Vicky Goh

Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?

BackgroundTumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical imagesMethodsImage texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods.ResultsEarly evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice.ConclusionThis review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging.Teaching Points• Tumor spatial heterogeneity is an important prognostic factor.• Image texture analysis is an approach of quantifying heterogeneity.• Different methods can be applied, including statistical-, model-, and transform-based methods.• Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment.

Are Pretreatment 18F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy?

There is evidence in some solid tumors that textural features of tumoral uptake in 18F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non–small cell lung cancer (NSCLC). Methods: Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment 18F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis. Results: Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P = 0.004) and higher contrast (mean, 0.11 vs. 0.044; P = 0.002) and busyness (mean, 0.76 vs. 0.37; P = 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan–Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P = 0.003; 12.6 vs. 25.8 mo, P = 0.002; and 12.9 vs. 20.5 mo, P = 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P = 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P = 0.015, and median not reached vs. 24 mo, P = 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P = 0.01, and median not reached vs. 24 mo, P = 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters. Conclusion: In NSCLC, baseline 18F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.

Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis

Abstract18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is now routinely used in oncological imaging for diagnosis and staging and increasingly to determine early response to treatment, often employing semiquantitative measures of lesion activity such as the standardized uptake value (SUV). However, the ability to predict the behaviour of a tumour in terms of future therapy response or prognosis using SUVs from a baseline scan prior to treatment is limited. It is recognized that medical images contain more useful information than may be perceived with the naked eye, leading to the field of “radiomics” whereby additional features can be extracted by computational postprocessing techniques. In recent years, evidence has slowly accumulated showing that parameters obtained by texture analysis of radiological images, reflecting the underlying spatial variation and heterogeneity of voxel intensities within a tumour, may yield additional predictive and prognostic information. It is hoped that measurement of these textural features may allow better tissue characterization as well as better stratification of treatment in clinical trials, or individualization of future cancer treatment in the clinic, than is possible with current imaging biomarkers. In this review we focus on the literature describing the emerging methods of texture analysis in 18FDG PET/CT, as well as other imaging modalities, and how the measurement of spatial variation of voxel grey-scale intensity within an image may provide additional predictive and prognostic information, and postulate the underlying biological mechanisms.

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

IntroductionBreast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.MethodsMore than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer ‘stem’ cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.ResultsThe 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.ConclusionsWith resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

Assessment of Response to Tyrosine Kinase Inhibitors in Metastatic Renal Cell Cancer: CT Texture as a Predictive Biomarker

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.

Anal cancer: ESMO-ESSO-ESTRO Clinical Practice Guidelines for diagnosis, treatment and follow-up

Squamous cell carcinoma of the anus (SCCA) is a rare cancer but its incidence is increasing throughout the world, and is particularly high in the human immunodeficiency virus positive (HIVþ) population. A multidisciplinary approach is mandatory (involving radiation therapists, medical oncologists, surgeons, radiologists and pathologists). SCCA usually spreads in a loco-regional manner within and outside the anal canal. Lymph node involvement at diagnosis is observed in 30%e40% of cases while systemic spread is uncommon with distant extrapelvic metastases recorded in 5%e8% at onset, and rates of metastatic progression after primary treatment between 10 and 20%. SCCA is strongly associated with human papilloma virus (HPV, types 16e18) infection. The primary aim of treatment is to achieve cure with loco-regional control and preservation of anal function, with the best possible quality of life. Treatment dramatically differs from adenocarcinomas of the lower rectum. Combinations of 5FU-based chemoradiation and other cytotoxic agents (mitomycin C) have been established as the standard of care, leading to complete tumour regression in 80%e90% of patients with locoregional failures in the region of 15%. There is an accepted role for surgical salvage. Assessment and treatment should be carried out in specialised centres treating a high number of patients as early as possible in the clinical diagnosis. To date, the limited evidence from only 6 randomised trials [1,2,3,4,5,6,7], the rarity of the cancer, and the different behaviour/natural history depending on the predominant site of origin, (the anal margin, anal canal or above the dentate line) provide scanty direction for any individual oncologist. Here we aim to provide guidelines which can assist medical, radiation and surgical oncologists in the practical management of this unusual cancer. 2014 Elsevier Ltd. All rights reserved.

Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole-Tumor Texture Analysis : Contrast-enhanced CT Texture as a Biomarker of 5-year Survival

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.

Non–Small Cell Lung Cancer: Histopathologic Correlates for Texture Parameters at CT

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.

Current status and guidelines for the assessment of tumour vascular support with dynamic contrast-enhanced computed tomography

AbstractDynamic contrast-enhanced computed tomography (DCE-CT) assesses the vascular support of tumours through analysis of temporal changes in attenuation in blood vessels and tissues during a rapid series of images acquired with intravenous administration of iodinated contrast material. Commercial software for DCE-CT analysis allows pixel-by-pixel calculation of a range of validated physiological parameters and depiction as parametric maps. Clinical studies support the use of DCE-CT parameters as surrogates for physiological and molecular processes underlying tumour angiogenesis. DCE-CT has been used to provide biomarkers of drug action in early phase trials for the treatment of a range of cancers. DCE-CT can be appended to current imaging assessments of tumour response with the benefits of wide availability and low cost. This paper sets out guidelines for the use of DCE-CT in assessing tumour vascular support that were developed using a Delphi process. Recommendations encompass CT system requirements and quality assurance, radiation dosimetry, patient preparation, administration of contrast material, CT acquisition parameters, terminology and units, data processing and reporting. DCE-CT has reached technical maturity for use in therapeutic trials in oncology. The development of these consensus guidelines may promote broader application of DCE-CT for the evaluation of tumour vascularity. Key Points • DCE-CT can robustly assess tumour vascular support • DCE-CT has reached technical maturity for use in therapeutic trials in oncology • This paper presents consensus guidelines for using DCE-CT in assessing tumour vascularity

Effect of nitric-oxide synthesis on tumour blood volume and vascular activity: a phase I study

BACKGROUND Nitric oxide has been implicated in tumour angiogenesis and in the maintaining of vasodilator tone of tumour blood vessels. The tumour vascular effects of inhibition of nitric-oxide synthesis have not been investigated in patients with cancer. METHODS Seven women and 11 men (12 with non-small-cell lung cancer, five prostate cancer, and one cervical cancer) were recruited onto a phase I dose-escalation study and received a single dose of the nitric oxide synthase inhibitor, N-nitro-L-arginine (L-NNA). Dose escalation was done by a modified Fibonacci scale with three patients at each dose level, starting with 0.1 mg/kg. Changes in dynamic contrast-enhanced CT measures of tumour relative blood volume and transfer constant (K) were measured at 1 h and 24 h after L-NNA administration. FINDINGS In the 18 patients, toxic effects were self-limiting cardiovascular changes: three patients had Common Toxicity Criteria version 2.0 grade 1 hypertension; two had grade 1 sinus bradycardia; and one had grade 1 palpitation. L-NNA area under the curve (AUC) increased linearly with dose from 163 micromol min(-1) L(-1) at 0.1 mg/kg L-NNA to 2150 micromol min(-1) L(-1) at 0.9 mg/kg L-NNA. In eight patients that underwent dynamic CT scanning, tumour blood volume decreased 1 h after L-NNA treatment (mean 42.9% [range 12.0-62.1]; paired t test p=0.0070), which was sustained for up to 24 h (mean 33.9% [range 6.5-64.9]; p=0.035). This decrease in blood volume was associated with an increase in the number of non-perfused pixels from 7.3% (SD 5.5) at baseline to 25.1% (15.3; p=0.0089) at 1 h, and 18.2% (12.9; p=0.050) at 24 h. There was a significant correlation between L-NNA plasma AUC and the reduction in tumour blood volume at 24 h after L-NNA (r=0.83; p=0.010). INTERPRETATION We have shown in vivo in patients with cancer that nitric oxide has a role in maintaining tumour blood supply, and we provide early clinical evidence that inhibition of nitric-oxide synthesis has tumour antivascular activity.