18F-fluorodeoxyglucose (FDG) PET or 18F-fluorothymidine (FLT) PET to assess early response to aromatase inhibitors (AI) in women with ER+ operable breast cancer in a window-of-opportunity study.

PURPOSE: This study evaluated the ability of 18F-Fluorodeoxyglucose (FDG) and 18F-Fluorothymidine (FLT) imaging with positron emission tomography (PET) to measure early response to endocrine therapy from baseline to just prior to surgical resection in estrogen receptor positive (ER+) breast tumors. METHODS: In two separate studies, women with early stage ER+ breast cancer underwent either paired FDG-PET (n = 22) or FLT-PET (n = 27) scans prior to endocrine therapy and again in the pre-operative setting. Tissue samples for Ki-67 were taken for all patients both prior to treatment and at the time of surgery. RESULTS: FDG maximum standardized uptake value (SUVmax) declined in 19 of 22 lesions (mean 17% (range -45 to 28%)). FLT SUVmax declined in 24 of 27 lesions (mean 26% (range -77 to 7%)). The Ki-67 index declined in both studies, from pre-therapy (mean 23% (range 1 to 73%)) to surgery [mean 8% (range < 1 to 41%)]. Pre- and post-therapy PET measures showed strong rank-order agreement with Ki-67 percentages for both tracers; however, the percent change in FDG or FLT SUVmax did not demonstrate a strong correlation with Ki-67 index change or Ki-67 at time of surgery. CONCLUSIONS: A window-of-opportunity approach using PET imaging to assess early response of breast cancer therapy is feasible. FDG and FLT-PET imaging following a short course of neoadjuvant endocrine therapy demonstrated measurable changes in SUVmax in early stage ER+ positive breast cancers. The percentage change in FDG and FLT-PET uptake did not correlate with changes in Ki-67; post-therapy SUVmax for both tracers was significantly associated with post-therapy Ki-67, an established predictor of endocrine therapy response.

The QIBA Profile for FDG PET/CT as an Imaging Biomarker Measuring Response to Cancer Therapy.

The Quantitative Imaging Biomarkers Alliance (QIBA) Profile for fluorodeoxyglucose (FDG) PET/CT imaging was created by QIBA to both characterize and reduce the variability of standardized uptake values (SUVs). The Profile provides two complementary claims on the precision of SUV measurements. First, tumor glycolytic activity as reflected by the maximum SUV (SUVmax) is measurable from FDG PET/CT with a within-subject coefficient of variation of 10%-12%. Second, a measured increase in SUVmax of 39% or more, or a decrease of 28% or more, indicates that a true change has occurred with 95% confidence. Two applicable use cases are clinical trials and following individual patients in clinical practice. Other components of the Profile address the protocols and conformance standards considered necessary to achieve the performance claim. The Profile is intended for use by a broad audience; applications can range from discovery science through clinical trials to clinical practice. The goal of this report is to provide a rationale and overview of the FDG PET/CT Profile claims as well as its context, and to outline future needs and potential developments.

The novel coronavirus disease (COVID-19) complicated by pulmonary embolism and acute respiratory distress syndrome.

Acute respiratory distress syndrome and coagulopathy played an important role in morbidity and mortality of severe COVID-19 patients. A higher frequency of pulmonary embolism (PE) than expected in COVID-19 patients was recently reported. The presenting symptoms for PE were untypical including dyspnea, which is one of the major symptoms in severe COVID-19, especially in those patients with acute respiratory distress syndrome (ARDS). We reported two COVID-19 cases with coexisting complications of PE and ARDS, aiming to consolidate the emerging knowledge of this global health emergency and raise the awareness that the hypoxemia or severe dyspnea in COVID-19 may be related to PE and not necessarily always due to the parenchymal disease.

Comparison of prediction models with radiological semantic features and radiomics in lung cancer diagnosis of the pulmonary nodules: a case-control study.

PURPOSE: To compare the ability of radiological semantic and quantitative texture features in lung cancer diagnosis of pulmonary nodules. MATERIALS AND METHODS: A total of N = 121 subjects with confirmed non-small-cell lung cancer were matched with 117 controls based on age and gender. Radiological semantic and quantitative texture features were extracted from CT images with or without contrast enhancement. Three different models were compared using LASSO logistic regression: "CS" using clinical and semantic variables, "T" using texture features, and "CST" using clinical, semantic, and texture variables. For each model, we performed 100 trials of fivefold cross-validation and the average receiver operating curve was accessed. The AUC of the cross-validation study (AUCCV) was calculated together with its 95% confidence interval. RESULTS: The AUCCV (and 95% confidence interval) for models T, CS, and CST was 0.85 (0.71-0.96), 0.88 (0.77-0.96), and 0.88 (0.77-0.97), respectively. After separating the data into two groups with or without contrast enhancement, the AUC (without cross-validation) of the model T was 0.86 both for images with and without contrast enhancement, suggesting that contrast enhancement did not impact the utility of texture analysis. CONCLUSIONS: The models with semantic and texture features provided cross-validated AUCs of 0.85-0.88 for classification of benign versus cancerous nodules, showing potential in aiding the management of patients. KEY POINTS: • Pretest probability of cancer can aid and direct the physician in the diagnosis and management of pulmonary nodules in a cost-effective way. • Semantic features (qualitative features reported by radiologists to characterize lung lesions) and radiomic (e.g., texture) features can be extracted from CT images. • Input of these variables into a model can generate a pretest likelihood of cancer to aid clinical decision and management of pulmonary nodules.

Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy.

BACKGROUND: Robust approaches to quantify tumor heterogeneity are needed to provide early decision support for precise individualized therapy. PURPOSE: To conduct a technical exploration of longitudinal changes in tumor heterogeneity patterns on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI) and FDG positron emission tomography / computed tomography (PET/CT), and their association to radiation therapy (RT) response in cervical cancer. STUDY TYPE: Prospective observational study with longitudinal MRI and PET/CT pre-RT, early-RT (2 weeks), and mid-RT (5 weeks). POPULATION: Twenty-one FIGO IB2 -IVA cervical cancer patients receiving definitive external beam RT and brachytherapy. FIELD STRENGTH/SEQUENCE: 1.5T, precontrast axial T1 -weighted, axial and sagittal T2 -weighted, sagittal DWI (multi-b values), sagittal DCE MRI (<10 sec temporal resolution), postcontrast axial T1 -weighted. ASSESSMENT: Response assessment 1 month after completion of treatment by a board-certified radiation oncologist from manually delineated tumor volume changes. STATISTICAL TESTS: Intensity histogram (IH) quantiles (DCE SI10% and DWI ADC10% , FDG-PET SUVmax ) and distribution moments (mean, variance, skewness, kurtosis) were extracted. Differences in IH features between timepoints and modalities were evaluated by Skillings-Mack tests with Holm's correction. Area under receiver-operating characteristic curve (AUC) and Mann-Whitney testing was performed to discriminate treatment response using IH features. RESULTS: Tumor IH means and quantiles varied significantly during RT (SUVmean : ↓28-47%, SUVmax : ↓30-59%, SImean : ↑8-30%, SI10% : ↑8-19%, ADCmean : ↑16%, P < 0.02 for each). Among IH heterogeneity features, FDG-PET SUVCoV (↓16-30%, P = 0.011) and DW-MRI ADCskewness decreased (P = 0.001). FDG-PET SUVCoV was higher than DCE-MRI SICoV and DW-MRI ADCCoV at baseline (P < 0.001) and 2 weeks (P = 0.010). FDG-PET SUVkurtosis was lower than DCE-MRI SIkurtosis and DW-MRI ADCkurtosis at baseline (P = 0.001). Some IH features appeared to associate with favorable tumor response, including large early RT changes in DW-MRI ADCskewness (AUC = 0.86). DATA CONCLUSION: Preliminary findings show tumor heterogeneity was variable between patients, modalities, and timepoints. Radiomic assessment of changing tumor heterogeneity has the potential to personalize treatment and power outcome prediction. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1388-1396.

Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

PURPOSE: To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters. MATERIALS AND METHODS: Radiation treatment planning CT scans were coregistered with pretreatment [99mTc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ≥ 2 (CTCAE v4 grading system). Anatomic lung dose-volume parameters were collected from the treatment planning scans. Perfusion dose-volume parameters were calculated from pretreatment SPECT/CT scans. Equivalent doses in 2 Gy per fraction were calculated in the lung to account for differences in treatment regimens and spatial variations in lung dose (EQD2lung). RESULTS: Anatomic lung dosimetric parameters (MLD) and functional lung dosimetric parameters (pMLD70%) were identified as candidate predictors of grade ≥ 2 radiation pneumonitis (AUC > 0.93, p < 0.01). Pairing of an anatomic and functional dosimetric parameter (e. g., MLD and pMLD70%) may further improve prediction accuracy. Not all individuals with high anatomic lung dose (MLD > 13.6 GyEQD2lung, 19.3 Gy for patients receiving 60 Gy in 30 fractions) developed radiation pneumonitis, but all individuals who also had high mean dose to perfused lung (pMLD70% > 13.3 GyEQD2) developed radiation pneumonitis. CONCLUSIONS: The preliminary application of this framework revealed differences between anatomic and perfused lung dosimetry in this limited patient cohort. The addition of perfused lung parameters may help risk stratify patients for radiation pneumonitis, especially in treatment plans with high anatomic mean lung dose. Further investigations are warranted.

Characterization of PET/CT images using texture analysis: the past, the present any future?

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties.

Extremely low-dose CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This work explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air+background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the RMSE by roughly 2 times compared to a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared to a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

Radiomics: Images Are More than Pictures, They Are Data.

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.

Morphology supporting function: attenuation correction for SPECT/CT, PET/CT, and PET/MR imaging.

Both SPECT, and in particular PET, are unique in medical imaging for their high sensitivity and direct link to a physical quantity, i.e. radiotracer concentration. This gives PET and SPECT imaging unique capabilities for accurately monitoring disease activity for the purposes of clinical management or therapy development. However, to achieve a direct quantitative connection between the underlying radiotracer concentration and the reconstructed image values several confounding physical effects have to be estimated, notably photon attenuation and scatter. With the advent of dual-modality SPECT/CT, PET/CT, and PET/MR scanners, the complementary CT or MR image data can enable these corrections, although there are unique challenges for each combination. This review covers the basic physics underlying photon attenuation and scatter and summarizes technical considerations for multimodal imaging with regard to PET and SPECT quantification and methods to address the challenges for each multimodal combination.

An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms.

Drawing regions of interest (ROIs) in positron emission tomography/computed tomography (PET/CT) scans of the National Electrical Manufacturers Association (NEMA) NU-2 Image Quality (IQ) phantom is a time-consuming process that allows for interuser variability in the measurements. In order to reduce operator effort and allow batch processing of IQ phantom images, we propose a fast, robust, automated algorithm for performing IQ phantom sphere localization and analysis. The algorithm is easily altered to accommodate different configurations of the IQ phantom. The proposed algorithm uses information from both the PET and CT image volumes in order to overcome the challenges of detecting the smallest spheres in the PET volume. This algorithm has been released as an open-source plug-in to the Osirix medical image viewing software package. We test the algorithm under various noise conditions, positions within the scanner, air bubbles in the phantom spheres, and scanner misalignment conditions. The proposed algorithm shows run-times between 3 and 4 min and has proven to be robust under all tested conditions, with expected sphere localization deviations of less than 0.2 mm and variations of PET ROI mean and maximum values on the order of 0.5% and 2%, respectively, over multiple PET acquisitions. We conclude that the proposed algorithm is stable when challenged with a variety of physical and imaging anomalies, and that the algorithm can be a valuable tool for those who use the NEMA NU-2 IQ phantom for PET/CT scanner acceptance testing and QA/QC.

A Digital Reference Object to Analyze Calculation Accuracy of PET Standardized Uptake Value.

PURPOSE: To determine the extent of variations in computing standardized uptake value (SUV) by body weight (SUV(BW)) among different software packages and to propose a Digital Imaging and Communications in Medicine (DICOM) reference test object to ensure the standardization of SUV computation between medical image viewing workstations. MATERIALS AND METHODS: Research ethics board approval was not necessary because this study only evaluated images of a phantom. A synthetic set of positron emission tomographic (PET)/computed tomographic (CT) image data, called a digital reference object (DRO), with known SUV was created. The DRO was sent to 16 sites and evaluated on 21 different PET/CT display software packages. Users were asked to draw various regions of interest (ROIs) on specific features and report the maximum, minimum, mean, and standard deviation of the SUVs for each ROI. Numerical tolerances were defined for each metric, and the fraction of reported values within the tolerance was recorded, as was the mean, standard deviation, and range of the metrics. RESULTS: The errors in reported maximum SUV ranged from -37.8% to 0% for an isolated voxel with 4.11:1 target-to-background activity level, and errors in the reported mean SUV ranged from -1.6% to 100% for a region with controlled noise. There was also a range of errors in the less commonly used metrics of minimum SUV and standard deviation SUV. CONCLUSION: The variability of computed SUV(BW) between different software packages is substantial enough to warrant the introduction of a reference standard for medical image viewing workstations.

AAPM/SNMMI Joint Task Force: report on the current state of nuclear medicine physics training.

The American Association of Physicists in Medicine (AAPM) and the Society of Nuclear Medicine and Molecular Imaging (SNMMI) recognized the need for a review of the current state of nuclear  medicine physics training and the need to explore pathways for improving nuclear medicine physics training opportunities. For these reasons, the two organizations formed a joint AAPM/SNMMI Ad Hoc Task Force on Nuclear Medicine Physics  Training. The mission of this task force was to assemble a representative group of stakeholders to:• Estimate the demand for board-certified nuclear medicine physicists in the next 5-10 years,• Identify the critical issues related to supplying an adequate number of physicists who have received the appropriate level of training in nuclear medicine physics, and• Identify approaches that may be considered to facilitate the training of nuclear medicine physicists.As a result, a task force was appointed and chaired by an active member of both organizations that included representation from the AAPM, SNMMI, the American Board of Radiology (ABR), the American Board of Science in Nuclear Medicine (ABSNM), and the Commission for the Accreditation of Medical Physics Educational Programs (CAMPEP). The Task Force first met at the AAPM Annual Meeting in Charlotte in July 2012 and has met regularly face-to-face, online, and by conference calls. This manuscript reports the findings of the Task Force, as well as recommendations to achieve the stated mission.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials.

BACKGROUND: Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients with bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.In this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified as the maximum tumor voxel normalized by dose and body weight (SUVmax) and the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals of SUVmax and SULpeak were used to determine limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment. RESULTS: The mean relative difference of SUVmax in 38 bone tumors of the first cohort was 4.3%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and -16.3%, respectively. The 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria changed the status of 3 patients compared to standard the standard Positron Emission Tomography Response Criteria in Solid Tumors of ±30% SULpeak. CONCLUSIONS: In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG uptake, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions from these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials.

BACKGROUND: Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases. METHODS: For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment. RESULTS: The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and - 16.3% for SUVmax, and 21.2% and - 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak. CONCLUSION: In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group.

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

Evaluation of strategies towards harmonization of FDG PET/CT studies in multicentre trials: comparison of scanner validation phantoms and data analysis procedures.

PURPOSE: PET quantification based on standardized uptake values (SUV) is hampered by several factors, in particular by variability in PET acquisition settings and data analysis methods. Quantitative PET/CT studies acquired during a multicentre trial require harmonization of imaging procedures to maximize study power. The aims of this study were to determine which phantoms are most suitable for detecting differences in image quality and quantification, and which methods for defining volumes of interest (VOI) are least sensitive to these differences. METHODS: The most common accreditation phantoms used in oncology FDG PET/CT trials were scanned on the same scanner. These phantoms were those used by the Society of Nuclear Medicine Clinical Trials Network (SNM-CTN), the European Association of Nuclear Medicine/National Electrical Manufacturers Association (EANM/NEMA) and the American College of Radiology (ACR). In addition, tumour SUVs were derived from ten oncology whole-body examinations performed on the same PET/CT system. Both phantom and clinical data were reconstructed using different numbers of iterations, subsets and time-of-flight kernel widths. Subsequently, different VOI methods (VOI(A50%), VOI(max), VOI(3Dpeak), VOI(2Dpeak)) were applied to assess the impact of changes in image reconstruction settings on SUV and recovery coefficients (RC). RESULTS: All phantoms demonstrated sensitivity for detecting changes in SUV and RC measures in response to changes in image reconstruction settings and VOI analysis methods. The SNM-CTN and EANM/NEMA phantoms showed almost equal sensitivity in detecting RC differences with changes in image characteristics. Phantom and clinical data demonstrated that the VOI analysis methods VOI(A50%) and VOI(max) gave SUV and RC values with large variability in relation to image characteristics, whereas VOI(3Dpeak) and VOI(2Dpeak) were less sensitive to these differences. CONCLUSION: All three phantoms may be used to harmonize parameters for data acquisition, processing and analysis. However, the SNM-CTN and EANM/NEMA phantoms are the most sensitive to parameter changes and are suitable for harmonizing SUV quantification based on 3D VOIs, such as VOI(A50%) and VOI(3Dpeak), and VOImax. Variability in SUV quantification after harmonization could be further minimized using VOI(3Dpeak) analysis, which was least sensitive to residual variability in image quality and quantification.

Model-based iterative reconstruction versus adaptive statistical iterative reconstruction and filtered back projection in liver 64-MDCT: focal lesion detection, lesion conspicuity, and image noise.

OBJECTIVE: The purpose of this study is to compare three CT image reconstruction algorithms for liver lesion detection and appearance, subjective lesion conspicuity, and measured noise. MATERIALS AND METHODS: Thirty-six patients with known liver lesions were scanned with a routine clinical three-phase CT protocol using a weight-based noise index of 30 or 36. Image data from each phase were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Randomized images were presented to two independent blinded reviewers to detect and categorize the appearance of lesions and to score lesion conspicuity. Lesion size, lesion density (in Hounsfield units), adjacent liver density (in Hounsfield units), and image noise were measured. Two different unblinded truth readers established the number, appearance, and location of lesions. RESULTS: Fifty-one focal lesions were detected by truth readers. For blinded reviewers compared with truth readers, there was no difference for lesion detection among the reconstruction algorithms. Lesion appearance was statistically the same among the three reconstructions. Although one reviewer scored lesions as being more conspicuous with MBIR, the other scored them the same. There was significantly less background noise in air with MBIR (mean [± SD], 2.1 ± 1.4 HU) than with ASIR (8.9 ± 1.9 HU; p < 0.001) or FBP (10.6 ± 2.6 HU; p < 0.001). Mean lesion contrast-to-noise ratio was statistically significantly higher for MBIR (34.4 ± 29.1) than for ASIR (6.5 ± 4.9; p < 0.001) or FBP (6.3 ± 6.0; p < 0.001). CONCLUSION: In routine-dose clinical CT of the liver, MBIR resulted in comparable lesion detection, lesion characterization, and subjective lesion conspicuity, but significantly lower background noise and higher contrast-to-noise ratio compared with ASIR or FBP. This finding suggests that further investigation of the use of MBIR to enable dose reduction in liver CT is warranted.

Multicenter trials using ¹8F-fluorodeoxyglucose (FDG) PET to predict chemotherapy response: effects of differential measurement error and bias on power calculations for unselected and enrichment designs.

BACKGROUND: Clinical validation of a predictive biomarker is especially difficult when the biomarker cannot be assessed retrospectively. A cost-effective, prospective multicenter replication study with rapid accrual is warranted prior to further validation studies such as a marker-based strategy for treatment selection. However, it is often unknown how measurement error and bias in a multicenter trial will differ from that in single-institution studies. PURPOSE: Power calculations using simulated data may inform the efficient design of a multicenter study to replicate single-institution findings. This case study used serial standardized uptake value (SUV) measures from (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) to predict early response to breast cancer neoadjuvant chemotherapy. We examined the impact of accelerating accrual through increased inclusion of secondary sites with greater levels of measurement error and bias. We also examined whether enrichment designs based on breast cancer initial uptake could increase the study power for a fixed budget (200 total scans). METHODS: Reference FDG PET SUV data were selected with replacement from a single-institution trial; pathologic complete response (pCR) data were simulated using a logistic regression model predicting response by mid-therapy percent change in SUV. The impact of increased error for SUV measurements in multicenter trials was simulated by sampling from error and bias distributions: 20%-40% measurement error, 0%-40% bias, and fixed error/bias values. The proportion of patients recruited from secondary sites (with higher additional error/bias compared to primary sites) varied from 25% to 75%. RESULTS: Reference power (from source data with no added error) was 0.92 for N = 100 to detect an association between percentage change in SUV and response. With moderate (20%) simulated measurement error for 3/4, 1/2, and 1/4 of measurements and 40% for the remainder, power was 0.70, 0.61, and 0.53, respectively. Reduction of study power was similar for other manifestations of measurement error (bias as a percentage of true value, absolute error, and absolute bias). Enrichment designs, which recruit additional patients by not conducting a second scan in patients with unsuitable pre-therapy uptake (low baseline SUV), did not lead to greater power for studies constrained to the same total cost. LIMITATIONS: Simulation parameters could be incorrect, or not generalizable. Under a different logistic regression model relating mid-therapy percent change in SUV to pCR (with no relationship for patients with low baseline SUV, rather than the modest point estimate from reference data), the enrichment design did have somewhat greater power than the unselected design. CONCLUSION: Even moderate additional measurement error substantially reduced study power under both unselected and enrichment designs.

Effects of Detector Thickness on Geometric Sensitivity and Event Positioning Errors in the Rectangular PET/X Scanner.

We used simulations to investigate the relationship between sensitivity and spatial resolution as a function of crystal thickness in a rectangular PET scanner intended for quantitative assessment of breast cancers. The system had two 20 × 15-cm2 and two 10 × 15-cm2 flat detectors forming a box, with the larger detectors separated by 4 or 8 cm. Depth-of-interaction (DOI) resolution was modeled as a function of crystal thickness based on prior measurements. Spatial resolution was evaluated independent of image reconstruction by deriving and validating a surrogate metric from list-mode data (dFWHM). When increasing crystal thickness from 5 to 40 mm, and without using DOI information, the dFWHM for a centered point source increased from 0.72 to 1.6 mm. Including DOI information improved dFWHM by 12% and 27% for 5- and 40-mm-thick crystals, respectively. For a point source in the corner of the FOV, use of DOI information improved dFWHM by 20% (5-mm crystal) and 44% (40-mm crystal). Sensitivity was 7.7% for 10-mm-thick crystals (8-cm object). Increasing crystal thickness on the smaller side detectors from 10 to 20 mm (keeping 10-mm crystals on the larger detectors) boosted sensitivity by 24% (relative) and degraded dFWHM by only ~3%/8% with/without DOI information. The benefits of measuring DOI must be evaluated in terms of the intended clinical task of assessing tracer uptake in small lesions. Increasing crystal thickness on the smaller side detectors provides substantial sensitivity increase with minimal accompanying loss in resolution.