R Kaufman

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

PURPOSEnThis study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR™) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR™. Empirically derived dose reduction limits were established for ASiR™ for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence∕adulthood.nnnMETHODSnImage quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR™ blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR™ implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent∕adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR™ reconstruction to maintain noise equivalence of the 0% ASiR™ image.nnnRESULTSnThe ASiR™ algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR™ reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR™ presented a more smoothed appearance than the pre-ASiR™ 100% FBP image. Finally, relative to non-ASiR™ images with 100% of standard dose across the pediatric phantom age spectrum, similar noise levels were obtained in the images at a dose reduction of 48% with 40% ASIR™ and a dose reduction of 82% with 100% ASIR™.nnnCONCLUSIONSnThe authors work was conducted to identify the dose reduction limits of ASiR™ for a pediatric oncology population using automatic tube current modulation. Improvements in noise levels from ASiR™ reconstruction were adapted to provide lower radiation exposure (i.e., lower mA) instead of improved image quality. We have demonstrated for the image quality standards required at our institution, a maximum dose reduction of 82% can be achieved using 100% ASiR™; however, to negate changes in the appearance of reconstructed images using ASiR™ with a medium to low frequency noise preserving reconstruction filter (i.e., standard), 40% ASiR™ was implemented in our clinic for 42%-48% dose reduction at all pediatric ages without a visually perceptible change in image quality or image noise.

Size-specific dose estimate (SSDE) provides a simple method to calculate organ dose for pediatric CT examinations

PURPOSEnTo investigate the correlation of size-specific dose estimate (SSDE) with absorbed organ dose, and to develop a simple methodology for estimating patient organ dose in a pediatric population (5-55 kg).nnnMETHODSnFour physical anthropomorphic phantoms representing a range of pediatric body habitus were scanned with metal oxide semiconductor field effect transistor (MOSFET) dosimeters placed at 23 organ locations to determine absolute organ dose. Phantom absolute organ dose was divided by phantom SSDE to determine correlation between organ dose and SSDE. Organ dose correlation factors (CF(organ)(SSDE)) were then multiplied by patient-specific SSDE to estimate patient organ dose. The [CF(organ)(SSDE)) were used to retrospectively estimate individual organ doses from 352 chest and 241 abdominopelvic pediatric CT examinations, where mean patient weight was 22 kg ± 15 (range 5-55 kg), and mean patient age was 6 yrs ± 5 (range 4 months to 23 yrs). Patient organ dose estimates were compared to published pediatric Monte Carlo study results.nnnRESULTSnPhantom effective diameters were matched with patient population effective diameters to within 4 cm; thus, showing appropriate scalability of the phantoms across the entire pediatric population in this study. Individual CF(organ)(SSDE) were determined for a total of 23 organs in the chest and abdominopelvic region across nine weight subcategories. For organs fully covered by the scan volume, correlation in the chest (average 1.1; range 0.7-1.4) and abdominopelvic region (average 0.9; range 0.7-1.3) was near unity. For organ/tissue that extended beyond the scan volume (i.e., skin, bone marrow, and bone surface), correlation was determined to be poor (average 0.3; range: 0.1-0.4) for both the chest and abdominopelvic regions, respectively. A means to estimate patient organ dose was demonstrated. Calculated patient organ dose, using patient SSDE and CF(organ)(SSDE), was compared to previously published pediatric patient doses that accounted for patient size in their dose calculation, and was found to agree in the chest to better than an average of 5% (27.6/26.2) and in the abdominopelvic region to better than 2% (73.4/75.0).nnnCONCLUSIONSnFor organs fully covered within the scan volume, the average correlation of SSDE and organ absolute dose was found to be better than ± 10%. In addition, this study provides a complete list of organ dose correlation factors (CF(organ)(SSDE)) for the chest and abdominopelvic regions, and describes a simple methodology to estimate individual pediatric patient organ dose based on patient SSDE.

Clinical and CT features of benign pneumatosis intestinalis in pediatric hematopoietic stem cell transplant and oncology patients

BackgroundPneumatosis intestinalis in children is associated with a wide variety of underlying conditions and often has a benign course. The CT features of this condition have not been systematically investigated.ObjectiveDefining benign pneumatosis intestinalis as pneumatosis intestinalis that resolved with medical management alone, we sought to: (1) determine whether the incidence of benign pneumatosis intestinalis had increased at our pediatric cancer hospital; (2) characterize CT features of benign pneumatosis intestinalis; and (3) determine the relationship between imaging features and clinical course of benign pneumatosis intestinalis in this cohort.Materials and methodsRadiology reports from November 1994 to December 2006 were searched for “pneumatosis intestinalis,” “free intraperitoneal air,” and “portal venous air or gas.” Corresponding imaging was reviewed by two radiologists who confirmed pneumatosis intestinalis and recorded the presence of extraluminal free air, degree of intramural gaseous distension, number of involved bowel segments, and time to pneumatosis resolution.ResultsThe search revealed 12 boys and 4 girls with pneumatosis intestinalis; 11 were hematopoietic stem cell transplant recipients. The annual incidences of benign pneumatosis have not changed at our institution. Increases in intramural distension marginally correlated with the number of bowel segments involved (P=0.08). Three patients had free air and longer times to resolution of pneumatosis (P=0.03).ConclusionMale children may be at increased risk of benign pneumatosis intestinalis. The incidence of benign pneumatosis at our institution is proportional to the number of hematopoietic stem cell transplants. The degree of intramural distension may correlate with the number of bowel segments involved. Patients with free air have a longer time to resolution of benign pneumatosis.

Establishing a standard calibration methodology for MOSFET detectors in computed tomography dosimetry

PURPOSEnThe use of metal-oxide-semiconductor field-effect transistor (MOSFET) detectors for patient dosimetry has increased by ~25% since 2005. Despite this increase, no standard calibration methodology has been identified nor calibration uncertainty quantified for the use of MOSFET dosimetry in CT. This work compares three MOSFET calibration methodologies proposed in the literature, and additionally investigates questions relating to optimal time for signal equilibration and exposure levels for maximum calibration precision.nnnMETHODSnThe calibration methodologies tested were (1) free in-air (FIA) with radiographic x-ray tube, (2) FIA with stationary CT x-ray tube, and (3) within scatter phantom with rotational CT x-ray tube. Each calibration was performed at absorbed dose levels of 10, 23, and 35 mGy. Times of 0 min or 5 min were investigated for signal equilibration before or after signal read out.nnnRESULTSnCalibration precision was measured to be better than 5%-7%, 3%-5%, and 2%-4% for the 10, 23, and 35 mGy respective dose levels, and independent of calibration methodology. No correlation was demonstrated for precision and signal equilibration time when allowing 5 min before or after signal read out. Differences in average calibration coefficients were demonstrated between the FIA with CT calibration methodology 26.7 ± 1.1 mV cGy(-1) versus the CT scatter phantom 29.2 ± 1.0 mV cGy(-1) and FIA with x-ray 29.9 ± 1.1 mV cGy(-1) methodologies. A decrease in MOSFET sensitivity was seen at an average change in read out voltage of ~3000 mV.nnnCONCLUSIONSnThe best measured calibration precision was obtained by exposing the MOSFET detectors to 23 mGy. No signal equilibration time is necessary to improve calibration precision. A significant difference between calibration outcomes was demonstrated for FIA with CT compared to the other two methodologies. If the FIA with a CT calibration methodology was used to create calibration coefficients for the eventual use for phantom dosimetry, a measurement error ~12% will be reflected in the dosimetry results. The calibration process must emulate the eventual CT dosimetry process by matching or excluding scatter when calibrating the MOSFETs. Finally, the authors recommend that the MOSFETs are energy calibrated approximately every 2500-3000 mV.

Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 (n) , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86u2009u2009±u2009u20090.03 for pediatric patient protocols, and 0.85u2009u2009±u2009u20090.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

The role of chest computed tomography (CT) as a surveillance tool in children with high-risk neuroblastoma.

Standardization of imaging obtained in children with neuroblastoma is not well established. This study examines chest CT in pediatric patients with high‐risk neuroblastoma.

Magnetic resonance imaging is the preferred method to assess treatment-related skeletal changes in children with brain tumors

To evaluate the growing skeleton for potential altered skeletalgenesis associated with antiangiogenesis therapy.

Full Dose-Reduction Potential of Statistical Iterative Reconstruction for Head CT Protocols in a Predominantly Pediatric Population

The authors set out to determine the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population while maintaining similar appearance and level of image noise in the reconstructed image. Dose-reduced head protocols using an adaptive statistical iterative reconstruction were compared for image quality with the original filtered back-projection reconstructed protocols in a phantom and CT dose index and image noise magnitude were assessed in 737 pre- and post-dose-reduced examinations. Implementation of 40% and 60% adaptive statistical iterative reconstruction led to an average reduction in the volume CT dose index of 43% for brain, 41% for orbit, 30% for maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years of age, while improving the contrast-to-noise ratio of low-contrast soft-tissue targets. BACKGROUND AND PURPOSE: A statistical iterative reconstruction algorithm provides an effective approach to reduce patient dose by compensating for increased image noise in CT due to reduced radiation output. However, after a point, the degree to which a statistical iterative algorithm is used for image reconstruction changes the image appearance. Our aim was to determine the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population while maintaining similar appearance and level of image noise in the reconstructed image. MATERIALS AND METHODS: Select head examinations (brain, orbits, sinus, maxilla, and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction were compared for image quality with the original filtered back-projection reconstructed protocols in a phantom by using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio, and spatial resolution. Dose-reduction estimates were based on CT dose index values. Patient volume CT dose index and image noise magnitude were assessed in 737 pre- and post-dose-reduced examinations. RESULTS: Image noise texture was acceptable for up to 60% adaptive statistical iterative reconstruction for the soft reconstruction kernel (at both 100 and 120 kV[peak]) and up to 40% adaptive statistical iterative reconstruction for the standard reconstruction kernel. Implementation of 40% and 60% adaptive statistical iterative reconstruction led to an average reduction in the volume CT dose index of 43% for brain, 41% for orbit, 30% for maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years of age, while maintaining an average noise magnitude difference of 0.1% (range, −3% to 5%), improving the contrast-to-noise ratio of low-contrast soft-tissue targets and the spatial resolution of high-contrast bony anatomy, compared with filtered back-projection. CONCLUSIONS: The methodology in this study demonstrates maximizing patient dose reduction and maintaining image quality by using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examinations.

Reply to: Radiation dose reduction thanks to split‐bolus multi‐1 detector computer tomography (MDCT) in children with non‐thoracic neuroblastoma

To the Editor: We thank Scialpi and colleagues for their letter supporting the premise of limiting radiation exposure from computed tomography in children with high-risk neuroblastoma. In their letter, they describe a new technique of administering a split bolus dose of contrast when performing computed tomography (CT).[1] They propose that this technique, as demonstrated in a single 14-year-old patient, leads to decreased radiation exposure delivered by CT. While we commend the authors for attempting to decrease radiation exposure from CT, we have questions about the technique described and the relevance to our manuscript, “The role of chest computed tomography (CT) as a surveillance tool in children with high-risk neuroblastoma.”[2] We are unclear how their technique leads to radiation dose savings. In general, a split bolus of contrast does not inherently provide radiation dose savings; instead, it is a change in image contrast that may allow for lower exposure factors. Their letter does not describe how the split bolus contrast dose contributes to decreased radiation dose. Further, although the authors provide a very low dose length product (DLP) for their patient, in order to determine the actual dose savings to the patient, preand postimplementation radiation dose information is needed as well as the length of the patient and CTDIvol value(s). As none of these parameters were provided, it is unclear if the patient was spared radiation exposure as a result of this technique. The authors conclude that their technique supports our publication’s proposal. However, our conclusion was to eliminate chest CT in patients without evidence of neuroblastoma in the chest at diagnosis in order to reduce radiation exposure. In their letter, Scialpi et al. include CT of the chest which contradicts our recommendation. Although Scialpi and colleagues’ letter to the editor may have merit as a technical note, it is unclear if their technique, as described, further reduces radiation exposure to the patient. We feel that this technique should be evaluated meticulously by a radiologic journal to determine validity. Regardless of the ultimate assessment of their technique, we recommend the elimination of surveillance chest CT in patients with non-thoracic high-risk neuroblastoma. Sara M. Federico, MD Departments of Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105 and Departments of Pediatrics, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee 38163

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool

PURPOSEnTo develop an automated methodology to estimate patient examination dose in digital radiography (DR) imaging using DICOM metadata as a quality assurance (QA) tool.nnnMETHODSnPatient examination and demographical information were gathered from metadata analysis of DICOM header data. The x-ray system radiation output (i.e., air KERMA) was characterized for all filter combinations used for patient examinations. Average patient thicknesses were measured for head, chest, abdomen, knees, and hands using volumetric images from CT. Backscatter factors (BSFs) were calculated from examination kVp. Patient entrance skin air KERMA (ESAK) was calculated by (1) looking up examination technique factors taken from DICOM header metadata (i.e., kVp and mA s) to derive an air KERMA (k air) value based on an x-ray characteristic radiation output curve; (2) scaling k air with a BSF value; and (3) correcting k air for patient thickness. Finally, patient entrance skin dose (ESD) was calculated by multiplying a mass-energy attenuation coefficient ratio by ESAK. Patient ESD calculations were computed for common DR examinations at our institution: dual view chest, anteroposterior (AP) abdomen, lateral (LAT) skull, dual view knee, and bone age (left hand only) examinations.nnnRESULTSnESD was calculated for a total of 3794 patients; mean age was 11 ± 8 yr (range: 2 months to 55 yr). The mean ESD range was 0.19-0.42 mGy for dual view chest, 0.28-1.2 mGy for AP abdomen, 0.18-0.65 mGy for LAT view skull, 0.15-0.63 mGy for dual view knee, and 0.10-0.12 mGy for bone age (left hand) examinations.nnnCONCLUSIONSnA methodology combining DICOM header metadata and basic x-ray tube characterization curves was demonstrated. In a regulatory era where patient dose reporting has become increasingly in demand, this methodology will allow a knowledgeable user the means to establish an automatable dose reporting program for DR and perform patient dose related QA testing for digital x-ray imaging.