholarly journals Multi-Cycle-Consistent Adversarial Networks for Edge Denoising of Computed Tomography Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-16
Author(s):  
Xiaowe Xu ◽  
Jiawei Zhang ◽  
Jinglan Liu ◽  
Yukun Ding ◽  
Tianchen Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Denoising ◽  
Ct Images ◽  
High Dose ◽  
Ct Image ◽  
Paired Data ◽  
High Quality ◽  
Computed Tomography Images ◽  
Significant Difference ◽  
Global Cycle

As one of the most commonly ordered imaging tests, the computed tomography (CT) scan comes with inevitable radiation exposure that increases cancer risk to patients. However, CT image quality is directly related to radiation dose, and thus it is desirable to obtain high-quality CT images with as little dose as possible. CT image denoising tries to obtain high-dose-like high-quality CT images (domain Y ) from low dose low-quality CT images (domain X ), which can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain X (noisy images) and a target domain Y (clean images). Recently, the cycle-consistent adversarial denoising network (CCADN) has achieved state-of-the-art results by enforcing cycle-consistent loss without the need of paired training data, since the paired data is hard to collect due to patients’ interests and cardiac motion. However, out of concerns on patients’ privacy and data security, protocols typically require clinics to perform medical image processing tasks including CT image denoising locally (i.e., edge denoising). Therefore, the network models need to achieve high performance under various computation resource constraints including memory and performance. Our detailed analysis of CCADN raises a number of interesting questions that point to potential ways to further improve its performance using the same or even fewer computation resources. For example, if the noise is large leading to a significant difference between domain X and domain Y , can we bridge X and Y with a intermediate domain Z such that both the denoising process between X and Z and that between Z and Y are easier to learn? As such intermediate domains lead to multiple cycles, how do we best enforce cycle- consistency? Driven by these questions, we propose a multi-cycle-consistent adversarial network (MCCAN) that builds intermediate domains and enforces both local and global cycle-consistency for edge denoising of CT images. The global cycle-consistency couples all generators together to model the whole denoising process, whereas the local cycle-consistency imposes effective supervision on the process between adjacent domains. Experiments show that both local and global cycle-consistency are important for the success of MCCAN, which outperforms CCADN in terms of denoising quality with slightly less computation resource consumption.

Image restoration in computed tomography: restoration of experimental CT images

1992 ◽  
Vol 11 (4) ◽  
pp. 546-553 ◽  
Author(s):  
S. Rathee ◽  
Z.J. Koles ◽  
T.R. Overton
Keyword(s):  
Computed Tomography ◽  
Image Restoration ◽  
Ct Images

The Labyrinthine Portion of the Facial Canal in Patients with Bell's Palsy Investigated by Computed Tomography

1987 ◽  
Vol 28 (1) ◽  
pp. 25-30 ◽  
Author(s):  
K. Wadin ◽  
L. Thomander ◽  
H. Wilbrand
Keyword(s):  
Computed Tomography ◽  
Temporal Bone ◽  
No Value ◽  
Bell’S Palsy ◽  
Ct Images ◽  
Slice Thickness ◽  
Facial Canal ◽  
Bell's Palsy ◽  
Unreliable Method ◽  
Different Parts

The reproducibility of the labyrinthine portion of the facial canal by computed tomography was investigated in 22 patients with Bell's palsy. The CT images were compared with those obtained in 18 temporal bone specimens. Measurements of the diameters of different parts of the facial canal were made on these images and also microscopically in plastic casts of the temporal bone specimens. No marked difference was found between the dimensions of the labyrinthine portion of the facial canal of the involved and healthy temporal bone in the patient, nor did these differ from the dimensions in the specimens. CT of the slender, curved labyrinthine portion was found to be of doubtful value for metric estimation of small differences in width. The anatomic variations of the canal rendered the evaluation more difficult. CT with a slice thickness of 2 mm was of no value for assessment of this part of the canal. Measurement of the diameters of the labyrinthine portion on CT images is an inappropriate and unreliable method for clinical purposes.

scholarly journals Medication-Related Osteonecrosis of the Jaw (MRONJ): Are Antiresorptive Drugs the Main Culprits or Only Accomplices? The Triggering Role of Vitamin D Deficiency

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 561
Author(s):  
Luca Dalle Carbonare ◽  
Monica Mottes ◽  
Maria Teresa Valenti
Keyword(s):  
Vitamin D ◽  
Clinical Condition ◽  
Case Series ◽  
Osteonecrosis Of The Jaw ◽  
First Case ◽  
Vitamin D Levels ◽  
Exposed Bone ◽  
Antiresorptive Drugs ◽  
Almost All

Osteonecrosis of the jaw (ONJ) is a severe clinical condition characterized mostly but not exclusively by an area of exposed bone in the mandible and/or maxilla that typically does not heal over a period of 6–8 weeks. The diagnosis is first of all clinical, but an imaging feedback such as Magnetic Resonance is essential to confirm clinical suspicions. In the last few decades, medication-related osteonecrosis of the jaw (MRONJ) has been widely discussed. From the first case reported in 2003, many case series and reviews have appeared in the scientific literature. Almost all papers concerning this topic conclude that bisphosphonates (BPs) can induce this severe clinical condition, particularly in cancer patients. Nevertheless, the exact mechanism by which amino-BPs would be responsible for ONJ is still debatable. Recent findings suggest a possible alternative explanation for BPs role in this pattern. In the present work we discuss how a condition of osteomalacia and low vitamin D levels might be determinant factors.

Enthesopathy of the Bicipital Tuberosity of the Radius Treated Under Intraoperative Computed Tomography

2021 ◽  
Author(s):  
Ryosuke Ikeguchi ◽  
Takashi Noguchi ◽  
Maki Ando ◽  
Koichi Yoshimoto ◽  
Diachi Sakamoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Surgical Treatment ◽  
Surgical Resection ◽  
Tendon Rupture ◽  
Computed Tomography Scan ◽  
Forearm Rotation ◽  
Elbow Pain ◽  
Intraoperative Computed Tomography ◽  
Tomography Scan ◽  
Bicipital Tuberosity

Abstract There is no report of the application of intraoperative computed tomography to the extremities, and its usefulness is not mentioned. We present a case of a patient with the elbow pain and loss of the forearm rotation due to the prominent bicipital tuberosity of the radius, which was diagnosed as enthesopathy. Surgical treatment to excise the prominent part of the bicipital tuberosity of the radius was recommended. However, it is difficult to perform the appropriate excision of the abnormal prominent part because of complications such as bicipital tendon rupture. The patient was successfully treated by surgical resection under the control of intraoperative computed tomography. Intraoperative computed tomography scan is a useful tool to assess the remaining volume of the abnormal bones.

Deep Learning Enabled Deblurring of Computed Tomography Images of Porous Media

2021 ◽  
Author(s):  
Khalid Labib Alsamadony ◽  
Ertugrul Umut Yildirim ◽  
Guenther Glatz ◽  
Umair bin Waheed ◽  
Sherif M. Hanafy
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Transfer Learning ◽  
Temporal Resolution ◽  
Exposure Time ◽  
Ct Images ◽  
Loss Functions ◽  
High Quality ◽  
X Ray ◽  
Training Images

Abstract Computed tomography (CT) is an important tool to characterize rock samples allowing quantification of physical properties in 3D and 4D. The accuracy of a property delineated from CT data is strongly correlated with the CT image quality. In general, high-quality, lower noise CT Images mandate greater exposure times. With increasing exposure time, however, more wear is put on the X-Ray tube and longer cooldown periods are required, inevitably limiting the temporal resolution of the particular phenomena under investigation. In this work, we propose a deep convolutional neural network (DCNN) based approach to improve the quality of images collected during reduced exposure time scans. First, we convolve long exposure time images from medical CT scanner with a blur kernel to mimic the degradation caused because of reduced exposure time scanning. Subsequently, utilizing the high- and low-quality scan stacks, we train a DCNN. The trained network enables us to restore any low-quality scan for which high-quality reference is not available. Furthermore, we investigate several factors affecting the DCNN performance such as the number of training images, transfer learning strategies, and loss functions. The results indicate that the number of training images is an important factor since the predictive capability of the DCNN improves as the number of training images increases. We illustrate, however, that the requirement for a large training dataset can be reduced by exploiting transfer learning. In addition, training the DCNN on mean squared error (MSE) as a loss function outperforms both mean absolute error (MAE) and Peak signal-to-noise ratio (PSNR) loss functions with respect to image quality metrics. The presented approach enables the prediction of high-quality images from low exposure CT images. Consequently, this allows for continued scanning without the need for X-Ray tube to cool down, thereby maximizing the temporal resolution. This is of particular value for any core flood experiment seeking to capture the underlying dynamics.

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