scholarly journals Maximal tumor diameter in the preoperative tumor magnetic resonance imaging (MRI) T2 image is associated with prognosis of Grade II Glioma

Medicine ◽  
2021 ◽  
Vol 100 (10) ◽  
pp. e24850
Author(s):  
Haipeng Liu ◽  
Liangfang Shen ◽  
Xinqiong Huang ◽  
Guangying Zhang
2021 ◽  
Vol 11 ◽  
Author(s):  
Zhen-hua Wang ◽  
Xin-Lan Xiao ◽  
Zhao-Tao Zhang ◽  
Keng He ◽  
Feng Hu

ObjectiveThis study aimed to develop a radiomics model to predict early recurrence (<1 year) in grade II glioma after the first resection.MethodsThe pathological, clinical, and magnetic resonance imaging (MRI) data of patients diagnosed with grade II glioma who underwent surgery and had a recurrence between 2017 and 2020 in our hospital were retrospectively analyzed. After a rigorous selection, 64 patients were eligible and enrolled in the study. Twenty-two cases had a pathologically confirmed recurrent glioma. The cases were randomly assigned using a ratio of 7:3 to either the training set or validation set. T1-weighted image (T1WI), T2-weighted image (T2WI), and contrast-enhanced T1-weighted image (T1CE) were acquired. The minimum-redundancy-maximum-relevancy (mRMR) method alone or in combination with univariate logistic analysis were used to identify the most optimal predictive feature from the three image sequences. Multivariate logistic regression analysis was then used to develop a predictive model using the screened features. The performance of each model in both training and validation datasets was assessed using a receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).ResultsA total of 396 radiomics features were initially extracted from each image sequence. After running the mRMR and univariate logistic analysis, nine predictive features were identified and used to build the multiparametric radiomics model. The model had a higher AUC when compared with the univariate models in both training and validation data sets with an AUC of 0.966 (95% confidence interval: 0.949–0.99) and 0.930 (95% confidence interval: 0.905–0.973), respectively. The calibration curves indicated a good agreement between the predictable and the actual probability of developing recurrence. The DCA demonstrated that the predictive value of the model improved when combining the three MRI sequences.ConclusionOur multiparametric radiomics model could be used as an efficient and accurate tool for predicting the recurrence of grade II glioma.


2019 ◽  
Vol 23 (04) ◽  
pp. 405-418 ◽  
Author(s):  
James F. Griffith ◽  
Radhesh Krishna Lalam

AbstractWhen it comes to examining the brachial plexus, ultrasound (US) and magnetic resonance imaging (MRI) are complementary investigations. US is well placed for screening most extraforaminal pathologies, whereas MRI is more sensitive and accurate for specific clinical indications. For example, MRI is probably the preferred technique for assessment of trauma because it enables a thorough evaluation of both the intraspinal and extraspinal elements, although US can depict extraforaminal neural injury with a high level of accuracy. Conversely, US is probably the preferred technique for examination of neurologic amyotrophy because a more extensive involvement beyond the brachial plexus is the norm, although MRI is more sensitive than US for evaluating muscle denervation associated with this entity. With this synergy in mind, this review highlights the tips for examining the brachial plexus with US and MRI.


Endoscopy ◽  
2004 ◽  
Vol 36 (10) ◽  
Author(s):  
BP McMahon ◽  
JB Frøkjær ◽  
A Bergmann ◽  
DH Liao ◽  
E Steffensen ◽  
...  

2019 ◽  
pp. 10-23
Author(s):  
T. A. Akhadov ◽  
S. Yu. Guryakov ◽  
M. V. Ublinsky

For a long time, there was a need to apply magnetic resonance imaging (MRI) technique for lung visualization in clinical practice. The development of this method is stimulated by necessity of the emergence of an alternative to computed tomography, especially when radiation and injection of iodine-containing contrast agents are contraindicated or undesirable, for example, in pregnant women and children, people with intolerance to iodinated contrast. One of the reasons why lung MRI is still rarely used is lack of elaborated standardized protocols that would be adapted to clinical needs of medical society. This publication is a current literature review on the use of MRI in lung studies.


2007 ◽  
Vol 30 (4) ◽  
pp. 41
Author(s):  
A. Dechant

On the morning of October 10, 2003, the residents of New York awoke to find that an entire page of their beloved paper, The Times, had been usurped for the sole purpose of flagrant self-promotion and protestation. On his own behalf, Dr. Raymand Damadian had purchased a one page spread bemoaning his exclusion in the Nobel Prize for Medicine that year which had previously been awarded to Paul Laterbur and Peter Mansfield for their contributions to the development of Magnetic Resonance Imaging (MRI). Over the course of the next few months, the public was to witness a series of such articles proclaiming that a shameful wrong had been committed, and that the truth would eventually prove Dr. Damadian’s accusations. That truth lay in the early theoretical and technical foundations that led to the discovery of MRI. Described just after the Second World War, nuclear magnetic resonance (NMR) was hailed as a breakthrough in physical chemistry for which Felix Bloch and Edward Purcell were awarded the Nobel Prize in Physics in 1952. Two decades later, in 1971, Dr. Damadian discovered that differences between the NMR signals of cancerous and normal tissue might provide a rapid means of cancer detection. However, Laterbur and Mansfield were the first to actually demonstrate images of live tissue using the application of magnetic gradients – the key to modern MRI. Though speculation exists that Dr. Damadian may have been excluded from the prize due to his religious beliefs or political rivalry, only time will reveal the whole truth when the Nobel files are opened 50 years hence. Bradley W. The Nobel Prize: Three Investigators Allowed but Two Were Chosen. Journal of Magnetic Resonance Imaging 2004; 19:520. Laterbur P. Image formation by induced local interactions: examples of employing nuclear magnetic resonance. Nature 1973; 242:190-191. Mansfield P, Grannell P. “NMR diffraction in solids?” Journal of Physics C: Solid State Physics 1973; 63:L433-L426.


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