Adaptive RT in Rectal Cancer: Superior to 3D-CRT? A Simple Question, a Complex Answer

Strahlentherapie und Onkologie

Supplement Article

Adaptive RT in Rectal Cancer: Superior to 3D-CRT? A Simple Question, a Complex Answer Karin Haustermans1, Sarah Roels1, Jan Verstraete1, Tom Depuydt1, Pieter Slagmolen2

Introduction Although the introduction of modern treatment techniques such as Total Mesorectal Excision (TME) and combined preoperative chemoradiation has strongly reduced local recurrence rates, there is still room for improvement in treatment in high-risk patients (T3–T4, lymph node positive) [1]. In these selected patients, progress may be achieved with higher preoperative doses and by integrating novel chemotherapeutic and molecular targeted agents [2, 3, 4]. Better treatment techniques such as adaptive radiotherapy may ultimately lead to less local recurrences and more sphincter and even organ preservation. But before adaptive radiation can be introduced into clinical routine several steps have to be taken going from target definition over target localisation and positioning to re-planning and cumulative dosimetry. Target Definition Intensity-modulated radiotherapy (IMRT) and intensity-modulated arc therapy (IMAT) can be used to spare the small bowel around which the clinical target volume (CTV) is located in a horseshoe shape [5]. However, because these techniques introduce dose gradients close to the planning target volume (PTV), proper definition and delineation of the CTV is required to avoid under-dosage of regions that could possibly harbour cancer cells. Based on an extensive review of the literature reporting on the incidence and predominant location of local recurrences [6] and the distribution of lymphatic spread in rectal cancer, we defined guidelines for CTV delineation. We propose to include the primary tumor, the mesorectal subsite, and the posterior pelvic subsite in the CTV in all patients. Moreover, the lateral lymph nodes are at high risk for microscopic involvement and should also be added in the CTV [7]. Target Localisation Sequential PET-CT and MR imaging was performed before the start of CRT [8], after 10 fractions of RT and before surgery (Figure 1). PET-CT studies were acquired on a Siemens Biograph 2 scanner and on a Siemens HiRez Biograph scanner with the patient in treatment position on a belly board device. Three different tracers were used: FDG, FLT and FMISO. FDG-PET signals were automatically processed and outlined by use of an adaptive threshold method, determined on the basis of the signal to background ratio [9]. FLT and FMISO scans will be analysed using the

watershed clustering algorithm [10]. This new gradient-based method is more robust against radio-induced peritumoral inflammation, allows to delineate smaller tumor volumes and is independent of the machine. Moreover, all patients were positioned supine on the MRtable at the same time points. Images were obtained with a 1.5T superconducting system. Transaxial T1-weighted images were used for tumour delineation based on visual interpretation of morphological changes by an experienced radiologist. Until now, we have analyzed 30 sequential FDG-PET-CT’s and MRI’s. Table 1 shows the tumor volumes identified on MRI versus FDG-PET. CT was not used for tumor volume analysis, because of the poor soft-tissue contrast. Analysis of the different images obtained before treatment demonstrated slightly larger tumor volumes on MRI compared to FDG-PET (mean volume MRI: 29.6 cc [range 12 cc–82 cc] vs. FDG-PET: 22.2 cc [range 9 cc–56.6 cc]. On the images obtained during treatment, FDG-PET tumor volumes revealed larger volumes compared to MRI (FDG-PET: 14.4 cc [range 6 cc–37.2 cc] vs. MRI: 14.4 cc [range 4.3 cc–48.4 cc]). The tumor volumes after RT were 7.8 cc [range 2.4 cc–20.4 cc] on MRI and 5.5 cc [range 0 cc–20 cc] on FDG-PET. In 4 patients, no clear FDG signal could be differentiated from the background activity; these patients were judged as having a complete metabolic response. On average, both MRI and FDG-PET showed a trend towards tumor shrinkage during and after CRT. The mean MRI tumor volume reduced to 48% (range 25% to 78%) of the initial mean volume after 10 fractions of RT and to 26% (range 7% to 60%) before surgery. The mean FDG-PET tumor volume decreased to 65% (32% to 109%) of the initial volume after 10 fractions of RT and to 24% (0% to 57%) before surgery. Although both modalities reveal similar volume reductions overall, the mean tumor volume measured on MRI during RT is smaller compared to FDG-PET (FDG-PET: 14.4 cc ± 9.1 vs. MRI: 12.5 cc ± 8.8). To assess the value of anatomical and functional information in target delineation, a dedicated method was developed to obtain a 3D co-registration of the resected specimen with the preoperative images [11]. Image Co-registration Introducing multiple imaging modalities, taken on various time points during the treatment process necessitates exact registration of the images to a common reference image, in order to accurately

Key Words: Rectal cancer · Image guidance · Radiation Strahlenther Onkol 2007;183 (Sondernr. 2):21–3 DOI 10.1007/s00066-007-2009-2

1 2

Leuvens Kanker Instituut, Dept. of Radiotherapy, University Hospital Gasthuisberg, Leuven, Belgium; ESAT/Radiology, Medical Image Computing, University Hospital Gasthuisberg, ESAT, Leuven, Belgium

Strahlenther Onkol 2007 · Sondernr. 2 © Urban & Vogel

21

Haustermans K, et al. Imageguided Radiotherapy in Rectal Cancer

(re)define the target, (re)plan the treatment and (re)calculate time-adjusted dose distributions. We tested a non-rigid image registration algorithm using a B-spline transformation model and mutual information (MI) constrains without use of regularisation penalties. Details of this registration process have been described previously [12]. Validation of the transformation obtained from the non-rigid registration algorithm was carried out on images with manually delineated mesorectal contours. We used 2 criteria to validate the registration: the distance between the centroids (CD) of corresponding mesorectal contours and their volume overlap, measured with the Dice Similarity Criterium (DSC). Analysis of the non-rigid registration of multi-temporal CT scans in 5 patients showed a strong increase in DSC and decrease in CD for all registrations from rigid to non-rigid registration with a mean DSC increasing from 0.81 to 0.88 and a mean CD decreas-

ing from 5.5 mm to 1.8 mm. A similar analysis of multi-temporal MR images resulted in a mean improvement in DSC from 0.79 to 0.88 and in CD from 4.37 to 1.27 mm. Rigid registration of MR and CT images results in larger variances compared to monomodal registration because of the differences in patient position and in characteristics of the native images. Overall, the registration quality improved with a mean decrease in CD from 7.37 mm to 2.98 mm and increase in DSC from 0.71 to 0.80 mm. Patient Positioning Quantification of set-up errors is necessary to assess the accuracy of patient positioning and define set-up margins. The results of the set-up analyses performed in our department on the basis of portal imaging show that patient positioning on a belly-board device by laser alignment to skin marks is accurate and reproducible. The systematic error should be identified and corrected during

Figure 1. From top: tumor volume displayed in transverse plane on macroscopic specimen at time of resection (row 1) with corresponding MRI (row 2), CT (row 3) and FDG PET (row 4) acquired just before surgery.

22

Strahlenther Onkol 2007 · Sondernr. 2 © Urban & Vogel

Haustermans K, et al. Imageguided Radiotherapy in Rectal Cancer

Table 1. Tumor volumes of 10 patients identified by MR and FDG-PET. n = 10

Time point

MR

FDG-PET

Mean

Before RT During RT After RT

29,61 14,38 7,84

22,16 14,44 5,54

STDEV

Before RT During RT After RT

21,44 12,83 6,22

13,72 9,09 6,33

MIN

Before RT During RT After RT

12,04 4,34 2,44

9,03 6,06 0,00

MAX

Before RT During RT After RT

82,03 48,35 20,39

56,56 37,19 19,97

the first fractions of treatment. Thereafter, verification should be performed at regular intervals to correct for possible time trends. In some patients a fixed vertical couch position is recommended [13]. We are currently investigating the role of cone beam CT scan in patient positioning as this will allow us to study internal organ motion as well. Dose Delivery Techniques Dose can be delivered by IMRT using a 7 beam set-up or by IMAT. Both delivery options are currently under investigation in our department. Moreover, improvement of dose reconstruction quality on repeated cone-beam CT will allow cumulative dosimetry. The resulting detailed dosimetric information about delivered radiation dose to the tumor and to organs at risk (OAR) will enable dose guided adaptive radiotherapy techniques. Treatment can then interactively be adjusted to the intended treatment, taking into account the variability in time of the patients anatomy. Conclusion The use of pre-treatment imaging only as a basis for the entire treatment assumes anatomy and functional characteristics of tissue do not change during the course of treatment. Since new technologies have made it possible to track geometrical and biological changes during treatment, this work tries to evaluate the feasibility of incorporating biological information and its changes during treatment into the radiation treatment process. If proven feasible, our model will enable dose- and biology- driven adaptive radiation therapy [14]. Adaptive radiotherapy is probably superior to 3D conformal RT based only on pre-treatment anatomical information. However, there are lots of pitfalls and more research is needed before implementing these new techniques in clinical routine. References

2. Bosset JF, Collette L, Calais G, Mineur L, Maingon P, Radosevic-Jelic L, Daban A, Bardet E, Beny A, Ollier JC; EORTC Radiotherapy Group Trial 22921. Chemotherapy with preoperative radiotherapy in rectal cancer. N Engl J Med 2006;355(11):1114–23. 3. Machiels JP, Sempoux C, Scalliet P, Coche JC, Humblet Y, Van Cutsem E, Kerger J, Canon JL, Peeters M, Aydin S, Laurent S, Kartheuser A, Coster B, Roels S, Daisne JF, Honhon B, Duck L, Kirkove C, Bonny MA, Haustermans K. Phase I/II study of preoperative cetuximab, capecitabine, and external beam radiotherapy in patients with rectal cancer. Ann Oncol 2007; 18(4):738–44. 4. Gerard JP, Conroy T, Bonnetain F, Bouche O, Chapet O, Closon-Dejardin MT, Untereiner M, Leduc B, Francois E, Maurel J, Seitz JF, Buecher B, Mackiewicz R, Ducreux M, Bedenne L. Preoperative radiotherapy with or without concurrent fluorouracil and leucovorin in T3–4 rectal cancers: results of FFCD 9203. J Clin Oncol 2006;24(28):4620–5. 5. Duthoy W, De Gersem W, Vergote K, Boterberg T, Derie C, Smeets P, De Wagter C, De Neve W. Clinical implementation of intensity-modulated arc therapy (IMAT) for rectal cancer. Int J Radiat Oncol Biol Phys 2004; 60(3):794–806. 6. Bagatzounis A, Kölbl O, Oppitz U. Das Lokoregionäre Rezidiv des Rektumkarzinomz: eine computertomographische Analyse und ein Zielvolumenconcept für die adjuvante Radiotherapie. Strahlenther Onkol 2006;173:68–75. 7. Roels S, Duthoy W, Haustermans K, Penninckx F, Vandecaveye V, Boterberg T, De Neve W. Definition and delineation of the clinical target volume for rectal cancer. Int J Radiat Oncol Biol Phys 2006 Jul 15;65(4):1129–42. 8. Grosu AL, Piert M, Weber WA, Jeremic B, Picchio M, Schratzenstaller U, Zimmermann FB, Schwaiger M, Molls M: Positron Emission Tomography for Radiation Treatment Planning. Strahlenther Onkol 2005;181(8): 483–99. 9. Daisne JF, Sibomana M, Bol A, Doumont T, Lonneux M, Gregoire V. Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms. Radiother Oncol 2003;69(3):247–50. 10. Geets X, Lee JA, Bol A, Lonneux M, Gregoire V. A gradient-based method for segmenting FDG-PET images: methodology and validation. Eur J Nucl Med Mol Imaging. 2007; [Epub ahead of print] 11. Daisne JF, Duprez T, Weynand B, Lonneux M, Hamoir M, Reychler H, Gregoire V. Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. Radiology 2004; 33(1):93–100. 12. Slagmolen P, Loeckx D, Roels S, Geets X, Maes F, Haustermans K, Suetens P. Non-rigid Registration of Multi-temporal CT and MR images for Radiotherapy Treatment Planning. Abstract WBIR 2006: Third International Workshop on biomedical image registration, LNCS 2006;4057:297–305. 13. Roels S, Verstraete J, Haustermans K. Set-up verification on a belly-board device using electronic portal imaging. J Radiotherapy in Practice 2007; 5:1–10. 14. Gregoire V, Haustermans K, Geets X, Roels S, Lonneux M. PET-Based Treatment Planning in Radiotherapy: A New Standard? J Nucl Med 2007; 48(1_suppl): 68S–77S.

Karin Haustermans Leuvens Kanker Instituut, Dept. of Radiotherapy University Hospital Gasthuisberg Herestraat 49 3000 Leuven Belgium [email protected]

1. Withers H, Haustermans K. Where next with preoperative radiation therapy for rectal cancer? Int J Radiat Oncol Biol Phys 2004;58(2):597–602.

Strahlenther Onkol 2007 · Sondernr. 2 © Urban & Vogel

23