Skip to main content
. 2018 Sep 7;4(1):168–176. doi: 10.1016/j.adro.2018.08.024

Table 1.

Unique synCT generation RPN and SOD scores before and after suggested modifications

Failure mode Failure pathway Before mitigation
Suggested Change After mitigation
S O D RPN SOD S O D RPN SOD
1. Bone segmentation
 Incorrect bone classification Bone/air indistinguishable in MR images 4 9 1 36 491 Consult with radiologists; apply consensus guidelines; attend education programs through national meetings (eg, RSNA) 4 9 1 36 491
Nonbone material classified as bone 5 8 1 40 581 5 4 1 20 541
Bone volume underestimated 4 7 4 112 474 4 4 3 48 443
Bone volume overestimated 4 8 4 128 484 4 5 3 60 453
Uncertainty from interobserver differences in manual bone segmentation 4 5 3 60 453 4 4 3 48 443
2. Tissue classification/density assignments
 SynCT not representative of average anatomy Long scan time leads to changes in internal anatomy (bladder/rectal filling) 4 7 1 28 471 Minimize number of acquired sequences; minimize acquisition time for each sequence 3 7 1 21 371
Varied physiologic states for different data sets needed for synCT 4 7 1 28 471 3 7 1 21 371
Changed target location because of state 6 5 2 60 652 4 5 2 40 452
Patient-specific distortion corrections for air/tissue may be inaccurate 4 4 5 80 445 3 4 5 60 345
 Tissue misclassification/inaccurate HU assignment Inaccurate autosegmentation 4 6 3 72 463 Standardize sequences; increase the number of patients to ensure a representative group of patients in the training set 3 4 3 36 343
Patient not well represented by population-based values 4 3 9 108 439 4 1 9 36 419
Population-based values derived from a nonrepresentative set of patients 4 1 9 36 419 2 1 9 18 219
Not enough patients used to determine population-based values 4 1 9 36 419 2 1 9 18 219
 Inaccurate segmentation Image nonuniformity affecting automated intensity-based segmentation approaches 4 5 5 100 455 Check constancy of vendor-implemented correction software; Implement independent postprocessing assessment and correction tools and QA procedures 4 3 4 48 434
Inadequate distortion correction 6 6 3 108 663 2 4 3 24 243
3. Overall synCT process
 External contour incorrect System-level geometric distortion not taken into account 5 9 3 135 593 Implement robust QA/QC including verification tests performed on phantoms; training of radiation oncology staff with respect to proper coil use 5 5 3 75 553
Image artifacts preventing accurate external delineation 3 8 1 24 381 3 6 1 18 361
External anatomy incomplete 3 8 1 24 381 3 6 1 18 361
Anatomy deformed by coils 3 7 2 42 372 3 4 2 24 342
 Inaccurate synCT Missing images required for generating synCT 4 2 1 8 421 Standardize sequences 4 1 1 4 411
 Organ location inaccurate System-level geometric distortion not taken into account 6 7 4 168 674 Standardize sequences; optimize sequence parameters to minimize acquisition time; implement vendor-independent postprocessing software 2 2 5 20 225
Patient-induced distortions near interfaces present 6 7 5 210 675 5 6 5 150 565
Patient anatomy is not standard for patient—unable to reproduce anatomy 7 3 3 63 733 7 1 3 21 713
Long scan time leads to changes in internal anatomy (bladder/rectal filling) 6 5 2 60 652 4 5 2 40 452
Varied physiologic states for different data sets needed for synCT 6 3 2 36 632 5 2 2 20 522
Changed target location because of state 8 2 2 32 822 6 2 2 24 622

Abbreviations: HU = Hounsfield unit; MR = magnetic resonance; QA = quality assurance; QC = quality control; RPN = risk priority numbers; RSNA = Radiological Society of North America; SOD = severity-occurrence-detectability; synCT = synthetic computed tomography.