TexRAD CT TEXTURE ANALYSIS: A NOVEL QUANTITATIVE IMAGING BIOMARKER IN ONCOLOGY

Transcription

1 TexRAD CT TEXTURE ANALYSIS: A NOVEL QUANTITATIVE IMAGING BIOMARKER IN ONCOLOGY

2 Quan>ta>ve Imaging Biomarkers Quan&ta&ve imaging is the extrac&on of quan&fiable features from medical images for the assessment of normal or the severity, degree of change, or status of a disease, injury, or chronic condi&on rela&ve to normal. h#p://

3 Quan>ta>ve CT- based Biomarkers in Oncology! Tumor Size! Tumor A#enua?on! Tumor Perfusion! Tumor Heterogeneity

4 Size Criteria in Cancer Imaging T & N Staging Response Evalua4on Before Therapy After Therapy Years since CT >20% increase = Progressive Disease >30% decrease = Response

5 How repeatable is RECIST? Mean diameter 4.1 cm (range: cm) 2 readers Single reader Progressive Disease (>20%) 29.75% ( %) Response (>30%) 13.75% ( %) 9.5% ( %) 3% (0-5%) Erasmus JJ et al. J Clin Oncol 2003;21:2574

6 CT AYenua>on & Tumor Response: Gastro- Intes>nal Stromal Tumors (GIST) Size Criteria Size & AYenua>on Ima4nib Therapy: Choi, H. et al. J Clin Oncol; 25:

7 Perfusion CT & survival in esophageal squamous cell carcinoma Perfusion <50 ml/min/100g predicts poor survival Responder: Perf 102 ml/min/100g Non- responder: Perf 32 ml/min/100g Hayano Y et al. Oncol Rep 2007;18:901-8

8 Vascular Heterogeneity NORMAL TUMOR Long pathways (high resistance) Flow voids Hypoxia Vascular hot spots (low resistance)

9 Biological Impact of Tumor Heterogeneity Adverse tumor microenvironment Hypoxic voids and acidic milieu Increased invasion and metastasis Impaired delivery of chemotherapeu?c agents Increased cellular resistance to chemotherapy & radiotherapy Inhibi?on of immune responses

10 Quan>fying Tumor Heterogeneity with CT Assess distribu?on of gray- levels with Texture Analysis Visual assessments of heterogeneity tend to reflect radiologists impression of image quality CT texture reported to reflect tumor vasculariza?on (modelling studies)

11 CTTA Aims to Highlight Biological Heterogeneity Image filtra?on (Laplacian of Gaussian) Tune filter to appropriate scale (filter value) Fine texture = noise Medium/coarse texture: biologically important Ganeshan B et al Academic Radiology, 2007; 14(12):

12 Quan>fying Heterogeneity Sta?s?cal measures Uniformity uniform distribu&on of gray- levels, probabilis&c value varying between 0 - non- uniform and 1 - uniform Entropy measures irregularity or complexity, indicated by a higher value Skogen K et al In Cancer Imaging, ICIS 2011, Copenhagen, Denmark

13 Quan>fying Heterogeneity Histogram analysis Histogram of Coarse Filtered Lesion Image No of Pixels Filtered Pixel Intensity Propor?on/mean of all/posi?ve pixels - loca&on of distribu&on Standard devia?on scale of the distribu&on Skogen K et al In Cancer Imaging, ICIS 2011, Copenhagen, Denmark

14 Quan>fying Heterogeneity Histogram analysis Skewness symmetry of the distribu&on may reflect structures Kurtosis poin&ness of the distribu&on may reflect vessels Skogen K et al In Cancer Imaging, ICIS 2011, Copenhagen, Denmark

15 Quan>fying Heterogeneity Histogram analysis vs Sta?s?cal measures Histogram measures may have the advantage of reflec?ng structures in a region They compensate for the standard devia?on and have the poten?al to be less sensi?ve to image noise and region size Skogen K et al In Cancer Imaging, ICIS 2011, Copenhagen, Denmark

16 Tumor Heterogeneity as an Imaging Correlate for Hypoxia in NSCLC pimonidazole Ganeshan B et al Radiological Society of North America (RSNA) 2010 h_p://rsna2010.rsna.org/search/search.cfm?ac4on=add&filter=author&value=85485

17 Tumor Heterogeneity is an independent predictor of survival in NSCLC Study 1 Kaplan- Meier survival curves for NSCLC pa?ents with lung lesions separated by (A) CT Texture analysis (B) SUV from PET and (C) PET stage. Survival curves were significantly different for CT texture analysis (p<0.002), PET stage (p<0.005) but not for SUV. Ganeshan B et al European Radiology 2011; [In press]

18 Tumor Heterogeneity is an independent predictor of survival in NSCLC Study 2 Tumor Characteris>c Hazard Ra>o 95% Confidence Limits p- value Heterogeneity (CTTA) Clinical Stage Permeability No significant interac?on was observed between the above significant predictors and treatment on overall pa?ent survival Courtesy Prof Ashley Groves, INM, University College London, UK

19 Tumor Heterogeneity correlates with glucose uptake in esophageal cancer Ganeshan B et al Clinical Radiology 2011; [Epub ahead of print]

20 Tumor Heterogeneity is an independent predictor of survival in esophageal cancer Kaplan- Meier survival curves for oesophageal pa?ents separated by (A) CT Texture analysis, (B) stage and (C) SUV from PET. Survival curves were significantly different for CT texture analysis (p=0.0006), stage (p=0.023) and SUV (p=0.0032). Ganeshan B et al Clinical Radiology 2011; [Epub ahead of print]

21 Tumor Heterogeneity & Treatment Response: Renal Cancer DISEASE- FREE SURVIVAL PRE Size & A_enua4on POST Heterogeneity Goh V et al Radiology 2011; Aug 3 [Epub]

22 Hepa>c Heterogeneity and Survival in Colorectal Cancer Fine Medium Coarse Miles KA et al Radiology 2009;250:444-52

23 Economic Analysis of CTTA in Colorectal Cancer Surveillance Cancer pa>ents for surveillance Full Surveillance (Baseline Strategy) Imaging Biomarker (Comparator Strategy) M High Risk Low Risk Strategy High Risk Low Risk Full Surveillance Reduced Surveillance M M Progression Free p2 Undetected Recurrence Markov Model p1 p3 Death Full Surveillance Reduced A CEA CT CEA CT 3 monthly Yearly 3 monthly Yearly Yearly p4 TM p4 IM Detected Recurrence p5 3 monthly cycle Reduced B 6 monthly 18 monthly

24 Impact of CTTA- based Surveillance Strategies Reduc?ons in frequency of CEA ± CT in low risk Minimal increase in mortality at 5 years 74.2% versus 73.9% Minimal reduc?on in average life expectancy days Cost savings: 1248 per pa?ent Cost- effec?veness Net Monetary Benefit: 427 per pa?ent (based on a willingness to pay 30,000 per life year) Miles KA et al European Society of Radiology 2011, Vienna, Austria

25 CT Texture Analysis (CTTA) in Cancer Care Performance Status Serum Markers Symptoms Serum Markers Pathological Markers Disease Severity Treatment Risk of Recurrence Surveillance Staging TexRAD RECIST TexRAD

26 Evolu>on of TexRAD Ini?al Research & Development (R&D) was undertaken by researchers engineers and clinicians at Brighton & Sussex Medical School, University of Sussex Commercialisa?on of TexRAD sooware is being undertaken by TexRAD Ltd Come and visit us for a sojware demonstra>on and discussion at our Booth LL- QRR3002 in the Quan>ta>ve Imaging Reading Room

27 Publica>ons Patent B. Ganeshan, K.A. Miles, R.C.D. Young, C.R. Chatwin. Method, apparatus and computer program for analysing medical image data. Patent applied for (Interna&onal Publica&on Number WO 2008 / ). 14 Peer- review publica?ons 24 Conference proceedings