Detection of parathyroid adenomas with multiphase 4DCT: towards a true four-dimensional technique.

BACKGROUND: Four-dimensional computed tomography (4DCT) is a commonly performed examination in the management of primary hyperparathyroidism, combining three-dimensional imaging with enhancement over time as the fourth dimension. We propose a novel technique consisting of 16 different contrast phases instead of three or four different phases. The main aim of this study was to ascertain whether this protocol allows the detection of parathyroid adenomas within dose limits. Our secondary aim was to examine the enhancement of parathyroid lesions over time. METHODS: For this prospective study, we included 15 patients with primary hyperparathyroidism and a positive ultrasound prior to surgery. We performed 4DCT with 16 different phases: an unenhanced phase followed by 11 consecutive arterial phases and 4 venous phases. Continuous axial scanning centered on the thyroid was performed over a fixed 8 cm or 16 cm coverage volume after the start of contrast administration. RESULTS: In all patients, an enlarged parathyroid lesion was demonstrated, and the mean lesion size was 13.6 mm. The mean peak arterial enhancement for parathyroid lesions was 384 Hounsfield units (HU) compared to 333 HU for the normal thyroid. No significant difference could be found. The time to peak (TTP) was significantly earlier for parathyroid adenomas than for normal thyroid tissue: 30.8 s versus 32.3 s (p value 0.008). The mean slope of increase (MSI) of the enhancement curve was significantly steeper than that of normal thyroid tissue: 29.8% versus 22.2% (p value 0.012). The mean dose length product was 890.7 mGy cm with a calculated effective dose of 6.7 mSv. CONCLUSION: Our 4DCT protocol may allow better visualization of the pattern of enhancement of parathyroid lesions, as enhancement over time curves can be drawn. In this way, wash-in and wash-out of contrast in suspected lesions can be readily demonstrated. Motion artifacts are less problematic as multiple phases are available. Exposure to our proposed 4DCT technique is comparable to that for classic helical 4DCT. Careful selection of parameters (lowering kV and SNR) can help to further reduce the dose.

Lung nodule detection by microdose CT versus chest radiography (standard and dual-energy subtracted).

OBJECTIVE: The purpose of this study was to investigate the feasibility of microdose CT using a comparable dose as for conventional chest radiographs in two planes including dual-energy subtraction for lung nodule assessment. MATERIALS AND METHODS: We investigated 65 chest phantoms with 141 lung nodules, using an anthropomorphic chest phantom with artificial lung nodules. Microdose CT parameters were 80 kV and 6 mAs, with pitch of 2.2. Iterative reconstruction algorithms and an integrated circuit detector system (Stellar, Siemens Healthcare) were applied for maximum dose reduction. Maximum intensity projections (MIPs) were reconstructed. Chest radiographs were acquired in two projections with bone suppression. Four blinded radiologists interpreted the images in random order. RESULTS: A soft-tissue CT kernel (I30f) delivered better sensitivities in a pilot study than a hard kernel (I70f), with respective mean (SD) sensitivities of 91.1%±2.2% versus 85.6%±5.6% (p=0.041). Nodule size was measured accurately for all kernels. Mean clustered nodule sensitivity with chest radiography was 45.7%±8.1% (with bone suppression, 46.1%±8%; p=0.94); for microdose CT, nodule sensitivity was 83.6%±9% without MIP (with additional MIP, 92.5%±6%; p<10(-3)). Individual sensitivities of microdose CT for readers 1, 2, 3, and 4 were 84.3%, 90.7%, 68.6%, and 45.0%, respectively. Sensitivities with chest radiography for readers 1, 2, 3, and 4 were 42.9%, 58.6%, 36.4%, and 90.7%, respectively. In the per-phantom analysis, respective sensitivities of microdose CT versus chest radiography were 96.2% and 75% (p<10(-6)). The effective dose for chest radiography including dual-energy subtraction was 0.242 mSv; for microdose CT, the applied dose was 0.1323 mSv. CONCLUSION: Microdose CT is better than the combination of chest radiography and dual-energy subtraction for the detection of solid nodules between 5 and 12 mm at a lower dose level of 0.13 mSv. Soft-tissue kernels allow better sensitivities. These preliminary results indicate that microdose CT has the potential to replace conventional chest radiography for lung nodule detection.

Implementation of ultra-low-dose lung protocols in CT-guided lung biopsies: feasibility and safety in the clinical setting.

Objective To evaluate the use of ultra-low-dose computed tomography (ULDCT) for CT-guided lung biopsy versus standard-dose CT (SDCT). Methods CT-guided lung biopsies from 115 patients (50 ULDCT, 65 SDCT) were analyzed retrospectively. SDCT settings were 120 kVp with automatic mAs modulation. ULDCT settings were 80 kVp with fixed exposure (20 mAs). Two radiologists evaluated image quality (i.e., needle artifacts, lesion contouring, vessel recognition, visibility of interlobar fissures). Complications and histological results were also evaluated. Results ULDCT was considered feasible for all lung interventions, showing the same diagnostic accuracy as SDCT. Its mean total radiation dose (dose-length product) was significantly reduced to 34 mGy-cm (SDCT 426 mGy-cm). Image quality and complication rates ( P = 0.469) were consistent. Conclusions ULDCT for CT-guided lung biopsies appears safe and accurate, with a significantly reduced radiation dose. We therefore recommend routine clinical use of ULDCT for the benefit of patients and interventionalists.

An effective noise reduction method for multi-energy CT images that exploit spatio-spectral features.

PURPOSE: To develop and evaluate an image-domain noise reduction method for multi-energy CT (MECT) data. METHODS: Multi-Energy Non-Local Means (MENLM) is a technique that uses the redundant information in MECT images to achieve noise reduction. In this method, spatio-spectral features are used to determine the similarity between pixels, making the similarity evaluation more robust to image noise. The performance of this MENLM filter was tested on images acquired on a whole-body research photon counting CT system. The impact of filtering on image quality was quantitatively evaluated in phantom studies in terms of image noise level (standard deviation of pixel values), noise power spectrum (NPS), in-plane and cross-plane spatial resolution, CT number accuracy, material decomposition performance, and subjective low-contrast spatial resolution using the American College of Radiology (ACR) CT accreditation phantom. Clinical feasibility was assessed by performing MENLM on contrast-enhanced swine images and unenhanced cadaver head images using clinically relevant doses and dose rates. RESULTS: The phantom studies demonstrated that the MENLM filter reduced noise substantially and still preserved the shape and peak frequency of the NPS. With 80% noise reduction, MENLM filtering caused no degradation of high-contrast spatial resolution, as illustrated by the modulation transfer function (MTF) and slice sensitivity profile (SSP). CT number accuracy was also maintained for all energy channels, demonstrating that energy resolution was not affected by filtering. Material decomposition performance was improved with MENLM filtering. The subjective evaluation using the ACR phantom demonstrated an improvement in low-contrast performance. MENLM achieved effective noise reduction in both contrast-enhanced swine images and unenhanced cadaver head images, resulting in improved detection of subtle vascular structures and the differentiation of white/gray matter. CONCLUSION: In MECT, MENLM achieved around 80% noise reduction and greatly improved material decomposition performance and the detection of subtle anatomical/low-contrast features while maintaining spatial and energy resolution. MENLM filtering may improve diagnostic or functional analysis accuracy and facilitate radiation dose and contrast media reduction for MECT.

Model-based iterative reconstruction in ultra-low-dose pediatric chest CT: comparison with adaptive statistical iterative reconstruction.

PURPOSE: To evaluate image quality and dose reduction of ultra-low-dose pediatric chest CT reconstructed with model-based iterative reconstruction (MBIR), as compared with adaptive statistical iterative reconstruction (ASIR). MATERIALS AND METHODS: Fifty-seven patients (mean age 14 years, M:F=31:26) who underwent ultra-low-dose chest CT reconstructed with both MBIR and ASIR were enrolled in the study. The subjective and objective image qualities of both reconstruction techniques were assessed by 3 radiologists, and compared using statistical analysis. We also evaluated radiation dose of ultra-low-dose chest CT as well as degree of dose reduction in comparison to the prior CT (either standard dose or reduced dose protocol) available in 36 patients. RESULTS: The image quality of MBIR was superior to ASIR both subjectively and objectively. While MBIR showed preserved diagnostic acceptability in 100%, ASIR showed 92% at mean 0.31 mSv (range, 0.13-0.57 mSv) ultra-low-dose CT. In the 36 patients who underwent the prior CT, mean decrease in size-specific dose estimate (SSDE) and dose length product (DLP) at ultra-low-dose CT was 88% (range, 34% - 98%) and 86% (range,42% - 99%), respectively. CONCLUSIONS: MBIR significantly improves image quality, as compared to ASIR. Furthermore, MBIR facilitates diagnostically acceptable ultra-low-dose chest CT with nearly 90% less radiation.

Computed tomography overexposure as a consequence of extended scan length.

INTRODUCTION: This study aimed to raise awareness around the increased effective dose as scan length chosen is increased from standard protocol METHODS: The Monte Carlo-based software CT-Expo (G. Stamm (Medizinische Hochschule Hannover, Hannover, Germany) and H.D. Nagel (SASCRAD, Buchholz, Germany)) was used to simulate the effective dose increase as the scanned region of the standard protocol increased. RESULTS: The results of this study show that for scans with a high computed tomography dose index (CTDI)vol the patient could be exposed to an extra 1 mSv within 6 cm of overscan. Protocols that investigated large scan areas may not see a significant relative dose reduction because of the use of a lower CTDIvol ; however, radiation exposure should be kept as low as reasonably achievable. CONCLUSION: There is significant dose optimisation potential when strictly adhering to appropriate scan lengths within each imaging protocol wherever possible.