scholarly journals Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers

Author(s):  
M. A. McAteer ◽  
J. P. B. O’Connor ◽  
D. M. Koh ◽  
H. Y. Leung ◽  
S. J. Doran ◽  
...  

SummaryThe National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies.

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Author(s):  
Kostas Marias

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.


2021 ◽  
pp. 174077452098193
Author(s):  
Nancy A Obuchowski ◽  
Erick M Remer ◽  
Ken Sakaie ◽  
Erika Schneider ◽  
Robert J Fox ◽  
...  

Background/aims Quantitative imaging biomarkers have the potential to detect change in disease early and noninvasively, providing information about the diagnosis and prognosis of a patient, aiding in monitoring disease, and informing when therapy is effective. In clinical trials testing new therapies, there has been a tendency to ignore the variability and bias in quantitative imaging biomarker measurements. Unfortunately, this can lead to underpowered studies and incorrect estimates of the treatment effect. We illustrate the problem when non-constant measurement bias is ignored and show how treatment effect estimates can be corrected. Methods Monte Carlo simulation was used to assess the coverage of 95% confidence intervals for the treatment effect when non-constant bias is ignored versus when the bias is corrected for. Three examples are presented to illustrate the methods: doubling times of lung nodules, rates of change in brain atrophy in progressive multiple sclerosis clinical trials, and changes in proton-density fat fraction in trials for patients with nonalcoholic fatty liver disease. Results Incorrectly assuming that the measurement bias is constant leads to 95% confidence intervals for the treatment effect with reduced coverage (<95%); the coverage is especially reduced when the quantitative imaging biomarker measurements have good precision and/or there is a large treatment effect. Estimates of the measurement bias from technical performance validation studies can be used to correct the confidence intervals for the treatment effect. Conclusion Technical performance validation studies of quantitative imaging biomarkers are needed to supplement clinical trial data to provide unbiased estimates of the treatment effect.


2019 ◽  
Author(s):  
Ying V. Liu ◽  
Simrat Sodhi ◽  
Gilbert Xue ◽  
Derek Teng ◽  
Dzhalal Agakishiev ◽  
...  

AbstractPurposeShort-term improvements in retinal anatomy are known to occur in preclinical models of photoreceptor transplantation. However, correlative changes over the long term are poorly understood. We aimed to develop a quantifiable imaging biomarker grading scheme, using non-invasive multimodal confocal scanning laser ophthalmoscopy (cSLO) imaging, to enable serial evaluation of photoreceptor transplantation over the long term.MethodsYellow-green fluorescent microspheres were transplanted into the vitreous cavity and/or subretinal space of C57/BL6J mice. Photoreceptor cell suspensions or sheets from rhodopsin-green fluorescent protein mice were transplanted subretinally, into either NOD.CB17-Prkdcscid/J or C3H/HeJ-Pde6brd1 mice. Multimodal cSLO imaging was performed serially for up to three months after transplantation. Imaging biomarkers were scored, and a grade was defined for each eye by integrating the scores. Image grades were correlated with immunohistochemistry (IHC) data.ResultsMultimodal imaging enabled the extraction of quantitative imaging biomarkers including graft size, GFP intensity, graft length, on-target graft placement, intra-graft lamination, hemorrhage, retinal atrophy, and peri-retinal proliferation. Migration of transplanted material was observed. Changes in biomarker scores and grades were detected in 13/16 and 7/16 eyes, respectively. A high correlation was found between image grades and IHC parameters.ConclusionsSerial evaluation of multiple imaging biomarkers, when integrated into a per-eye grading scheme, enabled comprehensive tracking of longitudinal changes in photoreceptor cell grafts over time. The application of systematic multimodal in vivo imaging could be useful in increasing the efficiency of preclinical retinal cell transplantation studies in rodents and other animal models.


2020 ◽  
Vol 13 (9) ◽  
Author(s):  
Tom Kai Ming Wang ◽  
Mnahi Bin Saeedan ◽  
Nicholas Chan ◽  
Nancy A. Obuchowski ◽  
Nabin Shrestha ◽  
...  

Background: Cardiac computed tomography (CT) is emerging as an adjunctive modality to echocardiography in the evaluation of infective endocarditis (IE) and surgical planning. CT studies in IE have, however, focused on its diagnostic rather than prognostic utility, the latter of which is important in high-risk diseases like IE. We evaluated the associations between cardiac CT and transesophageal echocardiography (TEE) findings and adverse outcomes after IE surgery. Methods: Of 833 consecutive patients with surgically proven IE during May 1, 2014 to May 1, 2019, at Cleveland Clinic, 155 underwent both preoperative ECG-gated contrast-enhanced CT and TEE. Multivariable analyses were performed to identify CT and TEE biomarkers that predict adverse outcomes after IE surgery, adjusting for EuroSCORE II (European System for Cardiac operative Risk Evaluation II). Results: CT and TEE were positive for IE in 123 (75.0%) and 124 (75.6%) of patients, respectively. Thirty-day mortality occurred in 3 (1.9%) patients and composite mortality or morbidities in 72 (46.5%). Pseudoaneurysm or abscess detected on TEE was the only imaging biomarker to show independent association with composite mortality or morbidities in-hospital, with odds ratio (95% CI) of 3.66 (1.76–7.59), P =0.001. There were 17 late deaths, and both pseudoaneurysm or abscess detected on CT and fistula detected on CT were the only independent predictors of total mortality during follow-up, with hazards ratios (95% CI) of 3.82 (1.25–11.7), P <0.001 and 9.84 (1.89–51.0), P =0.007, respectively. Conclusions: We identified cardiac CT and TEE features that predicted separate adverse outcomes after IE surgery. Imaging biomarkers can play important roles incremental to conventional clinical factors for risk stratification in patients undergoing IE surgery.


2020 ◽  
Vol 61 (12) ◽  
pp. 1708-1716
Author(s):  
Bruno R Tegel ◽  
Steffen Huber ◽  
Lynn J Savic ◽  
MingDe Lin ◽  
Bernhard Gebauer ◽  
...  

Background The prognosis of patients with renal cell carcinoma (RCC) depends greatly on the presence of extra-renal metastases. Purpose To investigate the value of total tumor volume (TTV) and enhancing tumor volume (ETV) as three-dimensional (3D) quantitative imaging biomarkers for disease aggressiveness in patients with RCC. Material and Methods Retrospective, HIPAA-compliant, IRB-approved study including 37 patients with RCC treated with image-guided thermal ablation during 2007–2015. TNM stage, RENAL Nephrometry Score, largest tumor diameter, TTV, and ETV were assessed on cross-sectional imaging at baseline and correlated with outcome measurements. The primary outcome was time-to-occurrence of extra-renal metastases and the secondary outcome was progression-free survival (PFS). Correlation was assessed using a Cox regression model and differences in outcomes were shown by Kaplan–Meier plots with significance and odds ratios (OR) calculated by Log-rank test/generalized Wilcoxon and continuity-corrected Woolf logit method. Results Patients with a TTV or ETV > 5 cm3 were more likely to develop distant metastases compared to patients with TTV (OR 6.69, 95% confidence interval [CI] 0.33–134.4, P=0.022) or ETV (OR 8.48, 95% CI 0.42–170.1, P=0.016) < 5 cm3. Additionally, PFS was significantly worse in patients with larger ETV ( P = 0.039; median PFS 51.87 months vs. 69.97 months). In contrast, stratification by median value of the established, caliper-based measurements showed no significant correlation with outcome parameters. Conclusion ETV, as surrogate of lesion vascularity, is a sensitive imaging biomarker for occurrence of extra-renal metastatic disease and PFS in patients with RCC.


2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 180-180
Author(s):  
Glenn Liu ◽  
Scott Perlman ◽  
Tim Perk ◽  
Stephanie Harmon ◽  
Kelly Simmons ◽  
...  

180 Background: CRPC is frequently associated with the development of osseous metastases. While imaging allows treatment response determination in soft tissue metastasis, its application in bony metastasis is limited to staging. Methods: QTBI is an innovative tool that allows extraction of comprehensive functional information in all osseous metastases, as well as treatment response in individual lesions, using 18F-Sodium Fluoride (NaF) PET/CT. We completed a multi-center trial assessing the performance characteristics (test-retest) and responsiveness of QTBI as an imaging biomarker of treatment response in men with metastatic CRPC to bone treated with either a taxane-based or androgen-signaling pathway directed therapy. Results: 54 patients have been enrolled from three academic centers. Potential imaging biomarkers of treatment response have been identified. Here we present initial data regarding the inter-lesional response heterogeneity and implications. Conclusions: Changes in SUVmax, SUVtotal, and SUVmean reflect quantifiable PET measurements that are complementary, but may have different meaning depending on the treatment administered (cytotoxic vs cytostatic). Relying on one measure alone can be misleading, particularly when assessing treatment response. For example, some lesions may experience a decrease in SUVmax, while simultaneously having an increase in SUVtotal. This implies that the therapy decreased the max functional activity of the lesion, but the overall functional burden of the lesion increased analogous to “slowing down” progression. This is in contrast with lesions that decrease (increase) in both SUVmax and SUVtotal, which would imply decreased activity and burden (increased activity and burden). We will show data representative of the above along with clinical outcomes in support of this conclusion, as well as the implications of treatment response heterogeneity in the clinical outcome. In summary, QTBI provides a unique tool in understanding the dynamics of treatment response, allowing newer trial designs that can explore combination, sequence, and the issue of continuing treatment beyond progression with existing therapies. Clinical trial information: NCT01516866.


Theranostics ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 2603-2620 ◽  
Author(s):  
Bastian Zinnhardt ◽  
Maximilian Wiesmann ◽  
Lisa Honold ◽  
Cristina Barca ◽  
Michael Schäfers ◽  
...  

2021 ◽  
Author(s):  
Biao Xiang ◽  
Matthew R. Brier ◽  
Manasa Kanthamneni ◽  
Jie Wen ◽  
Abraham Z. Snyder ◽  
...  

Abstract Background: Imaging biomarkers of progressive MS are needed. Quantitative gradient recalled echo (qGRE) MRI technique allows evaluation of tissue damage associated with microstructural damage in multiple sclerosis (MS). Objective: To evaluate qGRE-derived R2t* as an imaging biomarker of MS disease progression as compared to atrophy and lesion burden. Methods: Twenty-three non-relapsing progressive MS (PMS), twenty-two relapsing-remitting MS (RRMS) and eighteen healthy control participants were imaged with qGRE at 3T. PMS subjects were imaged and neurologically assessed every nine months over five sessions. In each imaging session, lesion burden, atrophy and R2t* in cortical grey matter (GM), deep GM, normal-appearing white matter (NAWM) were measured. Results: R2t* reductions correlated with neurological impairment cross-sectionally and longitudinally. PMS patients with clinically defined disease progression showed significantly faster decrease of R2t* in NAWM and deep GM compared with the clinically stable PMS group. Importantly, tissue damage measured by R2t* outperformed lesion burden and atrophy as a biomarker of progression during the study period. Conclusion: Clinical impairment and progression correlated with accumulating R2t*-defined microstructural tissue damage in deep GM and NAWM. qGRE-derived R2t* is a potential imaging biomarker of MS progression.


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