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Purpose: Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the potential to improve the image quality (IQ) over the filtered back projection method (FBP) and produce images quickly, performance generalizability of the data-driven DL methods is not fully understood yet. The main purpose of this work is to investigate the performance generalizability of a low-dose CT image denoising neural network in data acquired under different scan conditions, particularly relating to these three parameters: reconstruction kernel, slice thickness, and dose (noise) level. A secondary goal is to identify any underlying data property associated with the CT scan settings that might help predict the generalizability of the denoising network., Methods: We select the residual encoder-decoder convolutional neural network (REDCNN) as an example of a low-dose CT image denoising technique in this work. To study how the network generalizes on the three imaging parameters, we grouped the CT volumes in the Low-Dose Grand Challenge (LDGC) data into three pairs of training datasets according to their imaging parameters, changing only one parameter in each pair. We trained REDCNN with them to obtain six denoising models. We test each denoising model on datasets of matching and mismatching parameters with respect to its training sets regarding dose, reconstruction kernel, and slice thickness, respectively, to evaluate the denoising performance changes. Denoising performances are evaluated on patient scans, simulated phantom scans, and physical phantom scans using IQ metrics including mean-squared error (MSE), contrast-dependent modulation transfer function (MTF), pixel-level noise power spectrum (pNPS), and low-contrast lesion detectability (LCD)., Results: REDCNN had larger MSE when the testing data were different from the training data in reconstruction kernel, but no significant MSE difference when varying slice thickness in the testing data. REDCNN trained with quarter-dose data had slightly worse MSE in denoising higher-dose images than that trained with mixed-dose data (17%-80%). The MTF tests showed that REDCNN trained with the two reconstruction kernels and slice thicknesses yielded images of similar image resolution. However, REDCNN trained with mixed-dose data preserved the low-contrast resolution better compared to REDCNN trained with quarter-dose data. In the pNPS test, it was found that REDCNN trained with smooth-kernel data could not remove high-frequency noise in the test data of sharp kernel, possibly because the lack of high-frequency noise in the smooth-kernel data limited the ability of the trained model in removing high-frequency noise. Finally, in the LCD test, REDCNN improved the lesion detectability over the original FBP images regardless of whether the training and testing data had matching reconstruction kernels., Conclusions: REDCNN is observed to be poorly generalizable between reconstruction kernels, more robust in denoising data of arbitrary dose levels when trained with mixed-dose data, and not highly sensitive to slice thickness. It is known that reconstruction kernel affects the in-plane pNPS shape of a CT image, whereas slice thickness and dose level do not, so it is possible that the generalizability performance of this CT image denoising network highly correlates to the pNPS similarity between the testing and training data., (© 2021 American Association of Physicists in Medicine. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

Purpose: To compare cone-beam computed tomography (CT) navigation vs conventional CT image guidance during biopsies., Materials and Methods: Patients scheduled for image-guided biopsies were prospectively and randomly assigned to conventional CT guidance vs cone-beam CT navigation. Radiation dose, accuracy of final needle position, rate of histopathologic diagnosis, and number of needle repositions to reach the target (defined as pullback to adjust position) were compared., Results: A total of 58 patients (mean age, 57 y; 62.1% men) were randomized: 29 patients underwent 33 biopsies with CT guidance and 29 patients with 33 lesions underwent biopsy with cone-beam CT navigation. The average body mass index (BMI) was similar between groups, at 28.8 kg/m(2) ± 6.55 (P = .18). There was no difference between groups in terms of patient and lesion characteristics (eg, size, depth). The average lesion size was 29.1 ± 12.7mm for CT group vs 32.1mm ±16.8mm for cone-beam CT group (P < 0.59). Location of lesions was equally divided between the 2 groups, 20 lung lesions, 18 renal lesions and 20 other abdominal lesions. Mean number of needle repositions in the cone-beam CT group was 0.3 ± 0.5, compared with 1.9 ± 2.3 with conventional CT (P < .001). The average skin entry dose was 29% lower with cone-beam CT than with conventional CT (P < .04 accounting for BMI). The average estimated effective dose for the planning scan from phantom data was 49% lower with cone-beam CT vs conventional CT (P = .018). Accuracy, defined as the difference between planned and final needle positions, was 4.9 mm ± 4.1 for the cone-beam CT group, compared with 12.2 mm ± 8.1 for conventional CT (P < .001). Histopathologic diagnosis rates were similar between groups, at 90.9% for conventional CT and 93.9% for cone-beam CT (P = .67)., Conclusions: Cone-beam CT navigation for biopsies improved targeting accuracy with fewer needle repositions, lower skin entry dose, and lower effective dose for planning scan, and a comparable histopathologic diagnosis rate., (Copyright © 2016 SIR. All rights reserved.)

A straightforward method is presented to estimate peak skin doses (PSDs) delivered by computed tomography (CT) scanners. The measured PSD values are related to the well-known volume CT dose index (CTDI(vol)), displayed on the console of CT scanners. PSD measurement estimates were obtained, in four CT units, by placing radiochromic film on the surface of a CTDI head phantom. Six different X-ray tube currents including the maximum allowed value were used to irradiate the phantom. PSD and CTDI(vol) were independently measured and later related to the CTDI(vol) value displayed on the console. A scanner-specific relationship was found between the measured PSD and the associated CTDI(vol) displayed on the console. The measured PSD values varied between 27 and 136 mGy among all scanners when the routine head scan parameters were used. The results of this work allow relating the widely used CTDI(vol) to an actual radiation dose delivered to the skin of a patient.

Purpose: To measure radiation absorbed dose and its distribution in an anthropomorphic head phantom under clinically representative scan conditions in three widely used computed tomography (CT) scanners, and to relate those dose values to metrics such as high-contrast resolution, noise, and contrast-to-noise ratio (CNR) in the American College of Radiology CT accreditation phantom., Methods: By inserting optically stimulated luminescence dosimeters (OSLDs) in the head of an anthropomorphic phantom specially developed for CT dosimetry (University of Florida, Gainesville), we measured dose with three commonly used scanners (GE Discovery CT750 HD, Siemens Definition, Philips Brilliance 64) at two different clinical sites (Walter Reed National Military Medical Center, National Institutes of Health). The scanners were set to operate with the same data-acquisition and image-reconstruction protocols as used clinically for typical head scans, respective of the practices of each facility for each scanner. We also analyzed images of the ACR CT accreditation phantom with the corresponding protocols. While the Siemens Definition and the Philips Brilliance protocols utilized only conventional, filtered back-projection (FBP) image-reconstruction methods, the GE Discovery also employed its particular version of an adaptive statistical iterative reconstruction (ASIR) algorithm that can be blended in desired proportions with the FBP algorithm. We did an objective image-metrics analysis evaluating the modulation transfer function (MTF), noise power spectrum (NPS), and CNR for images reconstructed with FBP. For images reconstructed with ASIR, we only analyzed the CNR, since MTF and NPS results are expected to depend on the object for iterative reconstruction algorithms., Results: The OSLD measurements showed that the Siemens Definition and the Philips Brilliance scanners (located at two different clinical facilities) yield average absorbed doses in tissue of 42.6 and 43.1 mGy, respectively. The GE Discovery delivers about the same amount of dose (43.7 mGy) when run under similar operating and image-reconstruction conditions, i.e., without tube current modulation and ASIR. The image-metrics analysis likewise showed that the MTF, NPS, and CNR associated with the reconstructed images are mutually comparable when the three scanners are run with similar settings, and differences can be attributed to different edge-enhancement properties of the applied reconstruction filters. Moreover, when the GE scanner was operated with the facility's scanner settings for routine head exams, which apply 50% ASIR and use only approximately half of the 100%-FBP dose, the CNR of the images showed no significant change. Even though the CNR alone is not sufficient to characterize the image quality and justify any dose reduction claims, it can be useful as a constancy test metric., Conclusions: This work presents a straightforward method to connect direct measurements of CT dose with objective image metrics such as high-contrast resolution, noise, and CNR. It demonstrates that OSLD measurements in an anthropomorphic head phantom allow a realistic and locally precise estimation of magnitude and spatial distribution of dose in tissue delivered during a typical CT head scan. Additional objective analysis of the images of the ACR accreditation phantom can be used to relate the measured doses to high contrast resolution, noise, and CNR.

The purpose of this project was to assess the feasibility of imaging the velopharynx of adult volunteers during repetitive speech, using gated magnetic resonance imaging (MRI). Although a number of investigators have used conventional MRI in the study of the human vocal tract, the mismatch between the lengthy time necessary to acquire sufficiently detailed images and the rapidity of movement of the vocal tract during speech has forced investigators to acquire images either while the subject is at rest or during sustained utterances. The technique used here acquired a portion of each image during repetitive utterances, building the full image over multiple utterance cycles. The velopharyngeal portal was imaged on a 1.5-Tesla GE Signa LX 8.2 platform with gated fast spoiled gradient echo protocol. An external 1-Hertz trigger was fed to the cardiac gate. Subjects synchronized utterance of consonant-vowel syllables to a flashing light synchronized with the external trigger. Each acquisition of 30 phases per second at a single-slice location took 22 to 29 seconds. Four consonant-vowel syllables (/pa/, /ma/, /sa/, and /ka/) were evaluated. Subjects vocalized throughout the acquisition, beginning 5 to 6 seconds beforehand to establish a regular rhythm. Imaging of the velopharyngeal portal was performed for sagittal, velopharyngeal axial (aligned perpendicular to the "knee" of the velum), axial, and coronal planes. Volumes were obtained by sequential acquisition of six to 10 slices (each with 30 phases) in the axial or sagittal planes during repetition of the /pa/ syllable. Spatiotemporal volumes of the single-slice data were sectioned to provide time-motion images (analogous to M-mode echocardiograms). Three-dimensional dynamic volume renderings of palate motion were displayed interactively (Vortex; CieMed, Singapore). A method suitable for the collection and visualization of four-dimensional information regarding monosyllabic speech using gated MRI was developed. These techniques were applied to a population of adult volunteer subjects with no history of speech problems and two patients with a history of cleft lip and palate. The techniques allowed good real-time visualization of velopharyngeal anatomy during its entire range of motion and was also able to image pathology-specific anatomic differences in the subjects with cleft lip and cleft palate. These methods may be applicable to a wide spectrum of problems in speech physiology research and for clinical decision-making regarding surgery for speech and outcomes analysis.