What is the difference between T1 and T2 weighted images on MRI?
T1- or T2-weighting typically refers to the spin echo MR sequence.
Here are the difference between T1 and T2 weighted images on MRI
T1-weighted images are short TR (300–1000 ms) and short TE (10–30 ms) and provide excellent anatomic detail.
In contrast, T2-weighted images are long TR (1800–2500 ms) and long TE (40–90 ms), sensitive for detecting fluid and edema.
An intermediate-weighted sequence or proton density sequence combines T1 and T2 weighting by having a long TR (>T1) and short TE (<T2).
The two basic types of MRI images are T1-weighted and T2-weighted images, often referred to as T1 and T2 images.
The timing of radiofrequency pulse sequences used to make T1 images results in images which highlight fat tissue within the body.
The timing of radiofrequency pulse sequences used to make T2 images results in images which highlight fat AND water within the body.
The most common MRI sequences are T1-weighted and T2-weighted scans. T1-weighted images are produced by using short TE and TR times.
The contrast and brightness of the image are predominately determined by T1 properties of tissue. Conversely, T2-weighted images are produced by using longer TE and TR times.
So, this makes things easy to remember.
T1 images – 1 tissue type is bright – FAT
T2 images – 2 tissue types are bright – FAT and WATER
By controlling the radiofrequency pulse and gradient waveforms, computer programs produce specific pulse sequences that determine how an image is obtained (weighted) and how various tissues appear. Images can be
- T1-weighted
- T2-weighted
- Proton density–weighted
For example, fat appears bright (high signal intensity) on T1-weighted images and relatively dark (low signal intensity) on T2-weighted images; water and fluids appear relatively dark on T1-weighted images and bright on T2-weighted images.
T1-weighted images optimally show normal soft-tissue anatomy and fat (eg, to confirm a fat-containing mass).
T2-weighted images optimally show fluid and abnormalities (eg, tumors, inflammation, trauma).
In practice, T1- and T2-weighted images provide complementary information, so both are important for characterizing abnormalities.
What research says about the T1 and T2 weighted images on MRI?
In a study, T1 and T2 weighted MR images were compared in 32 hips with avascular necrosis, and the difference between them was discussed.
In 27 of 32 hips, abnormal low intensity area in the affected femoral head is smaller in T2 weighted images than in T1 weighted images.
The area of low intensity on T1 weighted image and high on T2 weighted image might be granuloma in reactive tissue and surrounding hyperemia.
The difference between T1 and T2 weighted images must be taken into consideration especially in determination of the border of affected bone.
This technique has some advantages of both T1 and T2-weighted sequences and is commonly used in musculoskeletal imaging.
Two other sequences commonly used are gradient echo and short tau (T1) inversion recovery (STIR).
Gradient echo sequences can be either T1- or T2-weighted and permit very rapid acquisition with thin-section, high-resolution images.
STIR is effectively a fat-suppression technique, very sensitive in detection of fluid or edema. These images greatly aid in the detection of subtle marrow and soft tissue disease, such as muscle tears, but have relatively poor spatial resolution.
The prediction by random forest method is averaged during the process of image synthesis. It may lead to a loss of high spatial frequency information.
The GAN model proposed in the current study trained the image generation and distinguishing the image of the real or synthesized images, simultaneously.
By incorporating the adversarial loss, the detail of the texture information in the target contrast is captured, thereby making higher synthesis quality possible by comparison with absolute error loss or typical squared.
Another study used the conditional GAN with a generator and a discriminator for generating brain MRIs based on GANs from T1-weighted or T2-weighted images and evaluated the appropriate input image parameters.
In a prior study, Jog et al. proposed the random forest method in multi-contrast MRI image synthesis.
The PSNR was 24.7–28.0 in the synthesis from T1-weighted to T2-weighted MRI images and 22.3–23.4 in the synthesis from T2-weighted to T1-weighted MRI images, which were lower than the current study.
Yang et al. predicted the T2-weighted MRI images from the T1-weighted MRI images with a conditional GAN.
The current study increased the convolutional layers and expanded the range of the grayscale in the images.
The current study had a higher PSNR and MI for both image synthesis of T1-weighted to T2-weighted MRI images and T2-weighted to T1-weighted MRI images.
