Favazza, Christopher P

PurposeTo assess risks of RF‐heating of a vagus nerve stimulator (VNS) during 1.5 T prostate MRI using body coil transmit and to compare these risks with those associated with MRI head exams using a transmit/receive head coil.MethodsSpatial distributions of radio‐frequency (RF) B1 fields generated by transmit/receive (T/R) body and head coils were empirically assessed along the long axis of a 1.5 T MRI scanner bore. Measurements were obtained along the center axis of the scanner and laterally offset by 15 cm (body coil) and 7 cm (head coil). RF‐field measurements were supplemented with direct measurements of RF‐heating of 15 cm long copper wires affixed to and submerged in the “neck” region of the gelled saline‐filled (sodium chloride and polyacrylic acid) “head‐and‐torso” phantom. Temperature elevations at the lead tips were measured using fiber‐optic thermometers with the phantom positioned at systematically increased distances from the scanner isocenter.ResultsB1 field measurements demonstrated greater than 10 dB reduction in RF power at distances beyond 28 cm and 24 cm from isocenter for body and head coil, respectively. Moreover, RF power from body coil transmit at distances greater than 32 cm from isocenter was found to be lower than from the RF power from head coil transmit measured at locations adjacent to the coil array at its opening. Correspondingly, maximum temperature elevations at the tips of the copper wires decreased with increasing distance from isocenter — from 7.4°C at 0 cm to no appreciable heating at locations beyond 40 cm.ConclusionsFor the particular scanner model evaluated in this study, positioning an implanted VNS farther than 32 cm from isocenter (configuration achievable for prostate exams) can reduce risks of RF‐heating resulting from the body coil transmit to those associated with using a T/R head coil.

PurposeModel observers have been successfully developed and used to assess the quality of static 2D CT images. However, radiologists typically read images by paging through multiple 2D slices (i.e., multislice reading). The purpose of this study was to correlate human and model observer performance in a low‐contrast detection task performed using both 2D and multislice reading, and to determine if the 2D model observer still correlate well with human observer performance in multislice reading.MethodsA phantom containing 18 low‐contrast spheres (6 sizes × 3 contrast levels) was scanned on a 192‐slice CT scanner at five dose levels (CTDIvol = 27, 13.5, 6.8, 3.4, and 1.7 mGy), each repeated 100 times. Images were reconstructed using both filtered‐backprojection (FBP) and an iterative reconstruction (IR) method (ADMIRE, Siemens). A 3D volume of interest (VOI) around each sphere was extracted and placed side‐by‐side with a signal‐absent VOI to create a 2‐alternative forced choice (2AFC) trial. Sixteen 2AFC studies were generated, each with 100 trials, to evaluate the impact of radiation dose, lesion size and contrast, and reconstruction methods on object detection. In total, 1600 trials were presented to both model and human observers. Three medical physicists acted as human observers and were allowed to page through the 3D volumes to make a decision for each 2AFC trial. The human observer performance was compared with the performance of a multislice channelized Hotelling observer (CHO_MS), which integrates multislice image data, and with the performance of previously validated CHO, which operates on static 2D images (CHO_2D). For comparison, the same 16 2AFC studies were also performed in a 2D viewing mode by the human observers and compared with the multislice viewing performance and the two CHO models.ResultsHuman observer performance was well correlated with the CHO_2D performance in the 2D viewing mode [Pearson product‐moment correlation coefficient R = 0.972, 95% confidence interval (CI): 0.919 to 0.990] and with the CHO_MS performance in the multislice viewing mode (R = 0.952, 95% CI: 0.865 to 0.984). The CHO_2D performance, calculated from the 2D viewing mode, also had a strong correlation with human observer performance in the multislice viewing mode (R = 0.957, 95% CI: 879 to 0.985). Human observer performance varied between the multislice and 2D modes. One reader performed better in the multislice mode (P = 0.013); whereas the other two readers showed no significant difference between the two viewing modes (P = 0.057 and P = 0.38).ConclusionsA 2D CHO model is highly correlated with human observer performance in detecting spherical low contrast objects in multislice viewing of CT images. This finding provides some evidence for the use of a simpler, 2D CHO to assess image quality in clinically relevant CT tasks where multislice viewing is used.

Abstract Channelized Hotelling model observer (CHO) methods were developed to assess performance of an x-ray angiography system. The analytical methods included correction for known bias error due to finite sampling. Detectability indices ( d ′ ) corresponding to disk-shaped objects with diameters in the range 0.5–4 mm were calculated. Application of the CHO for variable detector target dose (DTD) in the range 6–240 nGy frame −1 resulted in d ′ estimates which were as much as 2.9× greater than expected of a quantum limited system. Over-estimation of d ′ < ∼ 3.0 was presumed to be a result of bias error due to temporally variable non-stationary noise. Statistical theory which allows for independent contributions of ‘signal’ from a test object (o) and temporally variable non-stationary noise (ns) was developed. The theory demonstrates that the biased d β ′ is the sum of the detectability indices associated with the test object ( d o ′ ) and non-stationary noise ( d ns ′ ). Given the nature of the imaging system and the experimental methods, d o ′ cannot be directly determined independent of d ns ′ . However, methods to estimate d ns ′ independent of d o ′ were developed. In accordance with the theory, d ns ′ was subtracted from experimental estimates of d β ′ , providing an unbiased estimate of d o ′ . Estimates of d o ′ exhibited trends consistent with expectations of an angiography system that is quantum limited for high DTD and compromised by detector electronic readout noise for low DTD conditions. Results suggest that these methods provide d o ′ estimates which are accurate and precise for d o ′ ⩾ ∼ 1.0 . Further, results demonstrated that the source of bias was detector electronic readout noise. In summary, this work presents theory and methods to test for the presence of bias in Hotelling model observers due to temporally variable non-stationary noise and correct this bias when the temporally variable non-stationary noise is independent and additive with respect to the test object signal.