Multiple myeloma manifesting as an intraventricular brain tumor

2009 ◽  
Vol 110 (4) ◽  
pp. 737-739 ◽  
Author(s):  
Joo-Hun David Eum ◽  
Astrid Jeibmann ◽  
Werner Wiesmann ◽  
Werner Paulus ◽  
Heinrich Ebel
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Myeloma ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Lateral Ventricle ◽  
Histopathological Examination ◽  
Brain Parenchyma ◽  
Resonance Imaging

Primary intracerebral manifestation of multiple myeloma is rare and usually arises from the meninges or brain parenchyma. The authors present a case of multiple myeloma primarily manifesting within the lateral ventricle. A 67-year-old man was admitted with headache accompanied by slowly progressing right hemiparesis. Magnetic resonance imaging showed a large homogeneous contrast-enhancing intraventricular midline mass and hydrocephalus. The tumor was completely resected, and histopathological examination revealed plasmacytoma. After postoperative radio- and chemotherapy, vertebral osteolysis was detected as a secondary manifestation of multiple myeloma.

scholarly journals Differential Deep Convolutional Neural Network Model for Brain Tumor Classification

2021 ◽  
Vol 11 (3) ◽  
pp. 352
Author(s):  
Isselmou Abd El Kader ◽  
Guizhi Xu ◽  
Zhang Shuai ◽  
Sani Saminu ◽  
Imran Javaid ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Medical Image ◽  
Resonance Imaging ◽  
Feature Maps ◽  
Deep Cnn

The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

scholarly journals Prognostic significance of magnetic resonance imaging of bone marrow in previously untreated patients with multiple myeloma

2005 ◽  
Vol 16 (11) ◽  
pp. 1824-1828 ◽  
Author(s):  
L.A. Moulopoulos ◽  
D. Gika ◽  
A. Anagnostopoulos ◽  
K. Delasalle ◽  
D. Weber ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Myeloma ◽  
Bone Marrow ◽  
Magnetic Resonance ◽  
Prognostic Significance ◽  
Resonance Imaging

Closed rhinoplasty approach for excision of nasal dermoids

2009 ◽  
Vol 124 (5) ◽  
pp. 538-542
Author(s):  
R L Harris ◽  
H Daya
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Histopathological Examination ◽  
Resonance Imaging ◽  
Aesthetic Outcome ◽  
Cosmetic Results ◽  
Cutaneous Involvement

AbstractObjective:To assess the efficacy of excision of nasal dermoids through a closed rhinoplasty incision. This is the first description of the use of this approach for excision of superficial nasal dermoids.Methods:Three boys aged five, nine and 12 years presented with midline nasal dermoids with minimal cutaneous involvement. Magnetic resonance imaging demonstrated distinct, cystic, superficial nasal masses. The cysts were excised through a closed rhinoplasty approach. In each case, completeness of extirpation was judged by histopathological examination of the excised specimen. Aesthetic outcome was recorded photographically.Results:All three patients' cysts were completely excised, with excellent cosmetic results.Conclusions:The closed rhinoplasty incision is another approach in the surgeon's armamentarium for excision of small, superficial nasal dermoid cysts. In well selected cases, this approach gives optimal cosmetic results, provides adequate exposure with minimal dissection, and allows total extirpation.

scholarly journals Perfusion Magnetic Resonance Imaging to Assess Brain Tumor Responses to New Therapies

1998 ◽  
Vol 5 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Michael H. Lev ◽  
Fred Hochberg
Keyword(s):  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Imaging Techniques ◽  
Perfusion Mri ◽  
Perfusion Magnetic Resonance Imaging ◽  
Normal Brain ◽  
Resonance Imaging ◽  
New Therapies ◽  
Magnetic Resonance Imaging Mri

Background: Although magnetic resonance imaging (MRI) is effective in detecting the location of intracranial tumors, new imaging techniques have been studied that may enhance the specificity for the prediction of histologic grade of tumor and for the distinction between recurrence and tumor necrosis associated with cancer therapy. Methods: The authors review their experience and that of others on the use of perfusion magnetic resonance imaging to evaluate responses of brain tumors to new therapies. Results: Functional imaging techniques that can distinguish tumor from normal brain tissue using physiological parameters. These new approaches provide maps of tumor perfusion to monitor the effects of novel compounds that restrict tumor angiogenesis. Conclusions: Perfusion MRI not only may be as effective as radionuclide-based techniques in sensitivity and specificity in assessing brain tumor responses to new therapies, but also may offer higher resolution and convenient co-registration with conventional MRI, as well as time- and cost-effectiveness. Further study is needed to determine the role of perfusion MRI in assessing brain tumor responses to new therapies.

scholarly journals Vulvar Lipoma: A Case Report

2018 ◽  
Vol 40 (10) ◽  
pp. 647-649
Author(s):  
Ahmed Reda ◽  
Ihab Gomaa
Keyword(s):  
Magnetic Resonance Imaging ◽  
Case Report ◽  
Magnetic Resonance ◽  
Histopathological Examination ◽  
Surgical Excision ◽  
Imaging Modalities ◽  
Resonance Imaging ◽  
Rare Site ◽  
Magnetic Resonance Imaging Mri ◽  
Vulvar Mass

AbstractThe present study is a case report of vulvar lipoma. The vulva is a rare site for the development of lipomas, and the aim of the study is to determine if the current imaging modalities can diagnose lipomas correctly. A 43-year-old patient presented with a painless, slowly progressive, oval, mobile and non-tender right vulvar mass compressing the vagina and totally covering the introitus. Both the ultrasonography and magnetic resonance imaging (MRI) exams suggested the diagnosis of lipoma. Surgical excision was performed, and the histopathological examination of the mass confirmed a lipoma.

scholarly journals Diagnostic Accuracy and Validity of Magnetic Resonance Imaging in the Detection of Speci!c Type of Brain Tumour

2019 ◽  
Vol 46 (3) ◽  
pp. 85-89
Author(s):  
Swati Munshi ◽  
Farid Ahmed ◽  
Bibekananda Halder ◽  
Abdullah Yousuf ◽  
Md Mahbubur Rahman ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Diagnostic Accuracy ◽  
Brain Tumour ◽  
Brain Tumours ◽  
Histopathological Examination ◽  
Test Validity ◽  
Resonance Imaging ◽  
Grade Ii ◽  
Grade Iii

Magnetic Resonance Imaging (MRI) is a widely accessible imaging technique for the detection of brain tumours and cancer, which are further confirmed by histopathological examination. Accurate detection of the tumours and its extent is very difficult. The present study attempted to evaluate the convenience of MRI in detection of different grades of astrocytomas, which are the most commonly occurring brain tumours. This cross-sectional study was conducted at the Department of Radiology and Imaging with the collaboration of Department of Neurosurgery and Department of Pathology at Sir Salimullah Medical College (SSMC & MH), Dhaka from January 2013 to December 2013 for a period of one year. The study population was all the diagnosed cases of intracranial astrocytoma patients regardless of their age and sex. The studied included 48 brain tumour (astrocytoma) patients, ages between 13 and 69 years old. All cases having no contraindication for MRI underwent MR examination followed by histopathological examination of the postoperative resected tissues. The findings of the MRI and histopathological examination were compared to find out the test validity of the MRI findings of the different grades of astrocytoma’s. The highest sensitivity was found in grade III astrocytoma (90.5%) followed by grade II (85.7%) grade IV (75.0%) and grade I (60.0%). The highest specificity was found in grade I astrocytoma (97.7%) followed by Grade III (96.3%), grade IV (92.5%) and grade II (91.5%). The highest accuracy was found in both grade I astrocytoma (93.7%) and grade III (93.7%) followed by grade II (92.5%) and grade IV (89.6%). As per the study findings it can be concluded that,MRI has a high diagnostic accuracy and validity for the detection of different grades of astrocytoma. Bangladesh Med J. 2017 Sep; 46 (3): 85-89

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