Image Basics | MRIQUIZ
Pulse sequence: a precisely timed series of radiofrequency (RF) pulses and magnetic field gradient applications that dictate how the magnetic resonance (MR) signal is generated and acquired from the sampled tissue, thereby determining the final image contrast and appearance.
After the initial RF excitation, which tips the net magnetization vector into the transverse plane, two fundamental and simultaneous processes occur as the spins attempt to return to equilibrium:
T1 relaxation (spin-lattice relaxation): This is the process of longitudinal magnetization regrowth along the Z-axis (parallel to the main magnetic field, B_0). It involves the exchange of energy between the excited spins and their surrounding molecular environment (the 'lattice'). This process is relatively slow, typically taking hundreds of milliseconds to several seconds, as spins transfer their excess energy to the lattice.
T2 relaxation (spin-spin relaxation): This describes the dephasing of spins in the transverse plane, leading to a loss of transverse magnetization and thus a decaying MR signal. It occurs due to interactions between adjacent spins and local magnetic field inhomogeneities, causing them to lose phase coherence. T2 relaxation is much faster than T1, occurring in milliseconds.
The fundamental difference in these intrinsic relaxation rates across various tissues is what gives rise to significant MRI tissue contrast.
Therefore, T1 and T2 relaxation times are the cornerstone values that underpin all tissue contrast mechanisms and guide the choice of image weighting settings in MRI.
T1 and T2 Relaxation Times
T1 relaxation: Represents the time required for the longitudinal magnetization to recover to approximately 63% of its original (equilibrium) value after an RF pulse. This is also accurately described as the regrowth of the net magnetization vector along the longitudinal (Z) axis as spins realign with the B_0 field.
T2 relaxation: Defined as the time required for the transverse magnetization to decay to approximately 37% of its initial peak value (which is equivalent to 63% of the magnetization having decayed) after the RF excitation. This decay is exponential.
Tissue contrast in MRI is fundamentally derived because different biological tissues possess distinct and characteristic T1 and T2 values, reflecting their unique molecular compositions and environments.
Fat vs. Water: These two common biological components represent the extremes of T1 and T2 relaxation, making them excellent examples for understanding MRI contrast:
Fat: Generally has a relatively short T1 and a relatively short T2. This is attributed to its molecular structure (large, less mobile molecules with many short-chain hydrogens) and its interaction with the lattice.
Water (e.g., CSF, edema): Characterized by a long T1 and a long T2. This is due to its highly mobile hydrogen protons within a relatively free molecular environment, allowing for slower energy exchange with the lattice (long T1) and slower dephasing (long T2 due to less significant spin-spin interactions compared to restricted environments).
The hydrogen Larmor frequency in water is negligibly different from that in fat under typical clinical fields. The relaxation differences are due to molecular environment, not inherent Larmor frequency shifts.
Physiologically, fat recovers its longitudinal magnetization along the Z-axis more rapidly than water (short T1), and conversely, it loses its transverse magnetization faster than water (short T2).
Practical implication: To achieve a low signal (dark appearance) in the image, the imaging parameters must be set such that only a small transverse magnetization component is available for detection by the receiver coil at the time of signal acquisition (Echo Time, TE). Conversely, to obtain a high signal (bright appearance), a large transverse magnetization component must be present and received by the coil.
Tissue Contrast: Fat and Water Signals
Fat vs. Water as primary examples for demonstrating MRI contrast:
Fat typically appears bright on T1-weighted images and dark on T2-weighted images when using standard acquisition settings. This is because its short T1 allows for rapid regrowth of longitudinal magnetization, and its short T2 causes rapid decay of transverse magnetization.
Watery tissues (such as Cerebrospinal Fluid [CSF], edema, cysts) generally appear dark on T1-weighted images and bright on T2-weighted images. Their long T1 means slower longitudinal recovery, and their long T2 means sustained transverse magnetization for longer periods.
Basic relationship governing image weighting:
T1-weighted images are designed to emphasize differences in T1 relaxation times. This is achieved by employing short Repetition Time (TR) and short Echo Time (TE). The short TR capitalizes on T1 differences, while the short TE minimizes T2 effects.
T2-weighted images are tailored to highlight differences in T2 relaxation times. This is accomplished by utilizing a long TR and a long TE. The long TR allows most tissues to fully recover their longitudinal magnetization before the next excitation, thus largely nulling T1 contrast, while the long TE allows T2 differences to fully manifest.
Fat-specific characteristics in imaging:
The T1 time of fat is significantly shorter than that of water. Consequently, the net magnetization vector of fat realigns with the B_0 field (recovers longitudinal magnetization) much faster than that of water immediately following the RF pulse.
As a direct result, fat appears bright on T1-weighted images because it quickly generates a strong longitudinal signal, which is then converted into a strong transverse signal by the subsequent RF pulse. Water, with its longer T1, appears darker because it hasn't fully recovered its longitudinal magnetization during the short TR.
Image Weighting: T1, T2, and PD
T1-weighted imaging: Achieved by selecting a short TR and a short TE. These parameters are chosen to maximize the contribution of T1 information to the image contrast. Tissues with short T1 times (like fat) or those enhanced by T1-shortening contrast agents (e.g., gadolinium) appear bright.
T2-weighted imaging: Achieved by selecting a long TR and a long TE. These parameters are optimized to maximize the contribution of T2 information to the image contrast. Tissues with long T2 times (e.g., edema, CSF, inflammation, tumors) appear bright.
Proton Density (PD) weighting: This weighting emphasizes the relative concentration of hydrogen protons in tissues, rather than the differences in their T1 or T2 relaxation times. It is accomplished by using a long TR (to minimize T1 weighting) and a short TE (to minimize T2 weighting), allowing the signal intensity to primarily reflect the proton density within the tissue. PD-weighted images typically show gray matter brighter than white matter.
Repetition Time (TR) and Echo Time (TE)
Repetition Time (TR): The time interval between successive RF excitation pulses applied to the same slice. TR is the primary controlling factor for T1 weighting/contrast; a shorter TR accentuates T1 differences.
Echo Time (TE): The time interval between the center of the RF excitation pulse and the peak of the echo signal acquisition. TE is the primary controlling factor for T2 weighting/contrast; a longer TE accentuates T2 differences.
Effects of TR changes:
Increasing TR (lengthening the time between pulses):
Improves Signal-to-Noise Ratio (SNR): Allows more time for longitudinal magnetization to recover, leading to a stronger signal.
Increases scan time: Directly proportional relationship, longer TR means longer scan.
Reduces T1 weighting: As TR becomes longer, T1 differences diminish since most tissues have recovered more fully.
Increases number of slices available: Longer TR provides more time slots to excite and acquire data from multiple slices sequentially within one TR period.
Decreasing TR (shortening the time between pulses):
Lowers SNR: Less time for longitudinal recovery results in a weaker signal.
Reduces scan time: Directly proportional, shorter TR means faster scan.
Increases T1 weighting: Enhances the contrast based on T1 differences as tissues recover distinctly during the short TR.
Reduces number of slices available: Shorter TR limits the number of slices that can be acquired efficiently within the TR window.
Effects of TE changes:
Short TE: Generally yields higher SNR because less T2 decay has occurred before the signal is measured.
Long TE: Allows for greater T2 weighting but results in lower SNR due to more T2 decay.
Spin Echo (SE) pulse sequence parameter ranges (typical values, can vary by manufacturer and clinical application):
T1-weighted: TR \text{ in } [350, 700] \text{ ms}, \text{ TE in } [10, 30] \text{ ms}
PD-weighted: TR \text{ in } [1500, 3000] \text{ ms}, \text{ TE in } [10, 30] \text{ ms}
T2-weighted: TR \text{ in } [2000, 6000] \text{ ms}, \text{ TE in } [70, 120] \text{ ms}
Scan time calculation: If TR is doubled, the scan time roughly doubles because TR is a direct multiplier in the scan time formula. The total scan time is approximately proportional to:
\text{Scan Time} \propto TR \times \text{Phase Matrix} \times NEX \times \text{Number of Slices}
Strategies to reduce scan time: Given that scan time can be a critical factor for patient comfort and throughput:
Reduce TR: Directly shortens the time between excitations.
Reduce NSA/NEX (Number of Signal Averages/Excitations): Fewer repetitions reduce total data acquisition, but also reduce SNR.
Increase parallel imaging factor: Uses multiple receiver coils to acquire data simultaneously, effectively reducing the number of phase-encode steps required.
Use Rectangular Field of View (RecFOV): Acquires a non-square FOV, reducing the number of phase-encode steps.
Use Half-Fourier/Halfscan: Acquires only slightly more than half of the k-space data, with the rest symmetrically reconstructed, significantly reducing scan time.
Use the coarsest matrix possible while maintaining diagnostic quality: Reduces the number of phase and frequency encode steps.
Signal-to-Noise Ratio (SNR) and Number of Excitations (NEX/NSA)
Signal-to-Noise Ratio (SNR): A crucial metric in MRI, representing the ratio of the strength of the MR signal to the level of background noise. Higher SNR results in clearer, less grainy images.
Increasing NEX/NSA (Number of Excitations / Number of Signal Averages): This involves repeating the data acquisition for each phase-encode step multiple times and then averaging the signals. Increasing NEX/NSA enhances SNR, but not linearly. The SNR improvement is approximately proportional to the square root of the factor by which NEX/NSA is increased.
Example: If NEX is increased from 2 to 6, this is a 3-fold increase. The SNR would increase by approximately \sqrt{3} \approx 1.73 times.
More precisely: If NEX increases by a factor 'f' (e.g., from 1 to 4, f=4), the SNR increases by approximately \text{SNR}{new} = \text{SNR}{old} \times \sqrt{f}. This is because noise is random and averages out, while the signal is coherent and adds up.
Impact of NEX/NSA on scan time: A higher NEX/NSA directly increases the total scan time, as each acquisition repetition adds to the overall duration.
Effect of NEX/NSA on pixel size/resolution: NEX has no direct effect on pixel size or spatial resolution. The resolution (and thus pixel size) is determined by the Field of View (FOV) and the acquisition matrix (number of phase and frequency encode steps). NEX only improves the signal quality for the existing pixel size.
Slice thickness and voxel volume influence on SNR: Thicker slices contain more hydrogen protons within each voxel, leading to a larger available signal and thus generally a higher SNR.
Adjustments that commonly increase SNR:
Increasing NEX/NSA: As explained above.
Increasing FOV: A larger FOV (with a fixed matrix) means a larger pixel and voxel volume, leading to more signal per voxel.
Decreasing phase matrix or frequency matrix: Reduces the number of pixels within the FOV, thereby increasing individual pixel size and voxel volume.
Increasing TR: Allows for more longitudinal recovery, resulting in a stronger signal.
Increasing slice thickness: Increases the voxel volume, capturing more signal.
Reducing receiver bandwidth: Narrows the range of frequencies acquired, reducing the amount of noise measured per unit time, but can increase chemical shift artifact.
Reducing ETL (Echo Train Length) for certain sequences like FSE/Fast Spin Echo: Shorter ETL can lead to less T2 decay and better SNR (though this is more complex due to T2 blurring considerations).
Adjustments that commonly decrease SNR:
Reducing NEX/NSA: Less averaging means more noise relative to signal.
Reducing FOV: A smaller FOV (with a fixed matrix) means smaller pixel and voxel volume, reducing signal per voxel.
Increasing phase matrix or frequency matrix: Increases the number of pixels within the FOV, thereby decreasing individual pixel size and voxel volume.
Reducing TR: Less time for longitudinal recovery, resulting in a weaker signal.
Increasing ETL (Echo Train Length): While it speeds up acquisition, longer echo trains introduce more T2 decay and potentially increase image blurring, indirectly affecting effective SNR or image quality.
The longer the ETL, the greater the potential for T2 blurring (due to T2 decay across the echo train) and signal loss, which influences both the perceived SNR and image sharpness.
Slice Thickness, Voxel Size, and Isotropy
Slice thickness directly affects several critical image characteristics:
SNR: Thicker slices encompass a larger volume of tissue, meaning more protons contribute to the signal, leading to a higher SNR.
Image resolution (along the Z-axis): Thinner slices provide finer detail and better resolution in the slice direction, allowing for better visualization of small structures.
Anatomical coverage: Adjusting slice thickness, coupled with the number of slices, determines the overall anatomical region covered during the scan.
Voxel volume considerations:
A voxel is the fundamental 3D unit of an MRI image, representing a tiny cube or cuboid of tissue from which the signal is acquired. Its size directly influences the amount of signal received (and thus SNR) and the spatial resolution.
Voxel size is determined by the pixel area on the slice plane and the slice thickness.
Pixel size (2D): The dimensions of an individual pixel within the slice plane are calculated as:
\text{Pixel size}{frequency} = \frac{\text{FOV}{frequency}}{\text{N}_{frequency}}
\text{Pixel size}{phase} = \frac{\text{FOV}{phase}}{\text{N}_{phase}}
Pixel Area: The area of a single pixel in the acquisition plane is the product of its dimensions:
A{\text{pixel}} = \text{Pixel size}{frequency} \times \text{Pixel size}_{phase}
Voxel size: The total volume of a voxel is the pixel area multiplied by the slice thickness:
\text{Voxel Volume} = A_{\text{pixel}} \times \text{Slice Thickness}
An isotropic voxel (or cubic voxel) has equal dimensions in all three spatial directions: frequency-encode, phase-encode, and slice-select. To produce isotropic voxels, the imaging parameters (FOV, matrix, and slice thickness) must be deliberately selected and adjusted so that the calculated pixel size in both frequency and phase directions equals the slice thickness.
Field of View (FOV), Matrix, and Pixel Size
Field of View (FOV): The anatomical area encompassed by the imaging acquisition. It is the region from which signal is intentionally acquired and displayed in the image.
Matrix: Refers to the number of frequency-encode steps and phase-encode steps (e.g., 256 \times 192). It defines the number of individual pixels that will make up the image in the frequency and phase directions.
Pixel size is intrinsically governed by the FOV and the Matrix dimensions. In each dimension, the pixel size is calculated as:
\text{Pixel size}{dimension} = \frac{\text{FOV}{dimension}}{\text{Matrix}_{dimension}}
Reducing the FOV: If the matrix remains fixed, reducing the FOV leads to smaller pixel sizes and thus smaller voxel volumes. This can potentially increase spatial resolution (ability to distinguish small objects) within the smaller field, but it simultaneously results in a reduction in SNR because less tissue volume is contributing signal to each voxel.
Quantitative impact: Halving the FOV in both dimensions (e.g., from 20cm x 20cm to 10cm x 10cm) while keeping the matrix constant reduces the pixel area and consequently the voxel volume by a factor of 4 ( (1/2) \times (1/2) = 1/4). This typically results in a corresponding reduction in SNR, often to approximately 25% of the original SNR if other factors remain constant.
Doubling the FOV: Conversely, if the matrix remains fixed, doubling the FOV in both dimensions increases the pixel area and voxel volume by a factor of 4. This significantly increases SNR, roughly by a factor of 4 (assuming all other parameters are constant), but it concurrently leads to a decrease in spatial resolution (larger pixels).
The relationship \text{Pixel Size} = \frac{\text{FOV}}{\text{Matrix}} is fundamental for calculating the resolution achieved in an MR image. Example calculations:
Example A: If FOV = 220 mm and Matrix = 256 (for a square matrix/pixel), then the pixel size in both dimensions is approximately \frac{220 \text{ mm}}{256} \approx 0.86 \text{ mm} .
Example B: If FOV = 240 mm (frequency) x 180 mm (phase), and Matrix = 256 (frequency) x 192 (phase):
Pixel size (frequency) = \frac{240 \text{ mm}}{256} \approx 0.94 \text{ mm}
Pixel size (phase) = \frac{180 \text{ mm}}{192} \approx 0.94 \text{ mm} (leading to approximately square pixels in this example).
Careful selection of FOV and matrix is crucial for balancing desired resolution against acceptable SNR and scan time.