Publications by authors named "M Ikedo"
Magn Reson Imaging
December 2024
Article Synopsis
- This study aimed to evaluate how effective proton density with fat fraction (PD-FFQ) imaging is in diagnosing aplastic anemia and assessing blood production ability in adults.!
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- Researchers compared PD-FFQ imaging results in 14 aplastic anemia patients, 14 patients with myelodysplastic syndrome, and 14 control patients, analyzing correlations with blood test results and distinguishing features between groups.!
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- The findings indicated that PD-FFQ imaging, particularly measurements from vertebrae, correlated well with blood test results and demonstrated higher diagnostic accuracy and specificity when assessing aplastic anemia compared to other methods.!
Eur Radiol Exp
September 2024
Article Synopsis
- A study compared compressed sensing (CS) with deep learning reconstruction (DLR) to traditional parallel imaging (PI) for enhancing image quality and reducing scan time in female pelvic MRI at 1.5-T.
- Results showed that CS combined with DLR yielded significantly higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for both T1 and T2-weighted images, indicating improved diagnostic performance.
- The findings concluded that using CS with DLR is more effective than PI, providing better image quality and shorter examination times for female pelvic MRIs.
Cancers (Basel)
April 2024
Article Synopsis
- Diffusion-weighted imaging (DWI) is often affected by quality issues due to susceptibility artifacts, and new imaging techniques like fast advanced spin-echo (FASE) and deep learning reconstruction (DLR) aim to improve this.
- The study used both in vitro (phantom) and in vivo (patient) testing to compare the effectiveness of FASE and DLR against traditional echo-planar imaging (EPI) regarding image quality and the ability to distinguish between malignant and benign tumors.
- Results showed that FASE with DLR significantly enhanced image quality and signal-to-noise ratio while maintaining accuracy in measuring the apparent diffusion coefficient (ADC) and differentiating tumor types compared to EPI.
Magn Reson Imaging
May 2024
Article Synopsis
- The study aimed to evaluate how compressed sensing (CS) with deep learning reconstruction (DLR) can enhance the quality of liver imaging compared to traditional methods.
- Seventy-seven patients with liver lesions were analyzed using both high-resolution contrast-enhanced T1-weighted imaging (HR-CE-T1WI) and conventional methods to assess image quality, clarity, and lesion detection rates.
- Results showed that HR-CE-T1WI had significantly better image quality and sensitivity for detecting liver lesions while reducing the likelihood of false positives.
