Anne Catrine Trægde Martinsen

Iterative reconstruction reduces abdominal CT dose.

OBJECTIVE In medical imaging, lowering radiation dose from computed tomography scanning, without reducing diagnostic performance is a desired achievement. Iterative image reconstruction may be one tool to achieve dose reduction. This study reports the diagnostic performance using a blending of 50% statistical iterative reconstruction (ASIR) and filtered back projection reconstruction (FBP) compared to standard FBP image reconstruction at different dose levels for liver phantom examinations. METHODS An anthropomorphic liver phantom was scanned at 250, 185, 155, 140, 120 and 100 mAs, on a 64-slice GE Lightspeed VCT scanner. All scans were reconstructed with ASIR and FBP. Four readers evaluated independently on a 5-point scale 21 images, each containing 32 test sectors. In total 672 areas were assessed. ROC analysis was used to evaluate the differences. RESULTS There was a difference in AUC between the 250 mAs FBP images and the 120 and 100 mAs FBP images. ASIR reconstruction gave a significantly higher diagnostic performance compared to standard reconstruction at 100 mAs. CONCLUSION A blending of 50-90% ASIR and FBP may improve image quality of low dose CT examinations of the liver, and thus give a potential for reducing radiation dose.

Interphantom and interscanner variations for Hounsfield units—establishment of reference values for HU in a commercial QA phantom

In computer tomography (CT) diagnostics, the measured Hounsfield units (HU) are used to characterize tissue and are in that respect compared to nominal HU values found in the radiological literature. Quality assurance (QA) phantoms are commercially available with a variety of tissue substitutes and materials to test the HU values in CT. It is however recognized from CT physics that the HU for a given material is energy dependent and may vary substantially between scanners. The aim of this study is to analyze the characteristics of a commonly used QA phantom, the Catphan 500/600 (The Phantom Laboratory, NY). Four CT phantoms were scanned on one CT scanner to examine possible interphantom variations in HU values. Secondly, one selected phantom was scanned at three kVp levels on eight different CT scanners. The interphantom variations in HU values were small, in the range 2-5 HU. The interscanner variations were however substantial, in the range 7-56 HU depending on energy and material. Varying the x-ray energy produced a shift in the measured HU of up to 79 HU on one scanner. Reference HU values for the eight sensitometric test materials in Catphan are provided for eight CT scanner models from four vendors. The reference HU values are provided for 80, 120 and 140 kVp. Our results suggest that scanner-independent threshold levels for HU should be used only with extreme caution. Tissue characterization can be used provided that a scanner-specific data set for normal and abnormal is determined.

How to measure CT image quality: variations in CT-numbers, uniformity and low contrast resolution for a CT quality assurance phantom.

PURPOSE Quality assurance (QA) phantoms for testing different image quality parameters in computed tomography (CT) are commercially available. Such phantoms are also used as reference for acceptance in the specifications of CT-scanners. The aim of this study was to analyze the characteristics of the most commonly used QA phantom in CT: Catphan 500/504/600. METHODS Nine different phantoms were scanned on the same day, on one CT-scanner with the same parameter settings. Interphantom variations in CT-number values, image uniformity and low contrast resolution were evaluated for the phantoms. Comparisons between manual image analysis and results obtained from the automatic evaluation software QAlite were performed. RESULTS Some interphantom variations were observed in the low contrast resolution and the CT-number modules of the phantoms. Depending on the chosen regulatory framework, the variations in CT-numbers can be interpreted as substantial. The homogenous modules were found more invariable. However, the automatic image analysis software QAlite measures image uniformity differently than recommended in international standards, and will not necessarily give results in agreement with these standards. CONCLUSIONS It is important to consider the interphantom variations in relation to ones framework, and to be aware of which phantom is used to study CT-numbers and low contrast resolution for a specific scanner. Comparisons with predicted values from manual and acceptance values should be performed with care and consideration. If automatic software-based evaluations are to be used, users should be aware that large differences can exist for the image uniformity testing.

Improved image quality of low-dose thoracic CT examinations with a new postprocessing software*

In 2008 a phantom study indicated that there is a potential for reducing the CT doses when using a new postprocessing filter. The purpose of this study was to test this new postprocessing filter clinically for low‐dose chest CT examinations, to assess whether the diagnostic performance is the same or improved. A standardized clinical chest CT protocol was used on patients with colorectal cancer. Only mA settings changed between patients according to patient size. One standard and one low‐dose chest protocol were performed for all patients. The low‐dose images were postprocessed with a new software filter, which provides context‐controlled restoration of digital images by using adaptive filters. Three radiologists assessed randomly all the images independently. A total of 24 scan series were evaluated with respect to image quality according to quality criteria from the European guidelines for chest CT using a five‐point scale; 576 details were assessed. Overall mean score is the average score for all details rated for all three readers for all full‐dose series, low‐dose series and low‐dose enhanced series, respectively. The statistical methods used for comparison were paired sampled t‐test and intraclass correlation coefficient. The postprocessing filter improved the diagnostic performance compared to the unenhanced low‐dose images. Mean score for full‐dose, low‐dose and low‐dose enhanced series were 3.8, 3.0 and 3.3, respectively. For all patients the full‐dose series gave higher scores than the low‐dose series. Intraclass correlation coefficients were 0.2, 0.1 and 0.3 for the full‐dose, low‐dose and low‐dose enhanced series, respectively. There is a potential for improving diagnostic performance of low‐dose CT chest examinations using this new postprocessing filter. PACS number: 87.57.C‐, 87.57.Q‐

Image Quality in Oncologic Chest Computerized Tomography With Iterative Reconstruction: A Phantom Study.

Objective The purpose of this study was to validate iterative reconstruction technique in oncologic chest computed tomography (CT). Methods An anthropomorphic thorax phantom with 4 simulated tumors was scanned on a 64-slice CT scanner with 2 different iterative reconstruction techniques: one model based (MBIR) and one hybrid (ASiR). Dose levels of 14.9, 11.1, 6.7, and 0.6 mGy were used, and all images were reconstructed with filtered back projection (FBP) and both iterative reconstruction algorithms. Hounsfield units (HU) and absolute noise were measured in the tumors, lung, heart, diaphragm, and muscle. Contrast-to-noise ratios (CNRs) and signal-to-noise ratios (SNRs) were calculated. Results Model-based iterative reconstruction (MBIR) increased CNRs of the tumors (21.1–192.2) and SNRs in the lung (−49.0–165.6) and heart (3.1–8.5) at all dose levels compared with FBP (CNR, 1.1–23.0; SNR, −7.5–31.6 and 0.2–1.1) and with adaptive statistical iterative reconstruction (CNR, 1.2–33.2; SNR, −7.3–37.7 and 0.2–1.5). At the lowest dose level (0.6 mGy), MBIR reduced the cupping artifact (HU range: 17.0 HU compared with 31.4–32.2). An HU shift in the negative direction was seen with MBIR. Conclusions Quantitative image quality parameters in oncologic chest CT are improved with MBIR compared with FBP and simpler iterative reconstruction algorithms. Artifacts at low doses are reduced. A shift in HU values was shown; thus, absolute HU values should be used with care.

Classification of fatty and dense breast parenchyma: comparison of automatic volumetric density measurement and radiologists’ classification and their inter-observer variation:

Background Automatically calculated breast density is a promising alternative to subjective BI-RADS density assessment. However, such software needs a cutoff value for density classification. Purpose To determine the volumetric density threshold which classifies fatty and dense breasts with highest accuracy compared to average BI-RADS density assessment, and to analyze radiologists’ inter-observer variation. Material and Methods A total of 537 full field digital mammography examinations were randomly selected from a population based screening program. Five radiologists assessed density using the BI-RADS density scale, where BI-RADS I–II were classified as fatty and III–IV as dense. A commercially available software (Quantra) calculated volumetric breast density. We calculated the cutoff (threshold) values in volumetric density that yielded highest accuracy compared to median and individual radiologists’ classification. Inter-observer variation was analyzed using the kappa statistic. Results The threshold that best matched the median radiologists’ classification was 10%, which resulted in 87% accuracy. Thresholds that best matched individual radiologist’s classification had a range of 8–15%. A total of 191 (35.6 %) cases were scored both dense and fatty by at least one radiologist. Fourteen (2.6 %) cases were unanimously scored by the radiologists, yet differently using automatic assessment. The agreement (kappa) between reader’s median classification and individual radiologists was 0.624 to 0.902, and agreement between median classification and Quantra was 0.731. Conclusion The optimal volumetric threshold of 10% using automatic assessment would classify breast parenchyma as fatty or dense with substantial accuracy and consistency compared to radiologists’ BI-RADS categorization, which suffers from high inter-observer variation.

Tumor-Absorbed dose for non-hodgkin lymphoma patients treated with the anti-CD37 antibody radionuclide conjugate 177Lu-Lilotomab Satetraxetan

177Lu-lilotomab satetraxetan is a novel antibody radionuclide conjugate currently tested in a phase 1/2a first-in-human dosage escalation trial for patients with relapsed CD37+ indolent non-Hodgkin lymphoma. The aim of this work was to develop dosimetric methods and calculate tumor-absorbed radiation doses for patients treated with 177Lu-lilotomab satetraxetan. Methods: Patients were treated at escalating injected activities (10, 15 and 20 MBq/kg) of 177Lu-lilotomab satetraxetan and with different predosing, with or without 40 mg of unlabeled lilotomab. Eight patients were included for the tumor dosimetry study. Tumor radioactivity concentrations were calculated from SPECT acquisitions at multiple time points, and tumor masses were delineated from corresponding CT scans. Tumor-absorbed doses were then calculated using the OLINDA sphere model. To perform voxel dosimetry, the SPECT/CT data and an in-house–developed MATLAB program were combined to investigate the dose rate homogeneity. Results: Twenty-six tumors in 8 patients were ascribed a mean tumor-absorbed dose. Absorbed doses ranged from 75 to 794 cGy, with a median of 264 cGy across different dosage levels and different predosing. A significant correlation between the dosage level and tumor-absorbed dose was found. Twenty-one tumors were included for voxel dosimetry and parameters describing dose–volume coverage calculated. The investigation of intratumor voxel doses indicates that mean tumor dose is correlated to these parameters. Conclusion: Tumor-absorbed doses for patients treated with 177Lu-lilotomab satetraxetan are comparable to doses reported for other radioimmunotherapy compounds. Although the intertumor variability was considerable, a correlation between tumor dose and patient dosage level was found. Our results indicate that mean dose may be used as the sole dosimetric parameter on the lesion level.

BI-RADS Density Classification From Areometric and Volumetric Automatic Breast Density Measurements.

RATIONALE AND OBJECTIVES The aim of our study was to classify breast density using areometric and volumetric automatic measurements to best match Breast Imaging-Reporting and Data System (BI-RADS) density scores, and determine which technique best agrees with BI-RADS. Second, this study aimed to provide a set of threshold values for areometric and volumetric density to estimate BI-RADS categories. MATERIALS AND METHODS We randomly selected 537 full-field digital mammography examinations from a population-based screening program. Five radiologists assessed breast density using BI-RADS with all views available. A commercial program calculated areometric and volumetric breast density automatically. We compared automatically calculated density to all BI-RADS density thresholds using area under the receiver operating characteristic curve, and used Youdens index to estimate thresholds in automatic densities, with matching sensitivity and specificity. The 95% confidence intervals were estimated by bootstrapping. RESULTS Areometric density correlated well with volumetric density (r(2) = 0.76, excluding outliers, n = 2). For the BI-RADS threshold between II and III, areometric and volumetric assessment showed about equal area under the curve (0.94 vs. 0.93). For the threshold between I and II, areometric assessment was better than volumetric assessment (0.91 vs. 0.86). For the threshold between III and IV, volumetric assessment was better than areometric assessment (0.97 vs. 0.92). CONCLUSIONS Volumetric assessment is equal to or better than areometric assessment for the most clinically relevant thresholds (ie, between scattered fibroglandular and heterogeneously dense, and between heterogeneously dense and extremely dense breasts). Thresholds found in this study can be applied in daily practice to automatic measurements of density to estimate BI-RADS classification.

A Liver Phantom Study: Ct Radiation Dose Reduction and Different Image Reconstruction Algorithms Affect Diagnostic Quality

Objective The aim of this study was to evaluate whether iterative reconstruction techniques for different dose levels and/or reduction of tube potential can increase liver lesion detectability. Methods An anthropomorphic liver phantom was scanned at different dose levels (CTDIvol 15 mGy, 7.5 mGy, 5 mGy, and 2.6 mGy) and tube potential levels (120 kV, 100 kV, and 80 kV). Images were reconstructed with the following algorithms: filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR) 40%, and a model-based iterative reconstruction (Veo). The presence or absence of lesions was assessed independently on a 4-point scale by 4 readers. The areas under the receiver operating characteristic curve were calculated. Results Veo improved detectability of hyperdense liver lesions compared with both FBP and ASiR 40% at most dose levels (15 mGy, 7.5 mGy, and 5 mGy with P < 0.05). Veo also improved detectability at reduced tube potential compared with FBP (120 kV, 100 kV, and 80 kV at 5 mGy with P < 0.05) and ASiR 40% (120 kV and 100 kV at 5 mGy with P < 0.05). For ASiR 40%, the area under the receiver operating characteristic curve was significantly larger compared with FBP only at dose levels 7.5 mGy and 2.6 mGy at 120 kV. In general, the reduction of tube potential reduced the lesion detectability. Conclusions This study shows that iterative reconstruction algorithms, in particular Veo, improve lesion detectability in a liver phantom. However, a too aggressive dose reduction may result in poorer image quality. Results considering different tube potentials diverged, thus careful consideration is necessary upon tube potential reduction.

Improved Liver Lesion Conspicuity With Iterative Reconstruction in Computed Tomography Imaging

Studies on iterative reconstruction techniques on computed tomographic (CT) scanners show reduced noise and changed image texture. The purpose of this study was to address the possibility of dose reduction and improved conspicuity of lesions in a liver phantom for different iterative reconstruction algorithms. An anthropomorphic upper abdomen phantom, specially designed for receiver operating characteristic analysis was scanned with 2 different CT models from the same vendor, GE CT750 HD and GE Lightspeed VCT. Images were obtained at 3 dose levels, 5, 10, and 15mGy, and reconstructed with filtered back projection (FBP), and 2 different iterative reconstruction algorithms; adaptive statistical iterative reconstruction and Veo. Overall, 5 interpreters evaluated the images and receiver operating characteristic analysis was performed. Standard deviation and the contrast to noise ratio were measured. Veo image reconstruction resulted in larger area under curves compared with those adaptive statistical iterative reconstruction and FBP image reconstruction for given dose levels. For the CT750 HD, iterative reconstruction at the 10mGy dose level resulted in larger or similar area under curves compared with FBP at the 15mGy dose level (0.88-0.95 vs 0.90). This was not shown for the Lightspeed VCT (0.83-0.85 vs 0.92). The results in this study indicate that the possibility for radiation dose reduction using iterative reconstruction techniques depends on both reconstruction technique and the CT scanner model used.