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CT Physics Flashcards

7 cards from real ARRT practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 CT Physics flashcards as text
  1. In CT, 'effective mAs' (mAs/pitch) is important because:

    Answer: It remains constant regardless of pitch, maintaining image noise consistency

    Effective mAs = mAs ÷ pitch; keeping this constant as pitch changes maintains consistent image noise regardless of table speed.

  2. What is the effect of decreasing detector collimation (thinner slices) on image noise, assuming all other factors remain constant?

    Answer: Noise increases

    Thinner collimation means fewer photons contribute to each voxel, increasing statistical noise in the image.

  3. The Hounsfield unit (HU) value of pure water is defined as:

    Answer: 0 HU

    The CT number scale defines water as 0 HU and air as −1000 HU, with other tissues placed relative to these references.

  4. Which reconstruction kernel (filter) should be selected to best visualize lung parenchyma and fine pulmonary detail?

    Answer: High-resolution (sharp/edge-enhancing) kernel

    A high-resolution or edge-enhancing kernel accentuates fine structural detail needed for lung parenchyma evaluation, at the cost of increased noise.

  5. In CT dose reporting, CTDI_vol represents:

    Answer: Volume-averaged radiation dose within the scan volume

    CTDI_vol is the volume CT dose index, representing average dose within the irradiated volume; it accounts for pitch in helical scanning.

  6. Which of the following correctly describes 'isotropic voxels' in CT?

    Answer: Voxels with equal x, y, and z dimensions

    Isotropic voxels have equal dimensions in all three planes, enabling high-quality multiplanar reformations without resolution loss.

  7. The primary advantage of iterative reconstruction over filtered back projection (FBP) in CT is:

    Answer: Reduced image noise at equivalent or lower dose

    Iterative reconstruction algorithms reduce noise by modeling the imaging system and iteratively comparing projection data, allowing lower-dose acquisitions.