Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis.

OBJECTIVES: To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC). METHODS: This retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features which were computed from each tumor site. Three texture features that represented intra- and inter-site tumor heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumor sites and metastasis. Correlations between protein abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation coefficient and the Mann-Whitney U test, whereas the area under the receiver operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. P values < 0.05 were considered significant. RESULTS: Four proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p < 0.001, AUC = 0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumor heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p = 0.047, τ = 0.326). CONCLUSION: This study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra- and inter-site heterogeneity, and the abundance of several proteins. KEY POINTS: • CT-based texture features of intra- and inter-site tumor heterogeneity correlate with the abundance of several proteins in patients with HGSOC. • CT imaging traits correlate with protein abundance in patients with HGSOC.

Radiogenomics of High-Grade Serous Ovarian Cancer: Multireader Multi-Institutional Study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group.

Purpose To evaluate interradiologist agreement on assessments of computed tomography (CT) imaging features of high-grade serous ovarian cancer (HGSOC), to assess their associations with time-to-disease progression (TTP) and HGSOC transcriptomic profiles (Classification of Ovarian Cancer [CLOVAR]), and to develop an imaging-based risk score system to predict TTP and CLOVAR profiles. Materials and Methods This study was a multireader, multi-institutional, institutional review board-approved, HIPAA-compliant retrospective analysis of 92 patients with HGSOC (median age, 61 years) with abdominopelvic CT before primary cytoreductive surgery available through the Cancer Imaging Archive. Eight radiologists from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group developed and independently recorded the following CT features: characteristics of primary ovarian mass(es), presence of definable mesenteric implants and infiltration, presence of other implants, presence and distribution of peritoneal spread, presence and size of pleural effusions and ascites, lymphadenopathy, and distant metastases. Interobserver agreement for CT features was assessed, as were univariate and multivariate associations with TTP and CLOVAR mesenchymal profile (worst prognosis). Results Interobserver agreement for some features was strong (eg, α = .78 for pleural effusion and ascites) but was lower for others (eg, α = .08 for intraparenchymal splenic metastases). Presence of peritoneal disease in the right upper quadrant (P = .0003), supradiaphragmatic lymphadenopathy (P = .0004), more peritoneal disease sites (P = .0006), and nonvisualization of a discrete ovarian mass (P = .0037) were associated with shorter TTP. More peritoneal disease sites (P = .0025) and presence of pouch of Douglas implants (P = .0045) were associated with CLOVAR mesenchymal profile. Combinations of imaging features contained predictive signal for TTP (concordance index = 0.658; P = .0006) and CLOVAR profile (mean squared deviation = 1.776; P = .0043). Conclusion These results provide some evidence of the clinical and biologic validity of these image features. Interobserver agreement is strong for some features, but could be improved for others. © RSNA, 2017 Online supplemental material is available for this article.

Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor.

PURPOSE: To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers. MATERIALS AND METHODS: An institutional review board waiver was obtained for this HIPAA-compliant retrospective study. Forty-five patients with GBM underwent baseline imaging with contrast material-enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging. Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests. RESULTS: Worsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBVNER), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBVNER and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBVNER marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBVNER as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBVNER, age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49-1.79 years). CONCLUSION: Patients with high rCBVNER and NER crossing the midline and those with high rCBVNER and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBVNER provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.

Image data sharing for biomedical research--meeting HIPAA requirements for De-identification.

Data sharing is increasingly recognized as critical to cross-disciplinary research and to assuring scientific validity. Despite National Institutes of Health and National Science Foundation policies encouraging data sharing by grantees, little data sharing of clinical data has in fact occurred. A principal reason often given is the potential of inadvertent violation of the Health Insurance Portability and Accountability Act privacy regulations. While regulations specify the components of private health information that should be protected, there are no commonly accepted methods to de-identify clinical data objects such as images. This leads institutions to take conservative risk-averse positions on data sharing. In imaging trials, where images are coded according to the Digital Imaging and Communications in Medicine (DICOM) standard, the complexity of the data objects and the flexibility of the DICOM standard have made it especially difficult to meet privacy protection objectives. The recent release of DICOM Supplement 142 on image de-identification has removed much of this impediment. This article describes the development of an open-source software suite that implements DICOM Supplement 142 as part of the National Biomedical Imaging Archive (NBIA). It also describes the lessons learned by the authors as NBIA has acquired more than 20 image collections encompassing over 30 million images.

A 3D-Printed Patient-Specific Phantom for External Beam Radiation Therapy of Prostate Cancer.

This paper presents the design evolution, fabrication, and testing of a novel patient and organ-specific, 3D printed phantom for external beam radiation therapy of prostate cancer. In contrast to those found in current practice, this phantom can be used to plan and validate treatment tailored to an individual patient. It contains a model of the prostate gland with a dominant intraprostatic lesion, seminal vesicles, urethra, ejaculatory duct, neurovascular bundles, rectal wall, and penile bulb generated from a series of combined T2-weighted/dynamic contrast-enhanced magnetic resonance images. The iterative process for designing the phantom based on user interaction and evaluation is described. Using the CyberKnife System at Boston Medical Center a treatment plan was successfully created and delivered. Dosage delivery results were validated through gamma index calculations based on radiochromic film measurements which yielded a 99.8% passing rate. This phantom is a demonstration of a methodology for incorporating high-contrast magnetic resonance imaging into computed-tomography-based radiotherapy treatment planning; moreover, it can be used to perform quality assurance.

A combinatorial radiographic phenotype may stratify patient survival and be associated with invasion and proliferation characteristics in glioblastoma.

OBJECTIVE: Individual MRI characteristics (e.g., volume) are routinely used to identify survival-associated phenotypes for glioblastoma (GBM). This study investigated whether combinations of MRI features can also stratify survival. Furthermore, the molecular differences between phenotype-induced groups were investigated. METHODS: Ninety-two patients with imaging, molecular, and survival data from the TCGA (The Cancer Genome Atlas)-GBM collection were included in this study. For combinatorial phenotype analysis, hierarchical clustering was used. Groups were defined based on a cutpoint obtained via tree-based partitioning. Furthermore, differential expression analysis of microRNA (miRNA) and mRNA expression data was performed using GenePattern Suite. Functional analysis of the resulting genes and miRNAs was performed using Ingenuity Pathway Analysis. Pathway analysis was performed using Gene Set Enrichment Analysis. RESULTS: Clustering analysis reveals that image-based grouping of the patients is driven by 3 features: volume-class, hemorrhage, and T1/FLAIR-envelope ratio. A combination of these features stratifies survival in a statistically significant manner. A cutpoint analysis yields a significant survival difference in the training set (median survival difference: 12 months, p = 0.004) as well as a validation set (p = 0.0001). Specifically, a low value for any of these 3 features indicates favorable survival characteristics. Differential expression analysis between cutpoint-induced groups suggests that several immune-associated (natural killer cell activity, T-cell lymphocyte differentiation) and metabolism-associated (mitochondrial activity, oxidative phosphorylation) pathways underlie the transition of this phenotype. Integrating data for mRNA and miRNA suggests the roles of several genes regulating proliferation and invasion. CONCLUSIONS: A 3-way combination of MRI phenotypes may be capable of stratifying survival in GBM. Examination of molecular processes associated with groups created by this combinatorial phenotype suggests the role of biological processes associated with growth and invasion characteristics.

Population-based incremental interactive concept learning for image retrieval by stochastic string segmentations.

We propose a method for concept-based medical image retrieval that is a superset of existing semantic-based image retrieval methods. We conceive of a concept as an incremental and interactive formalization of the user's conception of an object in an image. The premise is that such a concept is closely related to a user's specific preferences and subjectivity and, thus, allows to deal with the complexity and content-dependency of medical image content. We describe an object in terms of multiple continuous boundary features and represent an object concept by the stochastic characteristics of an object population. A population-based incrementally learning technique, in combination with relevance feedback, is then used for concept customization. The user determines the speed and direction of concept customization using a single parameter that defines the degree of exploration and exploitation of the search space. Images are retrieved from a database in a limited number of steps based upon the customized concept. To demonstrate our method we have performed concept-based image retrieval on a database of 292 digitized X-ray images of cervical vertebrae with a variety of abnormalities. The results show that our method produces precise and accurate results when doing a direct search. In an open-ended search our method efficiently and effectively explores the search space.

Response assessment in clinical trials: implications for sarcoma clinical trial design.

Response assessment and design of clinical trials require careful consideration of many factors, especially as validated response criteria can ultimately lead to the approval of an anticancer agent. Current anatomic imaging criteria are difficult to apply for evaluation of certain types of tumors, including soft tissue sarcomas. The emergence of new molecular imaging techniques, such as 64-slice computed tomography scanners and dynamic contrast magnetic resonance imaging, provide complementary information to conventional anatomical imaging. Currently the U.S. National Cancer Institute and the U.S. Food and Drug Administration are aiming to revise existing response criteria based on the development of volumetric anatomic imaging for oncology. Reviewing existing and new approaches in the design of clinical trials will help to optimize the clinical development and evaluation of new therapies for sarcomas.

Blinded independent central review of progression-free survival in phase III clinical trials: important design element or unnecessary expense?

Progression-free survival is an important end point in advanced disease settings. Blinded independent central review (BICR) of progression in randomized clinical trials has been advocated to control bias that might result from errors in progression assessments. However, although BICR lessens some potential biases, it does not remove all biases from evaluations of treatment effectiveness. In fact, as typically conducted, BICRs may introduce bias because of informative censoring, which results from having to censor unconfirmed locally determined progressions. In this article, we discuss the rationale for BICR and different ways of implementing independent review. We discuss the limitations of these approaches and review published trials that report implementing BICR. We demonstrate the existence of informative censoring using data from a randomized phase II trial. We conclude that double-blinded trials with consistent application of measurement criteria are the best means of ensuring unbiased trial results. When such designs are not practical, BICR is not recommended as a general strategy for reducing bias. However, BICR may be useful as an auditing tool to assess the reliability of marginally positive results.

Measures of response: RECIST, WHO, and new alternatives.

RECIST (Response Evaluation Criteria in Solid Tumors) is a widely employed method introduced in 2000 to assess change in tumor size in response to therapy. The simplicity of the technique, however, contrasts sharply with the increasing sophistication of imaging instrumentation. Anatomically based imaging measurement, although supportive of drug development and key to some accelerated drug approvals, is being pressed to improve its methodologic robustness, particularly in the light of more functionally-based imaging that is sensitive to tissue molecular response such as fluorodeoxyglucose positron emission tomography. Nevertheless ready availability of computed tomography and magnetic resonance imaging machines largely assures anatomically based imaging a continuing role in clinical trials for the foreseeable future. Recent advances in image processing enabled by the computational power of modern clinical scanners open a considerable opportunity to characterize tumor response to therapy as a complement to image acquisition. Various alternative quantitative volumetric approaches have been proposed but have yet to gain wide acceptance by clinical and regulatory communities, nor have these more complex techniques shown incontrovertible evidence of greater reproducibility or predictive value of clinical events and outcome. Unless plans are created for clinical trials that incorporate the design needed to prove the added value and unique clinical utility of these novel approaches, any theoretical benefit of these more elaborate methods could remain unfulfilled.

Aortic intimal injuries from blunt trauma: resolution profile in nonoperative management.

OBJECTIVE: To provide preliminary data on the resolution profile of aortic intimal injuries treated nonoperatively and on the safety of nonoperative management of these injuries. METHODS: Five blunt trauma patients diagnosed by transesophageal echocardiography (TEE) with traumatic intimal injury of the aorta were assigned to nonoperative management. This included beta-blockade to maintain systolic blood pressure between 80 and 90 mm Hg and heart rate between 60 and 80 beats/min, serial TEE studies, and invasive monitoring in the intensive care unit. The evolution of injury, the effectiveness of nonoperative treatment, and the potential need for an operative intervention were monitored. RESULTS: The patients had a mean Injury Severity Score of 32 and sustained multiple associated thoracic and extrathoracic injuries. Aortic injuries were located at the level of the ligamentum arteriosum and in the descending aorta adjacent to the diaphragm in three and two patients, respectively. The mean size of injury was 12.5 mm (range, 5-20 mm) and a thrombus attached to the endothelium was present in three of the five patients. Complete resolution of injury occurred within 9.4 +/- 6.6 days (range, 3-19 days). All patients remained hemodynamically stable and adequately perfused. All demonstrated progressive resolution of their aortic intimal injuries. No complications related to the aortic injuries were identified during a mean follow-up of 16.8 months. CONCLUSION: This small series suggests that aortic intimal injuries smaller than 20 mm in hemodynamically stable patients treated with beta-blockade resolve within several days. This approach appears safe when monitored by serial TEE studies performed by experienced experts, and continuous invasive hemodynamic monitoring.

Tunnelling descent: a new algorithm for active contour segmentation of ultrasound images.

The presence of speckle in ultrasound images makes it hard to segment them using active contours. Speckle causes the energy function of the active contours to have many local minima, and the gradient descent procedure used for evolving the contour gets trapped in these minima. A new algorithm, called tunnelling descent, is proposed in this paper for evolving active contours. Tunnelling descent can jump out of many of the local minima that gradient descent gets trapped in. Experimental results with 70 short axis cardiac ultrasound images show that tunnelling descent has no trouble finding the blood-tissue boundary (the endocardium). This holds irrespective of whether tunnelling descent is initialized in blood or tissue.