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Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking., (© RSNA, 2024 See also the editorial by Huisman and D'Antonoli in this issue.)

Immunotherapy has transformed the treatment landscape of many cancers, with durable responses in disease previously associated with a poor prognosis. Patient selection remains a challenge, with predictive biomarkers an urgent unmet clinical need. Current predictive biomarkers, including programmed death-ligand 1 (PD-L1) (measured with immunohistochemistry), are imperfect. Promising biomarkers, including tumor mutation burden and tumor infiltrating lymphocyte density, fail to consistently predict response and have yet to translate to routine clinical practice. Heterogeneity of immune response within and between lesions presents a further challenge where fluorine 18 fluorodeoxyglucose PET/CT has a potential role in assessing response, stratifying treatment, and detecting and monitoring immune-related toxicities. Novel radiopharmaceuticals also present a unique opportunity to define the immune tumor microenvironment to better predict which patients may respond to therapy, for example by means of in vivo whole-body PD-L1 and CD8+ T cell expression imaging. In addition, longitudinal molecular imaging may help further define dynamic changes, particularly in cases of immunotherapy resistance, helping to direct a more personalized therapeutic approach. This review highlights current and emerging applications of molecular imaging to stratify, predict, and monitor molecular dynamics and treatment response in areas of clinical need., (© RSNA, 2022.)

The current coronavirus disease 2019 (COVID-19) crisis continues to grow and has resulted in marked changes to clinical operations. In parallel with clinical preparedness, universities have shut down most scientific research activities. Radiology researchers are currently grappling with these challenges that will continue to affect current and future imaging research. The purpose of this article is to describe the collective experiences of a diverse international group of academic radiology research programs in managing their response to the COVID-19 pandemic. The acute response at six distinct institutions will be described first, exploring common themes, challenges, priorities, and practices. This will be followed by reflections about the future of radiology research in the wake of the COVID-19 pandemic., (© RSNA, 2020.)

Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue.

Purpose To develop and test an artificial intelligence (AI) system, based on deep convolutional neural networks (CNNs), for automated real-time triaging of adult chest radiographs on the basis of the urgency of imaging appearances. Materials and Methods An AI system was developed by using 470 388 fully anonymized institutional adult chest radiographs acquired from 2007 to 2017. The free-text radiology reports were preprocessed by using an in-house natural language processing (NLP) system modeling radiologic language. The NLP system analyzed the free-text report to prioritize each radiograph as critical, urgent, nonurgent, or normal. An AI system for computer vision using an ensemble of two deep CNNs was then trained by using labeled radiographs to predict the clinical priority from radiologic appearances only. The system's performance in radiograph prioritization was tested in a simulation by using an independent set of 15 887 radiographs. Prediction performance was assessed with the area under the receiver operating characteristic curve; sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also determined. Nonparametric testing of the improvement in time to final report was determined at a nominal significance level of 5%. Results Normal chest radiographs were detected by our AI system with a sensitivity of 71%, specificity of 95%, PPV of 73%, and NPV of 94%. The average reporting delay was reduced from 11.2 to 2.7 days for critical imaging findings (P < .001) and from 7.6 to 4.1 days for urgent imaging findings (P < .001) in the simulation compared with historical data. Conclusion Automated real-time triaging of adult chest radiographs with use of an artificial intelligence system is feasible, with clinically acceptable performance. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Auffermann in this issue.

Purpose To assess the day-to-day repeatability of global and local-regional magnetic resonance (MR) imaging texture features derived from primary rectal cancer. Materials and Methods After ethical approval and patient informed consent were obtained, two pretreatment T2-weighted axial MR imaging studies performed prospectively with the same imaging unit on 2 consecutive days in 14 patients with rectal cancer (11 men [mean age, 61.7 years], three women [mean age, 70.0 years]) were analyzed to extract (a) global first-order statistical histogram and model-based fractal features reflecting the whole-tumor voxel intensity histogram distribution and repeating patterns, respectively, without spatial information and (b) local-regional second-order and high-order statistical texture features reflecting the intensity and spatial interrelationships between adjacent in-plane or multiplanar voxels or regions, respectively. Repeatability was assessed for 46 texture features, and mean difference, 95% limits of agreement, within-subject coefficient of variation (wCV), and repeatability coefficient (r) were recorded. Results Repeatability was better for global parameters than for most local-regional parameters. In particular, histogram mean, median, and entropy, fractal dimension mean and standard deviation, and second-order entropy, homogeneity, difference entropy, and inverse difference moment demonstrated good repeatability, with narrow limits of agreement and wCVs of 10% or lower. Repeatability was poorest for the following high-order gray-level run-length (GLRL) gray-level zone size matrix (GLZSM) and neighborhood gray-tone difference matrix (NGTDM) parameters: GLRL intensity variability, GLZSM short-zone emphasis, GLZSM intensity nonuniformity, GLZSM intensity variability, GLZSM size zone variability, and NGTDM complexity, demonstrating wider agreement limits and wCVs of 50% or greater. Conclusion MR imaging repeatability is better for global texture parameters than for local-regional texture parameters, indicating that global texture parameters should be sufficiently robust for clinical practice. Online supplemental material is available for this article.

Purpose: To determine if first-order and high-order textural features on fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET) images of non-small cell lung cancer (NSCLC) (a) at baseline, (b) at 6 weeks, or (c) the percentage change between baseline and 6 weeks can predict response or survival in patients treated with erlotinib., Materials and Methods: Institutional review board approval was obtained for post hoc analysis of data from a prospective single-center study for which informed consent was obtained. The study included 47 patients with NSCLC who underwent (18)F-FDG PET/computed tomography (CT) at baseline (n = 47) and 6 weeks (n = 40) after commencing treatment with erlotinib. First-order and high-order primary tumor texture features reflecting image heterogeneity, standardized uptake values, metabolic tumor volume, and total lesion glycolysis were measured for all (18)F-FDG PET studies. Response to erlotinib was assessed by using the Response Evaluation Criteria in Solid Tumors (RECIST) on CT images obtained at 12 weeks (n = 32). Associations between PET parameters, overall survival (OS), and RECIST-based treatment response were tested by Cox and logistic regression analyses, respectively., Results: Median OS was 14.1 months. According to CT RECIST at 12 weeks, there were 21 nonresponders and 11 responders. Response to erlotinib was associated with reduced heterogeneity (first-order standard deviation, P = .01; entropy, P = .001; uniformity, P = .001). At multivariable analysis, high-order contrast at 6 weeks (P = .002) and percentage change in first-order entropy (P = .03) were independently associated with survival. Percentage change in first-order entropy was also independently associated with treatment response (P = .01)., Conclusion: Response to erlotinib is associated with reduced heterogeneity at (18)F-FDG PET. Changes in first-order entropy are independently associated with OS and treatment response.

Purpose: To evaluate whether changes in magnetic resonance (MR) imaging heterogeneity may aid assessment for pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) in primary breast cancer and to compare pCR with standard Response Evaluation Criteria in Solid Tumors response., Materials and Methods: Institutional review board approval, with waiver of informed consent, was obtained for this retrospective analysis of 36 consecutive female patients, with unilateral unifocal primary breast cancer larger than 2 cm in diameter who were receiving sequential anthracycline-taxane NACT between October 2008 and October 2012. T2- and T1-weighted dynamic contrast material-enhanced MR imaging was performed before, at midtreatment (after three cycles), and after NACT. Changes in tumor entropy (irregularity) and uniformity (gray-level distribution) were determined before and after MR image filtration (for different-sized features). Entropy and uniformity for pathologic complete responders and nonresponders were compared by using the Mann-Whitney U test and receiver operating characteristic analysis., Results: With NACT, there was an increase in uniformity and a decrease in entropy on T2-weighted and contrast-enhanced subtracted T1-weighted MR images for all filters (uniformity: 23.45% and 22.62%; entropy: -19.15% and -19.26%, respectively). There were eight complete pathologic responders. An area under the curve of 0.84 for T2-weighted MR imaging entropy and uniformity (P = .004 and .003) and 0.66 for size (P = .183) for pCR was found, giving a sensitivity and specificity of 87.5% and 82.1% for entropy and 87.5% and 78.6% for uniformity compared with 50% and 82.1%, respectively, for tumor size change for association with pCR., Conclusion: Tumors become more homogeneous with treatment. An increase in T2-weighted MR imaging uniformity and a decrease in T2-weighted MR imaging entropy following NACT may provide an earlier indication of pCR than tumor size change., (© RSNA, 2014.)

Purpose: To determine the association between tumor heterogeneity, morphologic tumor response, and overall survival in primary esophageal cancer treated with chemotherapy and radiation therapy (CRT)., Materials and Methods: After an institutional review board waiver was obtained, contrast material-enhanced computed tomographic (CT) studies in 36 patients with stage T2 or greater esophageal tumors who underwent contrast-enhanced CT before and after CRT between 2005 and 2008 were analyzed in terms of whole-tumor texture, with quantification of entropy, uniformity, mean gray-level intensity, kurtosis, standard deviation of the histogram, and skewness for fine to coarse textures (filters 1.0-2.5, respectively). The association between texture parameters and survival time was assessed by using Kaplan-Meier analysis and a Cox proportional hazards model. Survival models involving texture parameters and combinations of texture and morphologic response assessment were compared with morphologic assessment alone by means of receiver operating characteristic (ROC) analysis., Results: Posttreatment medium entropy of less than 7.356 (median overall survival, 33.2 vs 11.7 months; P = .0002), coarse entropy of less than 7.116 (median overall survival, 33.2 vs 11.7 months; P = .0002), and medium uniformity of 0.007 or greater (median overall survival, 33.2 vs 11.7 months; P = .0002) were associated with improved survival time. These remained significant prognostic factors after adjustment for stage and age: entropy (filter 2.0: hazard ratio [HR] = 5.038, P = .0004; filter 2.5: HR = 5.038, P = .0004) and uniformity (HR = 0.199, P = .0004). Survival models that included a combination of pretreatment entropy and uniformity with maximal wall thickness assessment, respectively, performed better than morphologic assessment alone (area under the ROC curve, 0.767 vs 0.487 [P = .00005] and 0.802 vs 0.487 [P = .0003])., Conclusion: Posttreatment texture parameters are associated with survival time, and the combination of pretreatment texture parameters and maximal wall thickness performed better in survival models than morphologic tumor response alone., (© RSNA, 2013.)

Purpose: To compare four different tracer kinetic models for the analysis of dynamic contrast material-enhanced computed tomographic (CT) data with respect to the prediction of 5-year overall survival in primary colorectal cancer., Materials and Methods: This study was approved by the ethical review board. Archival dynamic contrast-enhanced CT data from 46 patients with colorectal cancer, obtained as part of a research study, were analyzed retrospectively by using the distributed parameter, conventional compartmental, adiabatic tissue homogeneity, and generalized kinetic models. Blood flow, blood volume, mean transit time (MTT), permeability-surface area product, extraction fraction, extravascular extracellular volume (v(e)), and volume transfer constant (K(trans)) were compared by using the Friedman test, with statistical significance at 5%. Following receiver operating characteristic analysis, parameters of the different kinetic models and tumor stage were compared with respect to overall survival discrimination, with use of Kaplan Meier analysis and a univariate Cox proportional hazard model, with additional cross-validation and permutation testing., Results: Blood flow was lower with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001), and blood flow values determined with the conventional compartmental and adiabatic tissue homogeneity models were similar. Conversely, MTT was longer with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001). Blood volume, permeability-surface area product, and v(e) were higher with the conventional compartmental model than with the adiabatic tissue homogeneity, distributed parameter, or generalized kinetic models (P < .0001). The extraction fraction was higher with the distributed parameter model than with the adiabatic tissue homogeneity model. With respect to 5-year overall survival, only the distributed parameter model-derived v(e) was predictive of 5-year overall survival with a threshold value of 15.48 mL/100 mL after cross-validation and permutation testing., Conclusion: Parameter values differ significantly between models. Of the models investigated, the distributed parameter model was the best predictor of 5-year overall survival., Supplemental Material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120186/-/DC1., (RSNA, 2013)

Purpose: To correlate computed tomographic (CT) texture in non-small cell lung cancer (NSCLC) with histopathologic markers for angiogenesis and hypoxia., Materials and Methods: The study was institutional review board approved, and informed consent was obtained. Fourteen patients with NSCLC underwent CT prior to intravenous administration of pimonidazole (0.5 g/m(2)), a marker of hypoxia, 24 hours before surgery. Texture was assessed for unenhanced and contrast material-enhanced CT images by using a software algorithm that selectively filters and extracts texture at different anatomic scales (1.0 [fine detail] to 2.5 [coarse features]), with quantification of the standard deviation (SD) of all pixel values and the mean value of positive pixels (MPP) and uniformity of distribution of positive gray-level pixel values (UPP). After surgery, matched tumor sections were stained for angiogenesis (CD34 expression) and for markers of hypoxia (glucose transporter protein 1 [Glut-1] and pimonidazole). The percentage and average intensity of the tumor stained were assessed. A linear mixed-effects model was used to assess the correlations between CT texture and staining intensity., Results: SD and MPP quantified from medium to coarse texture on contrast-enhanced CT images showed significant associations with the average intensity of tumor staining with pimonidazole (for SD: filter value, 2.5; slope = 0.003; P = .0003). UPP (medium to coarse texture) on unenhanced CT images showed a significant inverse association with tumor Glut-1 expression (filter value, 2.5; slope = -115.13; P = .0008). MPP quantified from medium to coarse texture on both unenhanced and contrast-enhanced CT images showed significant inverse associations with tumor CD34 expression (unenhanced CT: filter value, 1.8; slope = -0.0008; P = .003; contrast-enhanced CT: filter value, 1.8; slope = -0.0006; P = .004)., Conclusion: Texture parameters derived from CT images of NSCLC have the potential to act as imaging correlates for tumor hypoxia and angiogenesis., Supplemental Material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112428/-/DC1., (RSNA, 2012)

Purpose: To determine if computed tomographic (CT) texture features of primary colorectal cancer are related to 5-year overall survival rate., Materials and Methods: Institutional review board waiver was obtained for this retrospective analysis. Texture features of the entire primary tumor were assessed with contrast material-enhanced staging CT studies obtained in 57 patients as part of an ethically approved study and by using proprietary software. Entropy, uniformity, kurtosis, skewness, and standard deviation of the pixel distribution histogram were derived from CT images without filtration and with filter values corresponding to fine (1.0), medium (1.5, 2.0), and coarse (2.5) textures. Patients were followed up until death and were censored at 5 years if they were still alive. Kaplan-Meier analysis was performed to determine the relationship, if any, between CT texture and 5-year overall survival rate. The Cox proportional hazards model was used to assess independence of texture parameters from stage., Results: Follow-up data were available for 55 of 57 patients. There were eight stage I, 19 stage II, 17 stage III, and 11 stage IV cancers. Fine-texture feature Kaplan-Meier survival plots for entropy, uniformity, kurtosis, skewness, and standard deviation of the pixel distribution histogram were significantly different for tumors above and below each respective threshold receiver operating characteristic (ROC) curve optimal cutoff value (P = .001, P = .018, P = .032, P = .008, and P = .001, respectively), with poorer prognosis for ROC optimal values (a) less than 7.89 for entropy, (b) at least 0.01 for uniformity, (c) less than 2.48 for kurtosis, (d) at least -0.38 for skewness, and (e) less than 61.83 for standard deviation. Multivariate Cox proportional hazards regression analysis showed that each parameter was independent from the stage predictor of overall survival rate (P = .001, P = .009, P = .006, P = .02, and P = .001, respectively)., Conclusion: Fine-texture features are associated with poorer 5-year overall survival rate in patients with primary colorectal cancer., Supplemental Material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120254/-/DC1., (RSNA, 2012)

Purpose: To assess the relationship between helical dynamic contrast material-enhanced (DCE) computed tomographic (CT) parameters and immunohistochemical markers of hypoxia in patients with operable non-small cell lung cancer (NSCLC)., Materials and Methods: After institutional review board approval was obtained, 20 prospective patients who were suspected of having NSCLC underwent whole-tumor DCE CT with kinetic modeling (Patlak analysis) 24 hours before scheduled surgery. Flow-extraction product (in milliliters per 100 milliliters per minute) and blood volume (in milliliters per 100 milliliters) were derived. After surgery, matched whole-tumor sections were stained for exogenous and endogenous markers of hypoxia (pimonidazole infused intravenously 24 hours before surgery, immediately after DCE CT; glucose transporter protein). Correlation between DCE CT parameters and immunohistochemical markers was assessed by using the Spearman rank correlation. DCE CT parameters and immunohistochemical markers were also compared according to pathologic subtype, grade, stage, and nodal status by using the Mann-Whitney test. P values less than .05 indicated a statistically significant difference., Result: Fourteen patients with confirmed primary NSCLC underwent resection. There were negative correlations between blood volume and pimonidazole staining (r = -0.48, P = .004), and between flow-extraction product and glucose transporter protein expression (r = -0.50, P = .002). Flow-extraction product was significantly higher in adenocarcinomas than in squamous cell tumors (17.73 vs 11.46; P = .043). Glucose transporter protein expression was significantly lower for adenocarcinomas than for squamous tumors (14.07 vs 33.03; P < .001) and in node negative than in node positive tumors (15.63 vs 23.85; P = .005)., Conclusion: Blood volume and flow-extraction product derived at DCE CT correlated negatively with pimonidazole and glucose transporter protein expression, indicating the potential of these CT parameters as imaging biomarkers of hypoxia.

Purpose: To characterize the two-dimensional (2D) and three-dimensional (3D) fractal properties of rectal cancer regional blood flow assessed by using volumetric helical perfusion computed tomography (CT) and to determine its reproducibility., Materials and Methods: Institutional review board approval and informed consent were obtained. Ten prospective patients (eight men, two women; mean age, 72.3 years) with rectal adenocarcinoma underwent two repeated volumetric helical perfusion CT studies (four-dimensional adaptive spiral mode, 11.4-cm z-axis coverage) without intervening treatment within 24 hours, with regional blood flow derived by using deconvolution analysis. Two-dimensional and 3D fractal analyses of the rectal tumor were performed, after segmentation from surrounding structures by using thresholding, to derive fractal dimension and fractal abundance. Reproducibility was quantitatively assessed by using Bland-Altman statistics. Two-dimensional and 3D lacunarity plots were also generated, allowing qualitative assessment of reproducibility. Statistical significance was at 5%., Results: Mean blood flow was 63.50 mL/min/100 mL ± 8.95 (standard deviation). Good agreement was noted between the repeated studies for fractal dimension; mean difference was -0.024 (95% limits of agreement: -0.212, 0.372) for 2D fractal analysis and -0.024 (95% limits of agreement: -0.307, 0.355) for 3D fractal analysis. Mean difference for fractal abundance was -0.355 (95% limits of agreement: -0.869, 1.579) for 2D fractal analysis and -0.043 (95% limits of agreement: -1.154, 1.239) for 3D fractal analysis. The 95% limits of agreement were narrower for 3D than 2D analysis. Lacunarity plots also visually confirmed close agreement between repeat studies., Conclusion: Regional blood flow in rectal cancer exhibits fractal properties. Good reproducibility was achieved between repeated studies with 2D and 3D fractal analysis.

Targeted therapies are designed to interfere with specific aberrant biologic pathways involved in tumor development. The main classes of novel oncologic drugs include antiangiogenic drugs, antivascular agents, drugs interfering with EGFR-HER2 or KIT receptors, inhibitors of the PI3K/Akt/mTOR pathway, and hormonal therapies. Cancer cells usurp normal signal transduction pathways used by growth factors to stimulate proliferation and sustain viability. The interaction of growth factors with their receptors activates different intracellular pathways affecting key tumor biologic processes such as neoangiogenesis, tumor metabolism, and tumor proliferation. The response of tumors to anticancer therapy can be evaluated with anatomic response assessment, qualitative response assessment, and response assessment with functional and molecular imaging. Angiogenesis can be measured by means of perfusion imaging with computed tomography and magnetic resonance (MR) imaging. Diffusion-weighted MR imaging allows imaging evaluation of tumor cellularity. The main imaging techniques for studying tumor metabolism in vivo are positron emission tomography and MR spectroscopy. Familiarity with imaging findings secondary to tumor response to targeted therapies may help the radiologist better assist the clinician in accurate evaluation of tumor response to these anticancer treatments. Functional and molecular imaging techniques may provide valuable data and augment conventional assessment of tumor response to targeted therapies. Supplemental material available at http://radiographics.rsna.org/lookup/suppl/doi:10.1148/rg.317115108/-/DC1.

Purpose: To assess changes in tumor computed tomographic (CT) texture after two cycles of treatment with tyrosine kinase inhibitors (TKIs) and to determine if tumor texture correlates with measured time to progression in patients with metastatic renal cell cancer who received TKIs., Materials and Methods: A waiver of institutional review board approval was obtained for this retrospective analysis. Contrast material-enhanced CT texture parameters were assessed in 39 patients with metastatic renal cell cancer who received a TKI. A total of 87 metastases were analyzed at baseline and after two treatment cycles. Changes in tumor entropy and uniformity were derived with a software algorithm that selectively filters and extracts texture at different scales (fine to coarse detail: 1.0-2.5) and were recorded. Response assessment was also obtained by using response evaluation criteria in solid tumors (RECIST), as well as Choi and modified Choi criteria. The correlation of texture parameters and standard criteria with measured time to progression was assessed by using Kaplan-Meier analysis and a Cox regression model. Statistical significance was set at 5%., Results: Tumor entropy decreased by 3%-45% and uniformity increased by 5%-21% for the different scale values after administration of a TKI. With a threshold change of -2% or less for uniformity at a coarse scale value of 2.5, Kaplan-Meier curves of the proportion of patients without disease progression were significantly different and better than those for standard response assessment (P = .008 vs P = .267, P = .053, and P = .042 for RECIST, Choi, and modified Choi criteria, respectively). Cox regression analysis showed that texture uniformity was an independent predictor of time to progression (odds ratio, 4.02; 95% confidence interval: 1.52, 10.65; P = .005)., Conclusion: CT texture analysis reflecting tumor heterogeneity is an independent factor associated with time to progression and has potential as a predictive imaging biomarker of response of metastatic renal cancer to targeted therapy., (© RSNA, 2011.)

Purpose: To establish the relationships between quantitative perfusion computed tomography (CT) parameters-specifically, primary tumor blood flow, blood volume, transit time, and permeability surface-area product-and immunohistologic markers of angiogenesis in colorectal cancer., Materials and Methods: After institutional review board approval and informed patient consent were obtained for this prospective study, 23 patients (11 men, 12 women; mean age, 68.4 years; age range, 34.8-87.1 years) with colorectal adenocarcinoma underwent a 65-second perfusion CT examination, and tumor blood flow, blood volume, mean transit time, and permeability surface-area product were determined. After surgery, resected specimens were sectioned and stained immunohistochemically to identify CD34 for quantification of microvessel density (MVD), to identify smooth muscle actin for assessment of pericyte coverage index, to identify vascular endothelial growth factor (VEGF), and to identify glucose transporter protein (GLUT-1). Perfusion CT measurements were correlated with MVD, pericyte coverage index, VEGF expression, and GLUT-1 expression by using Pearson or Spearman rank correlation analysis, with significance assigned at the 5% level., Results: Mean blood flow, blood volume, transit time, and permeability surface-area product values were 72.1 mL/min/100 g of tissue +/- 28.4 (standard deviation), 6.2 mL/100 g of tissue +/- 1.4, 9.3 seconds +/- 3.9, and 13.9 mL/min/100 g of tissue +/- 3.2, respectively. Blood volume (r = 0.59, P = .002) and permeability surface-area product (r = 0.46, P = .03) correlated positively with MVD, but blood flow (r = 0.27, P = .22) and transit time (r = -0.18, P = .44) did not. There were no significant associations between any perfusion CT parameter and pericyte coverage index (r .05), VEGF score (rho or= .15), or GLUT-1 score (rho < 0.21, P >or= .33)., Conclusion: Tumor permeability surface-area product and blood volume correlate positively with MVD and may reflect the microvascularity of colorectal tumors., ((c) RSNA, 2008.)

Purpose: To prospectively determine whether position and size of tumor region of interest (ROI) influence estimates of colorectal cancer vascular parameters at computed tomography (CT)., Materials and Methods: After institutional review board approval and informed consent, 25 men and 22 women (mean age, 65.8 years) with colorectal adenocarcinoma underwent 65-second CT perfusion study. Blood volume, blood flow, and permeability-surface area product were determined for 40- or 120-mm(2) circular ROIs placed at the tumor edge and center and around (outlining) visible tumor. ROI analysis was repeated by two observers in different subsets of patients to assess intra- and interobserver variation. Measurements were compared by using analysis of variance; a difference with P = .002 was significant., Results: Blood volume, blood flow, and permeability-surface area product measurements were substantially higher at the edge than at the center for both 40- and 120-mm(2) ROIs. For 40-mm(2) ROI, means of the three measurements were 6.9 mL/100 g (standard deviation [SD], 1.4), 108.7 mL/100 g per minute (SD, 39.2), and 16.9 mL/100 g per minute (SD, 4.2), respectively, at the edge versus 5.1 mL/100 g (SD, 1.5), 56.3 mL/100 g per minute (SD, 33.1), and 13.9 mL/100 g per minute (SD, 4.6), respectively, at the center. For 120-mm(2) ROI, means of the three measurements were 6.6 mL/100 g (SD, 1.3), 96.7 mL/100 g per minute (SD, 42.5), and 16.3 mL/100 g per minute (SD, 5.6), respectively, at the edge versus 5.1 mL/100 g (SD, 1.4), 58.3 mL/100 g per minute (SD, 32.5), and 13.4 mL/100 g per minute (SD, 4.3) at the center (P < .0001). Measurements varied substantially depending on the ROI size; values for the ROI for outlined tumor were intermediate between those at the tumor edge and center. Inter- and intraobserver agreement was poor for both 40- and 120-mm(2) ROIs., Conclusion: Position and size of tumor ROI and observer variation substantially influence ultimate perfusion values. ROI for outlined entire tumor is more reliable for perfusion measurements and more appropriate clinically than use of arbitrarily determined smaller ROIs., ((c) RSNA, 2008.)

Purpose: To retrospectively compare primary three-dimensional (3D) endoluminal analysis with primary two-dimensional (2D) transverse analysis supplemented by computer-assisted reader (CAR) software for computed tomographic (CT) polyp detection and reader reporting times., Materials and Methods: Ethical permission and patient consent were obtained from all donor institutions for use of CT colonography data sets. Twenty CT colonography data sets from 14 men (median age, 61 years; age range, 52-78 years) with 48 endoscopically proved polyps were selected. Polyp coordinates were documented in consensus by three unblinded radiologists to create a reference standard. Two radiologists read the data sets, which were randomized between primary 3D endoluminal views with 2D problem solving and 2D views supplemented by CAR software. Reading times and diagnostic confidence were documented. The CAR software highlighted possible polyps by superimposing circles on the 2D transverse images. Data sets were reread after 1 month by using the opposing analysis method. Detection rates were compared by using the McNemar test. Reporting times and diagnostic confidence were compared by using the paired t test and Mann-Whitney U test, respectively., Results: Mean sensitivity values for polyps measuring 1-5, 6-9, and 10 mm or larger were 14%, 53%, and 83%, respectively, for 2D CAR analysis and 16%, 53%, and 67%, respectively, for primary 3D analysis. Overall sensitivity values were 41% for 2D CAR analysis and 39% for primary 3D analysis (P=.77). Reader 1 detected more polyps than reader 2, particularly when using the 3D fly-through method (P=.002). Mean reading times were significantly longer with the 3D method (P=.001). Mean false-positive findings were 1.5 for 2D analysis and 5.5 for 3D analysis. Reader confidence was not significantly different between analysis methods (P=.42)., Conclusion: Two-dimensional CAR analysis is quicker and at least matches the sensitivity of primary 3D endoluminal analysis, with fewer false-positive findings., (Copyright (c) RSNA, 2006.)

Institutional review board approval and informed consent were obtained for this study. The aim of the study was to prospectively assess, in patients with lung cancer, the reproducibility of a quantitative whole tumor perfusion computed tomographic (CT) technique. Paired CT studies were performed in 10 patients (eight men, two women; mean age, 66 years) with lung cancer. Whole tumor permeability and blood volume were measured, and reproducibility was evaluated by using Bland-Altman statistics. Coefficient of variation of 9.49% for permeability and 26.31% for blood volume and inter- and intraobserver variability ranging between 3.30% and 6.34% indicate reliable assessment with this whole tumor technique., ((c) RSNA, 2006.)

Purpose: To investigate the effects of hyoscine butylbromide and an inflatable rectal balloon catheter on luminal distention during computed tomographic (CT) colonography., Materials and Methods: One hundred thirty-six subjects undergoing CT colonography were randomized to receive either 20 mg or 40 mg of hyoscine butylbromide or no spasmolytic. Subjects were also independently randomized to undergo CT colonography with an inflatable rectal balloon catheter or a standard thin rectal tube. Multi-detector row CT colonography was performed with patients in prone and supine positions, with colonic segmental distention assessed by a single observer with a four-point scale. A simple assessment of whether distention was adequate for clinical interpretation was also made, and the effect of hyoscine butylbromide and catheter use was examined by using multivariate ordered logistic regression., Results: Administration of hyoscine butylbromide was associated with significantly improved cecal (P =.05), ascending (P =.001), and transverse (P <.001) colonic distention when patients were supine and improved ascending (P <.001) and descending (P <.001) colonic distention when patients were prone. Compared with control subjects, patients given a spasmolytic had odds of 6.49 for clinically adequate distention throughout all colonic segments (P =.001). There was no incremental advantage with use of a 40-mg dose. In contrast, rectal balloon catheter use was not significantly associated with improved distention., Conclusion: Hyoscine butylbromide improves colonic distention during CT colonography and should be routinely administered where it is available. Use of a thin rectal tube for insufflation is adequate., (Copyright RSNA, 2003)