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Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI

Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI. Dr Anwar Padhani anwar.padhani@paulstrickland-scannercentre.co.uk Mount Vernon Cancer Centre London. Montreal November 2004. Mount Vernon Cancer Centre & Gray Cancer Institute. Royal Marsden Hospital &

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Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI

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  1. Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI Dr Anwar Padhani anwar.padhani@paulstrickland-scannercentre.co.uk Mount Vernon Cancer Centre London Montreal November 2004

  2. Mount Vernon Cancer Centre & Gray Cancer Institute Royal Marsden Hospital & Institute of Cancer Research Jane Taylor, James Stirling Gordon Rustin, Sue Galbraith, Kate Lankester, Andreas Makris, Mei-Lin Ah-See Ross Maxwell, Gill Tozer Janet Husband and Martin Leach, David Collins, James d’Arcy, Simon Walker-Samuel, Carmel Hayes, Geoff Parker, John Suckling, Ian Judson I acknowledge other contributors who have provided additional materials of their work in support of this lecture Dr H Choi, MD Andersen Cancer Cemtre, Houston Dr WE Reddick, St Jude Children Research Hospital, Memphis

  3. Talk outline • Dynamic MRI – biological basis & quantification • Illustrate utility of dynamic MRI to assess benefit of therapy in patients with bone sarcomas • Predict response to neoadjuvant chemotherapy • Assess activity of residual disease • Biomarker for assessing effects of treatment with antiangiogenesis/vascular targeting drugs • Biomedical challenges in clinical implementation specific to patients with sarcomas Perfusion MR imaging of extracranial tumor angiogenesis. A Dzik-Jurasz, AR Padhani. Top Magn Reson Imaging. 2004;15(1):41-57.

  4. Talk outline • Dynamic MRI – biological basis & quantification • Illustrate utility of dynamic MRI to assess benefit of therapy in patients with bone sarcomas • Predict response to neoadjuvant chemotherapy • Assess activity of residual disease • Biomarker for assessing effects of treatment with antiangiogenesis/vascular targeting drugs • Biomedical challenges in clinical implementation specific to patients with sarcomas Perfusion MR imaging of extracranial tumor angiogenesis. A Dzik-Jurasz, AR Padhani. Top Magn Reson Imaging. 2004;15(1):41-57.

  5. Dynamic contrast enhanced MRI (DCE-MRI) • Technique where enhancement of a tissue or organ is continuously monitored using MRI after bolus IV contrast medium • Low molecular weight contrast media (<1 kDa) • Diffuse into extravascular-extracellular space (does not cross cell membranes) • Experiment lasts a few minutes 7 minutes Haemangiopericytoma Data courtesy of David Collins and Ian Judson, Institute of cancer Research, London

  6. Basis of dynamic contrast enhanced MRI

  7. T2*W DCE-MRI of Mixed Mullerian Tumour Typical acquisition 1-2 mins

  8. T1W DCE-MRI of Mixed Mullerian Tumour Typical acquisition 5-8 mins

  9. T2*W versus T1W DCE-MRI

  10. Evaluation of signal enhancement during DCE-MRI • Qualitative - shape of signal intensity (SI) data curve • Semi-quantitative - indices that describe one or more parts of SI or [Gd] curves • Upslope gradient, max amplitude, washout rate or area under curve at a fixed time point • True quantitative - indices from contrast medium concentration changes using pharmacokinetic modelling

  11. kep(min-1) = 0.5 kep(min-1) = 8.9 kep(min-1) = 3.4 Patterns of enhancement on T1W DCE-MRI and histological correlates Type I (semi-necrotic with reactive changes) Type II (viable tumour) Type III (rapidly proliferating tumour edge) (Taylor and Reddick, Adv Drug Del Rev, 2000)

  12. Pharmacokinetic modelling of T1W DCE-MRI data • Transfer constant (Ktrans) • Extracellular leakage space (ve) • Rate constant (kep) Not today Modified from Tofts 1995

  13. Quantitative analysis with pharmacokinetic modelling • Advantages • Whole curve shape is analysed • Biologically relevant physiological parameters • Independent of scanner strength, manufacturer and imaging routines • Enables valid comparisons of serial measurements and data exchange between different imaging centres • Disadvantages • Data acquisition and analysis is more complex • Lack of commercial software for analysis • Models may not fit the data observed

  14. Clinical indications for DCE-MRI in patients with musculoskeletal lesions • To improve characterisation of lesions* • Monitoring response to treatment • Conventional treatments (chemotherapy/physical treatments) • Novel biological treatments including antiangiogenic/vascular targeting drugs • Assess activity of residual disease after definitive treatment *Ma LD, et al. Radiology 1997; 202(3):739-44 *van der Woude HJ et al. Radiology 1998; 208(3):821-8 *Verstraete KL, Radiology. 1994; 192(3):835-43

  15. Importance of predicting early tumour response to chemotherapy • If pathological response can be reliably predicted after a few cycles of neoadjuvant chemotherapy • Treatment regimen could be adjusted (early surgery, cryotherapy, isolated limb perfusion etc) • Pathological response rates may be improved • Changing treatment could increase expense and exposes patients to greater toxicity There is very little objective data that DCE-MRI can predict responses early after stating neoadjuvant chemotherapy

  16. Good response to treatment (99% necrosis) Baseline 2 months on treatment SUV 13.0 FDG-PET scans Pre-operative SUV 2.4 2 A Courtesy of Dr H Choi, MD Andersen Cancer Center, Houston

  17. Correlation of DCE-MRI and necrotic fraction after chemotherapy Dyke JP, et al. Radiology 2003; 228:271-278

  18. Tumors < 56 cm2 100 kep < 1.167 min-1 80 kep 1.167 min-1 Disease-free Survival (%) 60 40 20 0 1 2 3 5 6 4 0 Tumors > 56 cm2 100 80 kep < 1.167 min-1 60 kep> 1.167 min-1 40 Disease-free Survival (%) P = 0.05 20 0 0 1 2 3 5 6 4 Year Prognostic value of DCE-MRI in osteosarcomas Change in kep as a function of pre-treatment value. Higher permeability at presentation results in greater decreases with therapy 2 ) -1 0 During Therapy (min -2 -4 ep k -6 0 1 2 3 4 5 6 7 k at Presentation (min-1) ep Disease free survival for 31 patients stratified by tumour size and DCE-MRI after 9 weeks of Rx; Reddick WE, et al. Cancer 2001; 91:2230-2237

  19. Tumors < 56 cm2 100 kep < 1.167 min-1 80 kep 1.167 min-1 Disease-free Survival (%) 60 40 20 0 1 2 3 5 6 4 0 Tumors > 56 cm2 100 80 kep < 1.167 min-1 60 kep> 1.167 min-1 40 Disease-free Survival (%) P = 0.05 20 0 0 1 2 3 5 6 4 Year Prognostic value of DCE-MRI in osteosarcomas Change in kep as a function of pre-treatment value. Higher permeability at presentation results in greater decreases with therapy 2 ) -1 0 During Therapy (min -2 -4 ep k -6 0 1 2 3 4 5 6 7 k at Presentation (min-1) ep Disease free survival for 31 patients stratified by tumour size and DCE-MRI after 9 weeks of Rx; Reddick WE, et al. Cancer 2001; 91:2230-2237

  20. Poor access to contrast before treatment Baseline SUV 5.9 FDG-PET scans Poor response to treatment (75% necrosis) SUV 8.3 Pre-operative Courtesy of Dr H Choi, MD Andersen Cancer Center, Houston

  21. Drugs targeting tumour neovasculature Vascular targeting drugs •  Permeability •  rBV • or  rBF Probably depends on drug duration and dose Anti-VEGF drugs  Permeability  rBV rBF

  22. Time course of Combretastatin effects on microvasculature 2 hours post CA4P PreRx Window chamber view P22 Carcinosarcoma IAP - radiolabelled iodoantipyrine B Vojnovic and G Tozer, Gray Cancer Institute

  23. Morphological & kinetic changes After 1st dose of CA4P (52mg/m2) 24 hrs Pre 4 hrs Post

  24. DLT 114 mg/m2 Biologically active dose 52 mg/m2 MTD 88 mg/m2 Galbraith SM, et al. J Clin Oncol – 2003;21:2831-42.

  25. Galbraith SM, et al. J Clin Oncol – 2003;21:2831-42

  26. Phase I goals and DCE-MRI achievements in the CA4P study Galbraith SM, et al. J Clin Oncol – 2003;21:2831-42

  27. 160 • 25 patients with metastatic colon cancer evaluated at baseline, on day 2 and 28 140 120 100 80 Ki (% Baseline) 60 40 20 0 50 300 500 750 1000 1200 Dose (mg) Dose response in Ki for PTK787/ZK in colorectal cancer on Day 2 SEM bars, all colorectal liver metastases No maximum tolerated dose was reached Figure courtesy of A Thomas, B Morgan, Leicester Royal Infirmary Morgan, B., et al., J Clin Oncol, 2003. 21(21): p. 3955-3964.

  28. Phase I goals and DCE-MRI achievements in the PTK787/ZK study Morgan, B., et al., J Clin Oncol, 2003. 21(21): p. 3955-3964.

  29. Conclusions • Dynamic MRI provides unique information on the vascular characteristics of tumours • DCE-MRI can predict extent of histological response to chemotherapy in patients with osteosarcomas/Ewing tumours • Intriguingly, DCE-MRI may inform on drug access (? predict responsiveness) and patient prognosis • Acts as a biomarker that provides pharmacodynamic (PD) information in early trials of antivascular drug and should be used for evaluating combination therapies in sarcomas Dynamic MR imaging of tumor perfusion: approaches and biomedical challenges. DJ Collins, AR Padhani. IEEE Engineering in Medicine and Biology Magazine 2004

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