Evaluation of the malignant potential of gliomas using diffusion-weighted and gadolinium-enhanced magnetic resonance imaging

Matsuno, Akira; Takaya, Yoshinori; Chen, Hui; TEN, Hirotomo; Hoya, Katsumi; Jiang, Chuanlu; Oyama, Kenichi; Onoda, Keisuke

doi:10.26599/bsa.2021.9050023

Cited by 6 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Experiments have shown that color Doppler ultrasound (US) and magnetic resonance imaging (MRI) and alpha-fetoprotein (AFP) imaging are currently used for prenatal screening for placenta accreta. Among them, AFP is not specific because of its many influencing factors and can only be used as a screening method, while the clinical reports of US and MRI diagnosis of placenta accreta are mostly used alone [ 10 ]. Zhi et al stated that the current prenatal diagnosis of placenta accreta mainly relies on two-dimensional color ultrasound, three-dimensional ultrasound Doppler ultrasound, three-dimensional color power Doppler ultrasound and magnetic resonance imaging (MRI), and other methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Color Doppler Ultrasound Combined with Magnetic Resonance Imaging in Placenta Accreta

Sun

Ren

et al. 2022

Scanning

View full text Add to dashboard Cite

In order to improve the diagnostic value of color Doppler ultrasonography in placenta accreta and make the diagnosis more accurate, a method to detect placenta accreta by combining color Doppler ultrasonography and magnetic resonance is proposed. The patients with placenta accreta were selected for color Doppler ultrasonography and MRI examination. Kappa test was used to analyze the consistency between the results of ultrasound and MRI examination alone and combined diagnosis and pathological examination results, and the receiver operating characteristic (ROC) was drawn. Price compliance, sensitivity, specificity, good estimate rate, negative bid success rate, and Youden index were chosen as the basis for measuring the value of our tests. The results showed that the Kappa combined test rate was 0.609, the equivalent efficiency was 80.90%, and the correlation was good; ROC curve analysis showed that the sensitivity and specificity of articular placenta accreta were 91.75% and 89.26%. The sensitivity, uniqueness, good estimate, negative predictive value, and Youden index of color Doppler ultrasound combined with magnetic resonance imaging>magnetic resonance imaging>color Doppler ultrasound in our laboratory were compared, and the difference was significant ( P < 0.05 ). The experimental results show that color Doppler ultrasound and MRI are effective in the diagnosis of placenta accreta, and each has advantages and disadvantages. Therefore, it has been improved in the diagnosis of placenta accreta, is helpful for the diagnosis of placenta accreta, and is suitable for popularization and use.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Application of Color Doppler Ultrasound Combined with Magnetic Resonance Imaging in Placenta Accreta

Sun

Ren

et al. 2022

Scanning

View full text Add to dashboard Cite

show abstract

“…10 Another study also found that a high signal intensity on DWI is helpful in diagnosing the malignant potential of gliomas, and the qualitative evaluation of the D score from DWI properly reflected the pathological grade of gliomas. 12 HGG has characteristics contrary to those of LGG, which is dense and actively growing with a high ratio of nucleus to the cytoplasm and higher intracellular water content than extracellular, so HGG shows high signal intensity on DWI. 13 However, traditional DWI cannot accurately display the actual movement of water molecules since it ignores the effects of capillary microcirculation.…”

Section: Discussionmentioning

confidence: 94%

Diffusion Weighted Imaging (DWI) Classification and Apparent Diffusion Coefficient (ADC) Value Tendency Based on Cerebral Glioma Grading in Patients at Dr. Soetomo General Academic Hospital in 2016-2020

Kurniawan

Utomo²,

Wahyuhadi³

2023

AKSONA

View full text Add to dashboard Cite

Highlight: Many studies conclude that the prognosis of gliomas can be determined using the DWI sequence and ADC value on MRI The correlation between DWI and ADC values with glioma grading is related to tumor cellularity, nuclear-cytoplasmic ratio, and extracellular space, which affect the movement of water molecules. ABSTRACT Introduction: Glioma grading is crucial to know its prognosis. Magnetic resonance imaging (MRI) is used as a preoperative examination that contains diffusion-weighted imaging (DWI) sequences confirmed by an apparent diffusion coefficient (ADC) value that helps assess tissue based on water diffusion. Objective: To prove the relationship between DWI and ADC values with cerebral glioma grading in patients at Dr. Soetomo General Academic Hospital in 2016—2020. Methods: This retrospective study collected medical records and MRI files in DICOM (Digital Imaging and Communications in Medicine) format. Gender, age, tumor histopathology, and glioma grading were collected. DWI and ADC values were obtained using the RadiAnt DICOM Viewer application. The data were analyzed using descriptive and analytical statistics. The chi-square test was used to analyze the relationship of DWI with glioma grading, and the spearman rank test was used to analyze the relationship of ADC value with glioma grading. Results: The majority of 35 patients were male (54.3%), aged 31–40 years old (22.9%), and the most common histopathology was glioblastoma (37.1%), WHO grade IV. On DWI, most low-grade glioma (LGG) patients showed unrestricted diffusion, and most high-grade glioma (HGG) patients showed restricted diffusion. The ADC value of HGG was lower than the ADC value of LGG. Statistical tests showed a relationship between DWI and glioma grading (p<0.05) and a relationship between the ADC value and glioma grading (p<0.05). Conclusion: There was a relationship between DWI and ADC with glioma grading in Dr. Soetomo General Academic Hospital patients for the period 2016—2020

show abstract

“…Magnetic Resonance Imaging (MRI) plays a crucial role in diagnosing brain tumors and is also extensively used in detecting various neurodegenerative conditions. 10 Leveraging MRI scan data has proven invaluable in glioblastoma prognosis and survival model studies. 11 Therefore, studies tried using MRI images as a survival predictor for the deep learning models.…”

Section: Introductionmentioning

confidence: 99%

MRI sequence impact on deep learning extraction of prognostic features for glioblastoma survival prediction

Mahootiha,

Qadir,

Balasingham

2024

Medical Imaging 2024: Computer-Aided Diagnosis

View full text Add to dashboard Cite

In glioblastoma, an aggressive brain tumor with a low survival rate, accurately predicting patient survival is crucial for effective treatment planning. For a deep learning model developed using MRI images for glioblastoma prognosis, it's essential to identify which MRI sequence -T1, T2, T1-contrast enhanced, or FLAIR -yields the most insightful prognostic features. This study utilizes a specialized autoencoder architecture, specifically a Unet model with an attention mechanism equipped with a custom-designed loss function for reconstructing tumor subregions from multimodal MRI scans. Once the autoencoder is trained, it extracts unique imaging features. Subsequently, these extracted features are analyzed using a Cox regression neural network, which is then applied to predict the survival probabilities of glioblastoma patients. The method was applied based on 5-fold cross-validation. The survival prediction performance of the model was assessed using various MRI sequences. The concordance index (C-index) values obtained were 0.62 for T1, 0.63 for T1CE, 0.63 for T2, and 0.66 for FLAIR. Additionally, the area under the curve (AUC) values recorded were 0.76 for T1, 0.74 for T1CE, 0.76 for T2, and 0.82 for FLAIR, indicating a variation in predictive accuracy across different sequences. The findings from our study underscore a discernible variation in the effectiveness of different MRI sequences for glioblastoma survival prognosis. Notably, the FLAIR sequence emerged as the most informative, providing the highest level of prognostic detail in comparison to T1, T1CE, and T2 sequences. This highlights the significance of sequence selection in enhancing the accuracy of survival predictions in glioblastoma cases.

show abstract

Evaluation of the malignant potential of gliomas using diffusion-weighted and gadolinium-enhanced magnetic resonance imaging

Cited by 6 publications

References 20 publications

Application of Color Doppler Ultrasound Combined with Magnetic Resonance Imaging in Placenta Accreta

Application of Color Doppler Ultrasound Combined with Magnetic Resonance Imaging in Placenta Accreta

Diffusion Weighted Imaging (DWI) Classification and Apparent Diffusion Coefficient (ADC) Value Tendency Based on Cerebral Glioma Grading in Patients at Dr. Soetomo General Academic Hospital in 2016-2020

MRI sequence impact on deep learning extraction of prognostic features for glioblastoma survival prediction

Contact Info

Product

Resources

About