Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images.

Quantitative imaging biomarkers (QIBs) provide medical image-derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II.

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study.

Image-Based 2D Re-Projection for Attenuation Substitution in PET Neuroimaging.

PURPOSE: In dual modality positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) methods are continually improving. Although a new AC can sometimes be generated from existing MR data, its application requires a new reconstruction. We evaluate an approximate 2D projection method that allows offline image-based reprocessing. PROCEDURE: 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) brain scans were acquired (Siemens HR+) for six subjects. Attenuation data were obtained using the scanner's transmission source (SAC). Additional scanning was performed on a Siemens mMR including production of a Dixon-based MR AC (MRAC). The MRAC was imported to the HR+ and the PET data were reconstructed twice: once using native SAC (ground truth); once using the imported MRAC (imperfect AC). The re-projection method was implemented as follows. The MRAC PET was forward projected to approximately reproduce attenuation-corrected sinograms. The SAC and MRAC images were forward projected and converted to attenuation-correction factors (ACFs). The MRAC ACFs were removed from the MRAC PET sinograms by division; the SAC ACFs were applied by multiplication. The regenerated sinograms were reconstructed by filtered back projection to produce images (SUBAC PET) in which SAC has been substituted for MRAC. Ideally SUBAC PET should match SAC PET. Via coregistered T1 images, FreeSurfer (FS; MGH, Boston) was used to define a set of cortical gray matter regions of interest. Regional activity concentrations were extracted for SAC PET, MRAC PET, and SUBAC PET. RESULTS: SUBAC PET showed substantially smaller root mean square error than MRAC PET with averaged values of 1.5 % versus 8.1 %. CONCLUSIONS: Re-projection is a viable image-based method for the application of an alternate attenuation correction in neuroimaging.

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data.

PURPOSE: Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making. METHODS: To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis. RESULTS: On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively. CONCLUSION: Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.

[18F]ML-10 PET: Initial Experience in Glioblastoma Multiforme Therapy Response Assessment.

The ability to assess tumor apoptotic response to therapy could provide a direct and prompt measure of therapeutic efficacy. 18F-labeled 2-(5-fluoro-pentyl)-2-methyl-malonic acid ([18F]ML-10) is proposed as a positron emission tomography (PET) apoptosis imaging radiotracer. This manuscript presents initial experience using [18F]ML-10 PET to predict therapeutic response in 4 patients with human glioblastoma multiforme. Each patient underwent [18F]ML-10 PET and contrast-enhanced magnetic resonance imaging (MRI) before (baseline) and at ∼2-3 weeks after therapy (early-therapy assessment). All PET and MRI data were acquired using a Siemens BioGraph mMR integrated PET/MRI scanner. PET acquisitions commenced 120 minutes after injection with 10 mCi of [18F]ML-10. Changes in [18F]ML-10 standard uptake values were assessed in conjunction with MRI changes. Time-to-progression was used as the outcome measure. One patient, ML-10 #4, underwent additional sodium-23 (23Na) MRI at baseline and early-therapy assessment. Siemens 3 T Magnetom Tim Trio scanner with a dual-tuned (1H-23Na) head coil was used for 23Na-MRI, acquiring two three-dimensional single-quantum sodium images at two echo times (TE). Volume-fraction-weighted bound sodium concentration was quantified through pixel-by-pixel subtraction of the two single-quantum sodium images. In the cases presented, [18F]ML-10 uptake changes were not clearly related to time-to-progression. We suggest that this may be because the tumors are undergoing varying rates of cell death and growth. Acquisition of complementary measures of tumor cell proliferation or viability may aid in the interpretation of PET apoptosis imaging.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge.

Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kepvs. 0.74 for Ktrans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than Ktrans.

Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods.

Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12-15 months for glioblastomas and 2-5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies, and importantly, for facilitating patient management, sparing patients from weeks or months of toxicity and ineffective treatment. This review will present an overview of epidemiology, molecular pathogenesis and current advances in diagnoses, and management of malignant gliomas.

Assessment of early therapy response with 18F-FLT PET in glioblastoma multiforme.

Early therapy response assessment in glioblastoma multiforme remains a challenge. Evaluation by MRI relies on changes in tumor contrast enhancement or size, which are usually not visible at early therapy response assessment times. In addition, MRI may not be reliable for early therapy response assessment if only molecular changes have occurred. PET with F-FLT, a tracer associated with cellular proliferation, has been proposed as a potential method of early therapy response assessment and is an area of active research. We present a case where early response assessment with F-FLT PET was associated with a favorable 1-year follow-up outcome.

First use of (18)F-labeled ML-10 PET to assess apoptosis change in a newly diagnosed glioblastoma multiforme patient before and early after therapy.

OBJECTIVES: The authors present the first use of the novel positron emission tomography (PET) apoptosis tracer (18)F-labeled 2-(5-fluoro-pentyl)-2-methyl-malonic acid ((18)F-ML-10) for early-therapy response assessment of a newly diagnosed glioblastoma multiforme (GBM) patient. CASE REPORT: A 71-year-old male with a newly diagnosed GBM received (18)F-ML-10 PET scans prior to therapy initiation (baseline) and after completing 3 weeks of whole-brain radiation therapy with concomitant temozolomide chemotherapy (early-therapy assessment, ETA). The baseline (18)F-ML-10 PET scan showed increased tracer uptake at the site of the GBM, with highest activity toward the central portion of the tumor. At the ETA time point, a new distribution of tracer uptake was observed compared to baseline. Normalized pixel-by-pixel subtraction of baseline from ETA was used to quantify change in tracer distribution between (18)F-ML-10 PET imaging time points. Results of this analysis showed reduction in (18)F-ML-10 uptake at the site of greatest baseline uptake, but increased uptake around the periphery of the tumor at the early-therapy time point. CONCLUSION: The changing patterns of (18)F-ML-10 uptake between baseline and ETA are suggestive for therapy-induced tumor cellular apoptosis.

Challenges and Approaches to Quantitative Therapy Response Assessment in Glioblastoma Multiforme Using the Novel Apoptosis Positron Emission Tomography Tracer F-18 ML-10.

Evaluation of cancer-therapy efficacy at early time points is necessary for realizing the goal of delivering maximally effective treatment. Molecular imaging with carefully selected tracers and methodologies can provide the means for realizing this ability. Many therapies are aimed at inducing apoptosis in malignant tissue; thus, the ability to quantify apoptosis in vivo may be a fruitful approach. Apoptosis rate changes occur on a fast time scale, potentially allowing correspondingly rapid decisions regarding therapy value. However, quantification of tissue status based on apoptosis imaging is complicated by this time scale and by the spatial heterogeneity of the process. Using the positron emission tomography (PET) tracer 2-(5-fluoro-pentyl)-2-methyl-malonic acid (F-18 ML-10), we present methods of voxelwise analysis yielding quantitative measures of apoptosis changes, parametric apoptosis change images, and graphical representation of apoptotic features. A method of deformable registration to account for anatomic changes between scan time points is also demonstrated. Overall apoptotic rates deduced from imaging depend on tumor density and the specific rate of apoptosis, a situation resulting in an ambiguity in the source of observed image-based changes. The ambiguity may be resolved through multimodality imaging. An example of intracellular sodium magnetic resonance imaging coupled with F-18 ML-10 PET is provided.

Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling.

PURPOSE: To evaluate the ability of various software (SW) tools used for quantitative image analysis to properly account for source-specific image scaling employed by magnetic resonance imaging manufacturers. METHODS: A series of gadoteridol-doped distilled water solutions (0%, 0.5%, 1%, and 2% volume concentrations) was prepared for manual substitution into one (of three) phantom compartments to create "variable signal," whereas the other two compartments (containing mineral oil and 0.25% gadoteriol) were held unchanged. Pseudodynamic images were acquired over multiple series using four scanners such that the histogram of pixel intensities varied enough to provoke variable image scaling from series to series. Additional diffusion-weighted images were acquired of an ice-water phantom to generate scanner-specific apparent diffusion coefficient (ADC) maps. The resulting pseudodynamic images and ADC maps were analyzed by eight centers of the Quantitative Imaging Network using 16 different SW tools to measure compartment-specific region-of-interest intensity. RESULTS: Images generated by one of the scanners appeared to have additional intensity scaling that was not accounted for by the majority of tested quantitative image analysis SW tools. Incorrect image scaling leads to intensity measurement bias near 100%, compared to nonscaled images. CONCLUSION: Corrective actions for image scaling are suggested for manufacturers and quantitative imaging community.

Variations of dynamic contrast-enhanced magnetic resonance imaging in evaluation of breast cancer therapy response: a multicenter data analysis challenge.

Pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) time-course data allows estimation of quantitative parameters such as K (trans) (rate constant for plasma/interstitium contrast agent transfer), v e (extravascular extracellular volume fraction), and v p (plasma volume fraction). A plethora of factors in DCE-MRI data acquisition and analysis can affect accuracy and precision of these parameters and, consequently, the utility of quantitative DCE-MRI for assessing therapy response. In this multicenter data analysis challenge, DCE-MRI data acquired at one center from 10 patients with breast cancer before and after the first cycle of neoadjuvant chemotherapy were shared and processed with 12 software tools based on the Tofts model (TM), extended TM, and Shutter-Speed model. Inputs of tumor region of interest definition, pre-contrast T1, and arterial input function were controlled to focus on the variations in parameter value and response prediction capability caused by differences in models and associated algorithms. Considerable parameter variations were observed with the within-subject coefficient of variation (wCV) values for K (trans) and v p being as high as 0.59 and 0.82, respectively. Parameter agreement improved when only algorithms based on the same model were compared, e.g., the K (trans) intraclass correlation coefficient increased to as high as 0.84. Agreement in parameter percentage change was much better than that in absolute parameter value, e.g., the pairwise concordance correlation coefficient improved from 0.047 (for K (trans)) to 0.92 (for K (trans) percentage change) in comparing two TM algorithms. Nearly all algorithms provided good to excellent (univariate logistic regression c-statistic value ranging from 0.8 to 1.0) early prediction of therapy response using the metrics of mean tumor K (trans) and k ep (=K (trans)/v e, intravasation rate constant) after the first therapy cycle and the corresponding percentage changes. The results suggest that the interalgorithm parameter variations are largely systematic, which are not likely to significantly affect the utility of DCE-MRI for assessment of therapy response.

Distinguishing pseudoprogression from progression in high-grade gliomas: a brief review of current clinical practice and demonstration of the potential value of 18F-FDG PET.

We report a case in which 18F-FDG PET was able to discriminate pseudoprogression from progression observed on contrast-enhanced (CE) MRI (CE-MRI). A 56-year-old male patient with anaplastic oligodendroglioma demonstrated markedly increased tumor enhancement on CE-MRI 1 month after completing radiation therapy (RT), suggesting radiological progression. However, the patient was clinically improved and therefore received an early-therapy response assessment PET to assess for pseudoprogression. PET showed low tumor uptake indicating stable disease. Follow-up CE-MRI at 3 and 4 months post-RT confirmed stable disease. This case emphasizes the value of 18F-FDG PET when pseudoprogression is clinically suspected.

Improved Benefit of SPECT/CT Compared to SPECT Alone for the Accurate Localization of Endocrine and Neuroendocrine Tumors.

OBJECTIVE: To assess the clinical utility of SPECT/ CT in subjects with endocrine and neuroendocrine tumors compared to SPECT alone. MATERIAL AND METHODS: 48 subjects (31 women;17 men; mean age 54±11) with clinical suspicion or diagnosis of endocrine and neuroendocrine tumor had 50 SPECT/CT scans (32 Tc-99m MIBI, 5 post treatment I-131, 8 In-111 Pentetreotide, and 5 I-123 MIBG). SPECT alone findings were compared to SPECT/CT and to pathology or radiological follow up. RESULTS: From the 32 Tc-99m MIBI scans, SPECT accurately localized the lesion in 22 positive subjects while SPECT/CT did in 31 subjects. Parathyroid lesions not seen on SPECT alone were smaller than 10 mm. In five post treatment I-131 scans, SPECT alone neither characterized, nor localized any lesions accurately. SPECT/CT revealed 3 benign etiologies, a metastatic lymph node, and one equivocal lesion. In 8 In-111 Pentetreotide scans, SPECT alone could not localize primary or metastatic lesions in 6 subjects all of which were localized with SPECT/CT. In five I-123 MIBG scans, SPECT alone could not detect a 1.1 cm adrenal lesion or correctly characterize normal physiologic adrenal uptake in consecutive scans of the same patient with prior history of adrenelectomy, all of which were correctly localized and characterized with SPECT/CT. CONCLUSION: SPECT/CT is superior to SPECT alone in the assessment of endocrine and neuroendocrine tumors. It is better in lesion localization and lesion characterization leading to a decrease in the number of equivocal findings. SPECT/CT should be included in the clinical work up of all patients with diagnosis or suspicion of endocrine and neuroendocrine tumors. CONFLICT OF INTEREST: None declared.

Combined imaging biomarkers for therapy evaluation in glioblastoma multiforme: correlating sodium MRI and F-18 FLT PET on a voxel-wise basis.

We evaluate novel magnetic resonance imaging (MRI) and positron emission tomography (PET) quantitative imaging biomarkers and associated multimodality, serial-time-point analysis methodologies, with the ultimate aim of providing clinically feasible, predictive measures for early assessment of response to cancer therapy. A focus of this work is method development and an investigation of the relationship between the information content of the two modalities. Imaging studies were conducted on subjects who were enrolled in glioblastoma multiforme (GBM) therapeutic clinical trials. Data were acquired, analyzed and displayed using methods that could be adapted for clinical use. Subjects underwent dynamic [(18)F]fluorothymidine (F-18 FLT) PET, sodium ((23)Na) MRI and 3-T structural MRI scans at baseline (before initiation of therapy), at an early time point after beginning therapy and at a late follow-up time point after therapy. Sodium MRI and F-18 FLT PET images were registered to the structural MRI. F-18 FLT PET tracer distribution volumes and sodium MRI concentrations were calculated on a voxel-wise basis to address the heterogeneity of tumor physiology. Changes in, and differences between, these quantities as a function of scan timing were tracked. While both modalities independently show a change in tissue status as a function of scan time point, results illustrate that the two modalities may provide complementary information regarding tumor progression and response. Additionally, tumor status changes were found to vary in different regions of tumor. The degree to which these methods are useful for GBM therapy response assessment and particularly for differentiating true progression from pseudoprogression requires additional patient data and correlation of these imaging biomarker changes with clinical outcome.