Computed Tomography Assessment of Response to Therapy: Tumor Volume Change Measurement,Truth Data,and Error

RATIONALE AND OBJECTIVES: This article describes issues and methods that are specific to the measurement of change in tumor volume as measured from computed tomographic (CT) images and how these would relate to the establishment of CT tumor volumetrics as a biomarker of patient response to therapy. The primary focus is on the measurement of lung tumors, but the approach should be generalizable to other anatomic regions. MATERIALS AND METHODS: The first issues addressed are the various sources of bias and variance in the measurement of tumor volumes, which are discussed in the context of measurement variation and its impact on the early detection of response to therapy. RESULTS AND RESOURCES: Research that seeks to identify the magnitude of some of these sources of error is ongoing, and several of these efforts are described herein. In addition, several resources for these investigations are being made available through the National Institutes of Health-funded Reference Image Database to Evaluate Response to therapy in cancer project, and these are described as well. Other measures derived from CT image data that might be predictive of patient response are described briefly, as well as the additional issues that each of these metrics may encounter in real-life applications. CONCLUSIONS: The article concludes with a brief discussion of moving from the assessment of measurement variation to the steps necessary to establish the efficacy of a metric as a biomarker for response.     

PET/CT Assessment of Response to Therapy: Tumor Change Measurement,Truth Data,and Error

We describe methods and issues that are relevant to the measurement of change in tumor uptake of ¹⁸F-fluorodeoxyglucose (FDG) or other radiotracers, as measured from positron emission tomography/computed tomography (PET/CT) images, and how this would relate to the establishment of PET/CT tumor imaging as a biomarker of patient response to therapy. The primary focus is on the uptake of FDG by lung tumors, but the approach can be applied to diseases other than lung cancer and to tracers other than FDG. The first issue addressed is the sources of bias and variance in the measurement of tumor uptake of FDG, and where there are still gaps in our knowledge. These are discussed in the context of measurement variation and how these would relate to the early detection of response to therapy. Some of the research efforts currently underway to identify the magnitude of some of these sources of error are described. In addition, we describe resources for these investigations that are being made available through the Reference Image Database for the Evaluation of Response project. Measures derived from PET image data that might be predictive of patient response as well as the additional issues that each of these metrics may encounter are described briefly. The relationship between individual patient response to therapy and utility for multicenter trials is discussed. We conclude with a discussion of moving from assessing measurement variation to the steps necessary to establish the efficacy of PET/CT imaging as a biomarker for response.     

Magnetic Resonance Assessment of Response to Therapy: Tumor Change Measurement,Truth Data and Error Sources

This article describes methods and issues that are specific to the assessment of change in tumor characteristics as measured using quantitative magnetic resonance (MR) techniques and how this relates to the establishment of quantitative MR imaging (MRI) biomarkers of patient response to therapy. The initial focus is on the various sources of bias and variance in the measurement of microvascular parameters and diffusion parameters as such parameters are being used relatively commonly as secondary or exploratory end points in current phase 1/2 clinical trails of conventional and targeted therapies. Several ongoing initiatives that seek to identify the magnitude of some of the sources of measurement variations are then discussed. Finally, resources being made available through the National Cancer Institute Reference Image Database to Evaluate Response (RIDER) project that might be of use in investigations of quantitative MRI biomarker change analysis are described. These resources include 1) data from phantom-based assessment of system response, including short-term (1 hour) and moderate-term (1 week) contrast response and relaxation time measurement, 2) data obtained from repeated dynamic contrast agent-enhanced MRI studies in intracranial tumors, and 3) data obtained from repeated diffusion MRI studies in both breast and brain. A concluding section briefly discusses issues that must be addressed to allow the transition of MR-based imaging biomarker measures from their current role as secondary/exploratory end points in clinical trials to primary/surrogate markers of response and, ultimately, in clinical application.     

<Emphasis Type="Italic">In vivo</Emphasis> fluorescence imaging to assess early therapeutic response to tumor progression in a xenograft cancer model

Bioimaging technology plays an important role in assessment of therapeutic response in cancer therapy. Here, we report a non-invasive monitoring system for measuring tumor growth by in vivo fluorescence imaging. Target cells for xenograft tumor induction were manipulated by cell-surface fluorescence labelling. Fluorescence was clearly detected in vitro and in vivo without affecting cytotoxicity. Anti-tumor efficacy was evaluated by directly measuring the fluorescence signal of a progressive tumor in a xenograft model. This non-invasive in vivo monitoring system can be used to assess the early response to antitumor therapeutics and may be a valuable tool to replace or complement traditional caliper-based methods for preclinical studies.     

Place de l’imagerie dans l’évaluation de l’efficacité des traitements dans le cancer du sein

This paper describes, from the current literature, the role of various imaging methods to assess the response to therapy in breast cancer. Two different clinical situations are considered: neoadjuvant chemotherapy of locally advanced breast cancer and the metastastic breast cancer. Significant clinical data are available for three criteria: the volume of the tumour, the uptake of fluorodeoxyglucose using PET and the perfusion of the tumor evaluated either by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) or by PET using ¹⁵O water. ¹⁸F FDG PET allows prediction of the response after one or two cycles of neoadjuvant chemotherapy. New approaches will offer opportunities to refine the role of imaging in monitoring the response to chemotherapy. PET using thymidine as biomarker is promising in assessing the tissular proliferation. Estrogen analogs could be used to predict hormonally responsive breast cancer. Many other approaches, although less developed, might offer new insights in the response to therapy of breast cancer like magnetic resonance spectroscopy or optical imaging of hemoglobin oxygenation. Imaging also offers potential of monitoring the down-regulation of specialized receptors of the cell membrane in response to treatment: the most studied receptor in preclinical model has been the human epidermal growth factor receptor type 2 (HER2). Integrin, a family of cell adhesion receptor, is also an important target for imaging. Apoptosis, multidrug resistance and hypoxia can also be studied using appropriate biomarkers. To allow reliable multicenter trials of new drugs, these different imaging approaches still require an improved standardization of image acquisition and processing.     

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.     

Measurement of tumor volumes improves RECIST-based response assessments in advanced lung cancer

OBJECTIVE: This study was designed to characterize the reproducibility of measurement for tumor volumes and their longest tumor diameters (LDs) and estimate the potential impact of using changes in tumor volumes instead of LDs as the basis for response assessments. METHODS: We studied patients with advanced lung cancer who have been observed longitudinally with x-ray computed tomography in a multinational trial. A total of 71 time points from 10 patients with 13 morphologically complex target lesions were analyzed. A total of 6461 volume measurements and their corresponding LDs were made by seven independent teams using their own work flows and image analysis tools. Interteam agreement and overall interrater concurrence were characterized. RESULTS: Interteam agreement between volume measurements was better than between LD measurements (ı = 0.945 vs 0.734, P = .005). The variability in determining the nadir was lower for volumes than for LDs (P = .005). Use of standard thresholds for the RECIST-based method and use of experimentally determined cutoffs for categorizing responses showed that volume measurements had a significantly greater sensitivity for detecting partial responses and disease progression. Earlier detection of progression would have led to earlier changes in patient management in most cases. CONCLUSIONS: Our findings indicate that measurement of changes in tumor volumes is adequately reproducible. Using tumor volumes as the basis for response assessments could have a positive impact on both patient management and clinical trials. More authoritative work to qualify or discard changes in volume as the basis for response assessments should proceed.     

Bioengineered 3D Human Kidney Tissue,a Platform for the Determination of Nephrotoxicity

The staggering cost of bringing a drug to market coupled with the extremely high failure rate of prospective compounds in early phase clinical trials due to unexpected human toxicity makes it imperative that more relevant human models be developed to better predict drug toxicity. Drug–induced nephrotoxicity remains especially difficult to predict in both pre-clinical and clinical settings and is often undetected until patient hospitalization. Current pre-clinical methods of determining renal toxicity include 2D cell cultures and animal models, both of which are incapable of fully recapitulating the in vivo human response to drugs, contributing to the high failure rate upon clinical trials. We have bioengineered a 3D kidney tissue model using immortalized human renal cortical epithelial cells with kidney functions similar to that found in vivo. These 3D tissues were compared to 2D cells in terms of both acute (3 days) and chronic (2 weeks) toxicity induced by Cisplatin, Gentamicin, and Doxorubicin using both traditional LDH secretion and the pre-clinical biomarkers Kim-1 and NGAL as assessments of toxicity. The 3D tissues were more sensitive to drug-induced toxicity and, unlike the 2D cells, were capable of being used to monitor chronic toxicity due to repeat dosing. The inclusion of this tissue model in drug testing prior to the initiation of phase I clinical trials would allow for better prediction of the nephrotoxic effects of new drugs.     

Monitoring of Tumor Response to Cisplatin Using Optical Spectroscopy

INTRODUCTION: Anatomic imaging alone is often inadequate for tuning systemic treatment for individual tumor response. Optically based techniques could potentially contribute to fast and objective response monitoring in personalized cancer therapy. In the present study, we evaluated the feasibility of dual-modality diffuse reflectance spectroscopy–autofluorescence spectroscopy (DRS-AFS) to monitor the effects of systemic treatment in a mouse model for hereditary breast cancer. METHODS: Brca1^−/−; p53^−/− mammary tumors were grown in 36 mice, half of which were treated with a single dose of cisplatin. Changes in the tumor physiology and morphology were measured for a period of 1 week using dual-modality DRS-AFS. Liver and muscle tissues were also measured to distinguish tumor-specific alterations from systemic changes. Model-based analyses were used to derive different optical parameters like the scattering and absorption coefficients, as well as sources of intrinsic fluorescence. Histopathologic analysis was performed for cross-validation with trends in optically based parameters. RESULTS: Treated tumors showed a significant decrease in Mie-scattering slope and Mie-to-total scattering fraction and an increase in both fat volume fraction and tissue oxygenation after 2 days of follow-up. Additionally, significant tumor-specific changes in the fluorescence spectra were seen. These longitudinal trends were consistent with changes observed in the histopathologic analysis, such as vital tumor content and formation of fibrosis. CONCLUSIONS: This study demonstrates that dual-modality DRS-AFS provides quantitative functional information that corresponds well with the degree of pathologic response. DRS-AFS, in conjunction with other imaging modalities, could be used to optimize systemic cancer treatment on the basis of early individual tumor response.     

Ultrasound Targeted Apoptosis Imaging in Monitoring Early Tumor Response of Trastuzumab in a Murine Tumor Xenograft Model of Her-2–Positive Breast Cancer1

OBJECTIVE: Our study aimed to monitor the trastuzumab therapy response of murine tumor xenograft model with human epidermal growth factor receptor 2 (Her-2)–positive breast cancer using ultrasound targeted apoptosis imaging. METHODS: We prepared targeted apoptosis ultrasound probes by nanobubble (NB) binding with Annexin V. In vitro, we investigated the binding rate of NB–Annexin V with breast cancer apoptotic cells after the trastuzumab treatment. In vivo, tumor-bearing mice underwent ultrasound targeted imaging over 7 days. After imaging was completed, the tumors were excised to determine Her-2 and caspase-3 expression by immunohistochemistry (IHC). The correlation between parameters of imaging and histologic results was then analyzed. RESULTS: For seeking the ability of targeted NB binding with apoptotic tumor cells (Her-2 positive), we found that binding rate in the treatment group was higher than that of the control group in vitro (P = .001). There were no differences of tumor sizes in all groups over the treatment process in vivo (P = .98). However, when using ultrasound imaging to visualize tumors by targeted NB in vivo, we observed that the mean and peak intensities from NBs gradually increased in the treatment group after trastuzumab therapy (P = .001). Furthermore, these two parameters were significantly associated with caspase-3 expression of tumor excised samples (P = .0001). CONCLUSION: Ultrasound targeted apoptosis imaging can be a non-invasive technique to evaluate the early breast tumor response to trastuzumab therapy.     

Organ-on-Chip platforms to study tumor evolution and chemosensitivity

Despite tremendous advancements in oncology research and therapeutics, cancer remains a primary cause of death worldwide. One of the significant factors in this critical challenge is a precise diagnosis and limited knowledge on how the tumor microenvironment (TME) behaves to the treatment and its role in chemo-resistance. Therefore, it is critical to understand the contribution of a heterogeneous TME in cancer drug response in individual patients for effective therapy management. Micro-physiological systems along with tissue engineering have facilitated the development of more physiologically relevant platforms, known as Organ-on-Chips (OoC). OoC platforms recapitulate the critical hallmarks of the TME in vitro and subsequently abet in sensitivity and efficacy testing of anti-cancer drugs before clinical trials. The OoC platforms incorporating conventional in vitro models enable researchers to control the cellular, molecular, chemical, and biophysical parameters of the TME in precise combinations while analyzing how they contribute to tumor progression and therapy response. This review discusses the application of OoC platforms integrated with conventional 2D cell lines, 3D organoids and spheroid models, and the organotypic tissue slices, including patient-derived and xenograft tumor slice cultures in cancer treatment responses. We summarize the relevance and drawbacks of conventional in vitro models in assessing cancer treatment response, challenges and limitations associated with OoC models, and future opportunities enabled by the OoC technologies towards developing personalized cancer diagnostics and therapeutics.     

Antibody-Guided In Vivo Imaging for Early Detection of Mammary Gland Tumors

BACKGROUND: Earlier detection of transformed cells using target-specific imaging techniques holds great promise. We have developed TAB 004, a monoclonal antibody highly specific to a protein sequence accessible in the tumor form of MUC1 (tMUC1). We present data assessing both the specificity and sensitivity of TAB 004 in vitro and in genetically engineered mice in vivo. METHODS: Polyoma Middle T Antigen mice were crossed to the human MUC1.Tg mice to generate MMT mice. In MMT mice, mammary gland hyperplasia is observed between 6 and 10 weeks of age that progresses to ductal carcinoma in situ by 12 to 14 weeks and adenocarcinoma by 18 to 24 weeks. Approximately 40% of these mice develop metastasis to the lung and other organs with a tumor evolution that closely mimics human breast cancer progression. Tumor progression was monitored in MMT mice (from ages 8 to 22 weeks) by in vivo imaging following retro-orbital injections of the TAB 004 conjugated to indocyanine green (TAB-ICG). At euthanasia, mammary gland tumors and normal epithelial tissues were collected for further analyses. RESULTS: In vivo imaging following TAB-ICG injection permitted significantly earlier detection of tumors compared with physical examination. Furthermore, TAB-ICG administration in MMT mice enabled the detection of lung metastases while sparing recognition of normal epithelia. CONCLUSIONS: The data highlight the specificity and the sensitivity of the TAB 004 antibody in differentiating normal versus tumor form of MUC1 and its utility as a targeted imaging agent for early detection, tumor monitoring response, as well as potential clinical use for targeted drug delivery.     

Probing Early Tumor Response to Radiation Therapy Using Hyperpolarized [1-13C]pyruvate in MDA-MB-231 Xenografts

Following radiation therapy (RT), tumor morphology may remain unchanged for days and sometimes weeks, rendering anatomical imaging methods inadequate for early detection of therapeutic response. Changes in the hyperpolarized [1-¹³C]lactate signals observed in vivo following injection of pre-polarized [1-¹³C]pyruvate has recently been shown to be a marker for tumor progression or early treatment response. In this study, the feasibility of using ¹³C metabolic imaging with [1-¹³C]pyruvate to detect early radiation treatment response in a breast cancer xenograft model was demonstrated in vivo and in vitro. Significant decreases in hyperpolarized [1-¹³C]lactate relative to [1-¹³C]pyruvate were observed in MDA-MB-231 tumors 96 hrs following a single dose of ionizing radiation. Histopathologic data from the treated tumors showed higher cellular apoptosis and senescence; and changes in the expression of membrane monocarboxylate transporters and lactate dehydrogenase B were also observed. Hyperpolarized ¹³C metabolic imaging may be a promising new tool to develop novel and adaptive therapeutic regimens for patients undergoing RT.     

PSP1, a Phosphatidylserine-Recognizing Peptide,Is Useful for Visualizing Radiation-Induced Apoptosis in Colorectal Cancer In Vitro and In Vivo

Accurate and timely visualization of apoptotic status in response to radiation is necessary for deciding whether to continue radiation or change to another mode of treatment. This is especially critical in patients with colorectal cancer, which requires a delicate combination of surgery, radiation, and chemotherapy in order to achieve optimal outcome. In this study, we investigated the potential of phosphatidylserine-recognizing peptide 1 (PSP1) as an apoptosis-targeting probe, which identifies phosphatidylserine on cell surfaces. We first screened colon cancer cell lines for their sensitivity to radiation and selected two cell lines: HCT116 and HT29. Cell binding assay using fluorescence-activated cell sorting and optical imaging showed that HCT116 cells had better binding to PSP1 than HT29 cells. Thus, mouse xenograft model using HCT116 cells was generated and was topically irradiated with either single or fractionated dose of radiation followed by systemic administration of PSP1 for subsequent molecular optical imaging. We confirmed that the PSP1 probe was selectively bound to apoptosis-induced tumor in a radiation dose-dependent manner. We also observed that fractionated radiation regimen, which is recently being used in clinical situation, was more effective in inducing tumor apoptosis than corresponding single-dose radiation treatment. We then evaluated the correlation between tumor targeting of PSP1 and suppression effect of tumor development and found that tumor volume and fluorescence intensity were correlated before (correlation coefficient r² = 0.534) and after (r² = 0.848) radiation therapy. Our study shows that PSP1 peptide is an efficient index probe for deciding “go or no-go” for radiation therapy in colorectal cancer.     

Diffusion-Weighted MRI as a Biomarker of Tumor Radiation Treatment Response Heterogeneity: A Comparative Study of Whole-Volume Histogram Analysis versus Voxel-Based Functional Diffusion Map Analysis

RATIONALE: Treatment of glioblastoma (GBM) remains challenging due in part to its histologic intratumoral heterogeneity that contributes to its overall poor treatment response. Our goal was to evaluate a voxel-based biomarker, the functional diffusion map (fDM), as an imaging biomarker to detect heterogeneity of tumor response in a radiation dose escalation protocol using a genetically engineered murine GBM model. EXPERIMENTAL DESIGN: Twenty-four genetically engineered murine GBM models [Ink4a-Arf^-/-/Pten^loxp/loxp/Ntv-a RCAS/PDGF(+)/Cre(+)] were randomized in four treatment groups (n = 6 per group) consisting of daily doses of 0, 1, 2, and 4 Gy delivered for 5 days. Contrast-enhanced T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scans were acquired for tumor delineation and quantification of apparent diffusion coefficient (ADC) maps, respectively. MRI experiments were performed daily for a week and every 2 days thereafter. For each animal, the area under the curve (AUC) of the percentage change of the ADC (AUC_ADC) and that of the increase in fDM values (AUC_fDM+) were determined within the first 5 days following therapy initiation. RESULTS: Animal survival increased with increasing radiation dose. Treatment induced a dose-dependent increase in tumor ADC values. The strongest correlation between survival and ADC measurements was observed using the AUC_fDM+ metric (R² = 0.88). CONCLUSION: This study showed that the efficacy of a voxel-based imaging biomarker (fDM) was able to detect spatially varying changes in tumors, which were determined to be a more sensitive predictor of overall response versus whole-volume tumor measurements (AUC_ADC). Finally, fDM provided for visualization of treatment-associated spatial heterogeneity within the tumor.     

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation.     

Epigenetic Regulation of RIP3 Suppresses Necroptosis and Increases Resistance to Chemotherapy in NonSmall Cell Lung Cancer

INTRODUCTION: The efficacy of chemotherapeutic agents in killing cancer cells is mainly attributed to the induction of apoptosis. However, the tremendous efforts on enhancing apoptosis-related mechanisms have only moderately improved lung cancer chemotherapy, suggesting that other cell death mechanisms such as necroptosis could be involved. In this study, we investigated the role of the necroptosis pathway in the responsiveness of nonsmall cell lung cancer (NSCLC) to chemotherapy. METHODS: In vitro cell culture and in vivo xenograft tumor therapy models and clinical sample studies are combined in studying the role of necroptosis in chemotherapy and mechanism of necroptosis suppression involving RIP3 expression regulation. RESULTS: While chemotherapeutic drugs were able to induce necroptotic cell death, this pathway was suppressed in lung cancer cells at least partly through downregulation of RIP3 expression. Ectopic RIP3 expression significantly sensitized lung cancer cells to the cytotoxicity of anticancer drugs such as cisplatin, etoposide, vincristine, and adriamycin. In addition, RIP3 suppression was associated with RIP3 promoter methylation, and demethylation partly restored RIP3 expression and increased chemotherapeutic-induced necroptotic cell death. In a xenograft tumor therapy model, ectopic RIP3 expression significantly sensitized anticancer activity of cisplatin in vivo. Furthermore, lower RIP3 expression was associated with worse chemotherapy response in NSCLC patients. CONCLUSION: Our results indicate that the necroptosis pathway is suppressed in lung cancer through RIP3 promoter methylation, and reactivating this pathway should be exploited for improving lung cancer chemotherapy.     

Multiparametric Characterization of Grade 2 Glioma Subtypes Using Magnetic Resonance Spectroscopic,Perfusion, and Diffusion Imaging

BACKGROUND AND PURPOSE: The purpose of this study was to derive quantitative parameters from magnetic resonance (MR) spectroscopic, perfusion, and diffusion imaging of grade 2 gliomas according to the World Health Organization and to investigate how these multiple imaging modalities can contribute to evaluating their histologic subtypes and spatial characteristics. MATERIALS AND METHODS: MR spectroscopic, perfusion, and diffusion images from 56 patients with newly diagnosed grade 2 glioma (24 oligodendrogliomas, 18 astrocytomas, and 14 oligoastrocytomas) were retrospectively studied. Metabolite intensities, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) were statistically evaluated. RESULTS: The 75th percentile rCBV and median ADC were significantly different between oligodendrogliomas and astrocytomas (P < .0001) and between oligodendrogliomas and oligoastrocytomas (P < .001). Logistic regression analysis identified both 75th percentile rCBV and median ADC as significant variables in the differentiation of oligodendrogliomas from astrocytomas and oligoastrocytomas. Group differences in metabolite intensities were not significant, but there was a much larger variation in the volumes and maximum values of metabolic abnormalities for patients with oligodendroglioma compared with the other tumor subtypes. CONCLUSIONS: Perfusion and diffusion imaging provide quantitative MR parameters that can help to differentiate grade 2 oligodendrogliomas from grade 2 astrocytomas and oligoastrocytomas. The large variations in the magnitude and spatial extent of the metabolic lesions between patients and the fact that their values are not correlated with the other imaging parameters indicate that MR spectroscopic imaging may provide complementary information that is helpful in targeting therapy, evaluating residual disease, and assessing response to therapy.     

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for radiologic assessment of solid tumors in response to anti-tumor drug therapy in the 1980s and 1990s, respectively. WHO criteria measure solid tumors in two-dimensions, whereas RECIST measurements use only one-dimension which is considered to be more reproducible ^{1, 2, 3,4,5}. These criteria have been widely used as the only imaging biomarker approved by the United States Food and Drug Administration (FDA) ⁶. In order to measure tumor response to anti-tumor drugs on images with accuracy, therefore, a robust quality assurance (QA) procedures and corresponding QA phantom are needed.To address this need, the authors constructed a preclinical multimodality (for ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI)) phantom using tissue-mimicking (TM) materials based on the limited number of target lesions required by RECIST by revising a Gammex US commercial phantom ⁷. The Appendix in Lee et al. demonstrates the procedures of phantom fabrication ⁷. In this article, all protocols are introduced in a step-by-step fashion beginning with procedures for preparing the silicone molds for casting tumor-simulating test objects in the phantom, followed by preparation of TM materials for multimodality imaging, and finally construction of the preclinical multimodality QA phantom. The primary purpose of this paper is to provide the protocols to allow anyone interested in independently constructing a phantom for their own projects. QA procedures for tumor size measurement, and RECIST, WHO and volume measurement results of test objects made at multiple institutions using this QA phantom are shown in detail in Lee et al. ⁸.