Automated method for tissue-based contrast media arrival detection for dynamic contrast enhanced MRI

A method for automated contrast arrival detection in temporally phased images or datasets of tissues, the method comprising:

• (a) identifying a plurality of tissue voxels in a plurality of the temporally phased images as a function of predetermined enhancement characteristics associated with discrete tissue voxels;
• (b) computing, with a processor, signal intensity curve madness for the tissue voxels identified in (a);
• (c) comparing the signal intensity curve madness computed for the tissue voxels in (b) to a smoothness threshold;
• and
• (d) identifying contrast media arrival phases in the temporally phased images based on the comparing in (c).

A device for automated contrast arrival detection in temporally phased images or datasets of tissues, the device comprising:

• a non-transitory, computer-readable medium comprising program instructions;
• and
• a processor configured by the program instructions to:
• (a) identify a plurality of tissue voxels in a plurality of the temporally phased images as a function of predetermined enhancement characteristics associated with discrete tissue voxels that include baseline signal intensity values and late phase signal intensity values to derive a signal intensity enhancement value for each of the voxels;
• (b) compare the signal intensity enhancement value to a signal intensity enhancement threshold for the tissue voxels identified in (a);
• (c) establish a plurality of candidate arrival phases based upon the comparison in (b);
• and
• (d) identify contrast media arrival phases in the temporally phased images from the candidate arrival phases established in (c).

A device for automated contrast arrival detection in temporally phased images or datasets of tissues, the device comprising:

• a non-transitory, computer-readable medium comprising program instructions;
• and
• a processor configured by the program instructions to:
• (a) identify a plurality of tissue voxels in a plurality of the temporally phased images as a function of predetermined enhancement characteristics associated with discrete tissue voxels;
• (b) compute a signal intensity curve madness for the tissue voxels identified in (a);
• (c) compare the signal intensity curve madness computed for the tissue voxels in (b) to a smoothness threshold;
• and
• (d) identify contrast media arrival phases in the temporally phased images based on the comparison in (c).

A non-transitory, computer-readable medium comprising program instructions that, when executed by a processor, causes the processor to:

• (a) identify a plurality of tissue voxels in a plurality of the temporally phased images as a function of predetermined enhancement characteristics associated with discrete tissue voxels that include baseline signal intensity values and late phase signal intensity values to derive a signal intensity enhancement value for each of the voxels;
• (b) compare the signal intensity enhancement value to a signal intensity enhancement threshold for the tissue voxels identified in (a);
• (c) establish a plurality of candidate arrival phases based upon the comparison in (b);
• and
• (d) identify contrast media arrival phases in the temporally phased images from the candidate arrival phases established in (c).

A non-transitory, computer-readable medium comprising program instructions that, when executed by a processor, causes the processor to:

• (a) identify a plurality of tissue voxels in a plurality of the temporally phased images as a function of predetermined enhancement characteristics associated with discrete tissue voxels;
• (b) compute a signal intensity curve madness for the tissue voxels identified in (a);
• (c) compare the signal intensity curve madness computed for the tissue voxels in (b) to a smoothness threshold;
• and
• (d) identify contrast media arrival phases in the temporally phased images based on the comparison in (c).