Computergestützte Assistenz zur Verbesserung der Therapie-Planung in der Kopf-Hals-Onkologie

Zusammenfassung

Die Weiterentwicklungen in der Therapie von Patienten mit Kopf-Hals-Tumoren haben sich in den letzten Jahren differenziert. Durch die komplexen chirurgischen Verfahren, verschiedenste multimodale Therapieansätze, veränderte Techniken in der Bestrahlung (intensitätsmodulierte Radiotherapie – IMRT) und den zahlreichen neuen „targeted therapies“ kommt der präzisen Therapieplanung unter Berücksichtigung relevanter Parameter eine zunehmend zentrale Bedeutung zu. Daneben hat auch die Bildgebung z. B. mit der Implementierung der PET/CT Kombinationsgeräte zusätzlich zum gerätespezifischen Fortschritt deutliche Verbesserungen erfahren. Diese Erhöhung des prätherapeutischen Datenvolumens, einhergehend mit der Diversifikation der therapeutischen Optionen zwingt zu einer intensiveren Auseinandersetzung mit den Grundlagen von Therapieentscheidungen. Um diese Entscheidungen zu unterstützen, können computer­assistierte Systeme zur sinnvollen Aufarbeitung planungsrelevanter Daten hilfreich sein. Diese Arbeit beschreibt den Ist-Stand computerassistierter Systeme in der ersten Prüfung zur Kopf-Hals-Tumortherapieplanung. Hierbei spielt die Integration von 3-dimensionalen Patientenmodellen eine zentrale Rolle. Dieses Planungstool stellt die integrale Grundlage für den weiteren Ausbau von Bestrahlungsplanung, Tumordokumentation und Studienmanagement dar.

Abstract

Computer Assistance to Improve Therapy Planning for Head Neck Oncology

The ongoing development in therapies of head and neck malignomas has led to a further differentiation of treatment options. Complex surgical procedures, a wide variety of multi modal therapy options, changing radiation technologies (IMRT – Intensity-modulated radiation therapy) and numerous “targeted therapies” emphasize the need for a precise treatment plan. Beside this, imaging has seen significant improvements beyond the technical ones, e. g. with the implementation of PET/CT scanners. This increase in pre-therapeutic data volume, together with a diversification of treatment options calls for a further discussion of the basics of therapeutic decisions. Planning relevant data processing by computer assisted systems can aid in these decisions. This work describes the current status of relevant computer assisted systems undergoing first testing for head and neck cancer therapy planning. Here, the integration of 3-dimensional patient data plays a central role. This planning tool forms the integrated base for a further development in the areas of radiation planning, documentation and study management.

Schlüsselwörter

computerassistierte ­Chirurgie - CAS - Kopf-Hals-Tumore - PET-CT - Volumetrie - Tumor Therapy Manager

Key words

computer assisted surgery - CAS - head neck cancer - PET-CT - volumetry - tumor therapy manager

• Literatur

• 1 Weinstein GS, O’Malley Jr BW, Desai SC, Quon H. Transoral robotic surgery: does the ends justify the means?. Curr Opin Otolaryngol Head Neck Surg 2009; Apr; 17 (02) 126-131
• 2 Christianen ME, Muijs CT, Chouvalova O, Burlage FR, Doornaert P, Koken PW, Leemans CR, Rinkel RN, de Bruijn MJ, de Bock GH, Roodenburg JL, van der Laan BF, Slotman BJ, Verdonck-de Leeuw IM, Bijl HP, Langendijk JA. Predictive modelling for swallowing dysfunction after primary (chemo)radiation: Results of a prospective observational study. Radiother Oncol 2011; Sep 8
• 3 Sant M, Allemani C, Santaquilani M, Knijn A, Marchesi F, Capocaccia R. EUROCARE Working Group. EUROCARE-4. Survival of cancer patients diagnosed in 1995–1999. Results and commentary. Eur J Cancer 2009; 45 (06) 931-991
• 4 Dietz A, Wichmann G. Translational research in head and neck cancer: Biological characteristics and general aspects. HNO 2011; Sep; 59 (09) 874-884
• 5 Buerke B, Puesken M, Beyer F, Gerss J, Weckesser M, Seifarth H, Heindel W, Wessling J. Semiautomatic lymph node segmentation in multislice computed tomography: impact of slice thickness on segmentation quality, measurement precision, and interobserver variability. Invest Radiol 2010; Feb; 45 (02) 82-88
• 6 Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, Rubinstein L, Shankar L, Dodd L, Kaplan R, Lacombe D, Verweij J. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009; Jan; 45 (02) 228-247
• 7 Hein PA, Rogalla P, Klessen C, Lembcke A, Romano VC. Computer-aided pulmonary nodule detection – performance of two CAD systems at different CT dose levels. Rofo 2009; Nov; 181 (11) 1056-1064
• 8 Hein PA, Romano VC, Rogalla P, Klessen C, Lembcke A, Dicken V, Bornemann L, Bauknecht HC. Linear and volume measurements of pulmonary nodules at different CT dose levels – intrascan and interscan analysis. Rofo 2009; Jan; 181 (01) 24-31
• 9 Hein PA, Romano VC, Rogalla P, Klessen C, Lembcke A, Bornemann L, Dicken V, Hamm B, Bauknecht HC. Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT. J Digit Imaging 2010; Feb; 23 (01) 8-17
• 10 Dornheim J, Seim H, Preim B, Hertel I, Strauss G. Segmentation of neck lymph nodes in CT datasets with stable 3D mass-spring models segmentation of neck lymph nodes. Acad Radiol 2007; Nov; 14 (11) 1389-1399
• 11 Müller S, Boehm A, Wichmann G, Stumpp P, Dornheim L, Strauss G, Preim P, Dietz A. Different approaches to volume assessment of lymph nodes in CT Scans of HNSCC in comparison with a real gold standard. Abstracts of CARS 2011: Computer Assisted Radiology and Surgery. Proceedings of the 25^th International Congress and Exhibition. Berlin, Germany: June 22–25, 2011
• 12 Rössling I, Cyrus C, Dornheim L, Boehm A, Preim B. Fast and flexible distance measures for treatment planning. Int J Comput Assist Radiol Surg 2010; Nov; 5 (06) 633-646
• 13 Hadjiiski L, Mukherji SK, Gujar SK, Sahiner B, Ibrahim M, Street E, Moyer J, Worden FP, Chan HP. Treatment response assessment of head and neck cancers on CT using computerized volume analysis. AJNR Am J Neuroradiol 2010; Oct; 31 (09) 1744-1751
• 14 Johnson CR, Thames HD, Huang DT, Ruppert K. Schmidt-Ulrich The influence of quantitative tumor volume measurements on local control in advanced head and neck cancer using concomitant boost accelerated superfractionated irradiation. Int J Radiation Oncology Biol Phys 1995; 32: 635-641
• 15 Chong VFH. Tumour volume measurement in head and neck cancer. Cancer Imaging 2007; 7: S47-S49
• 16 Johnson CR, Thames HD, Huang DT. The tumor volume and clonogen number relationship: tumor control predictions based upon tumor volume estimates derived from computed tomography. Int J Radiation Oncology Biol Phys 1995; 33: 281-287
• 17 Chew MH, Khoo JBK, Chong VFH, Tai BC, Soo KC, Lim DTH. Significance of tumour volume measurements in tongue cancer: a novel role in staging. ANZ J Surg 2007; 77: 632-637
• 18 Bhatia KS, King AD, Yu KH, Vlantis AC, Tse GM, Mo FK, Ahuja AT. Does primary tumour volumetry performed early in the course of definitive concomitant chemoradiotherapy for head and neck squamous cell carcinoma improve prediction of primary site outcome?. Br J Radiol 2010; Nov; 83 (995) 964-970
• 19 Kohlfürst S, Markitz M, Raunik W, Eckel HE, Kresnik E, Hausegger K, Salzwimmer M, Gaggl A, Chiari F, Lind P. Positron-emission tomography (PET) and PET/CT in head and neck cancer – recommendations of an interdisciplinary consensus conference. Laryngorhinootologie 2009; Feb; 88 (02) 84-90
• 20 Schöder H, Fury M, Lee N, Kraus D. PET monitoring of therapy response in head and neck squamous cell carcinoma. J Nucl Med 2009; May; 50 (Suppl. 01) 74S-88S
• 21 De Maeseneer DJ, Lambert B, Surmont V, Geboes K, Rottey SW. 18-Fluo­rodeoxyglucose positron emission tomography as a tool for response prediction in solid tumours. Acta Clin Belg 2010; Sep-Oct; 65 (05) 291-299
• 22 Deron P, Mertens K, Goethals I, Rottey S, Duprez F, De Neve W, Vermeersch H, Van de Wiele C. Metabolic tumour volume. Prognostic value in locally advanced squamous cell carcinoma of the head and neck. Nuklearmedizin 2011; 50 (04) 141-146
• 23 Voigt D, Döllinger M, Yang A, Eysholdt U, Lohscheller J. Automatic diag­nosis of vocal fold paresis by employing phonovibrogram features and machine learning methods. Comput Methods Programs Biomed 2010; Sep; 99 (03) 275-288
• 24 Voigt D, Eysholdt U. Identifying relevant analysis parameters for the classification of vocal fold dynamics. J Acoust Soc Am 2011; Oct; 130 (04) 2550
• 25 Lohscheller J, Döllinger M, Schuster M, Schwarz R, Eysholdt U, Hoppe U. Quantitative investigation of the vibration pattern of the substitute voice generator. IEEE Trans Biomed Eng 2004; Aug; 51 (08) 1394-1400
• 26 Verikas A, Gelzinis A, Bacauskiene M, Valincius D, Uloza V. A kernel-based approach to categorizing laryngeal images. Comput Med Imaging Graph 2007; Dec; 31 (08) 587-594
• 27 Arens C, Reussner D, Woenkhaus J, Leunig A, Betz CS, Glanz H. Indirect fluorescence laryngoscopy in the diagnosis of precancerous and cancerous laryngeal lesions. Eur Arch Otorhinolaryngol 2007; Jun 264 (06) 621-626
• 28 Verikas A, Uloza V, Bacauskiene M, Gelzinis A, Kelertas E. Advances in laryngeal imaging. Eur Arch Otorhinolaryngol 2009; Oct; 266 (10) 1509-1520
• 29 Sambale M, Schuster M, Bocklet T, Maier A, Eysholdt U, Ströbele A, Stelzle F. Speech intelligibility degree and coping after multimodal therapy of oral squamous carcinoma. Laryngorhinootologie 2011; Mar; 90 (03) 151-156
• 30 Haderlein T, Nöth E, Batliner A, Eysholdt U, Rosanowski F. Automatic intelligibility assessment of pathologic speech over the telephone. Logoped Phoniatr Vocol 2011; Aug 30; [Epub ahead of print]
• 31 Moers C, Möbius B, Rosanowski F, Nöth E, Eysholdt U, Haderlein T. Vowel- and Text-Based Cepstral Analysis of Chronic Hoarseness. J Voice 2011; Sep 21; [Epub ahead of print]
• 32 Fischer M, Straus G, Gahr S, Richter I, Müller S, Burgert O, Dornheim J, Preim B, Dietz A, Boehm A. Three-dimensional visualization for preoperative planning and evaluation in head and neck surgery. Laryngorhinootologie 2009; Apr; 88 (04) 229-233
• 33 Boehm A, Dornheim J, Fischer M, Strauss G, Dietz A, Preim B. 3-D-Panendoscopy. Int J CARS 2009; 4 (Suppl. 01) S222-S224
• 34 Strauss G. Computer-assisted surgery of the frontal skull base. HNO 2009; Oct; 57 (10) 990-997
• 35 Hofer M, Dittrich E, Baumberger C, Strauss M, Dietz A, Lüth T, Strauss G. The influence of various registration procedures upon surgical accuracy during navigated controlled petrous bone surgery. Otolaryngol Head Neck Surg 2010; Aug; 143 (02) 258-262
• 36 Strauss G, Winkler D, Trantakis C, Schulz T, Meixensberger J. Post-processing of radiological data for preoperative planning in skull base surgery. Laryngorhinootologie 2004; Mar; 83 (03) 157-163
• 37 Strauss G, Limpert E, Strauss M, Hofer M, Dittrich E, Nowatschin S, Lüth T. Evaluation of a daily used navigation system for FESS. Laryngorhinootologie 2009; Dec; 88 (12) 776-781
• 38 Simpson DR, Lawson JD, Nath SK, Rose BS, Mundt AJ, Mell LK. Utilization of advanced imaging technologies for target delineation in radiation oncology. J Am Coll Radiol 2009; Dec; 6 (12) 876-883
• 39 Prabhakar R, Rath GK, Haresh KP, Manoharan N, Laviraj MA, Rajendran M, Julka PK. A study on the tumor volume computation between different 3D treatment planning systems in radiotherapy. J Cancer Res Ther 2011; Apr-Jun; 7 (02) 168-173
• 40 Shakam A, Scrimger R, Liu D, Mohamed M, Parliament M, Field GC, El-Gayed A, Cadman P, Jha N, Warkentin H, Skarsgard D, Zhu Q, Ghosh S. Dose-volume analysis of locoregional recurrences in head and neck IMRT, as determined by deformable registration: a prospective multi-institutional trial. Radiother Oncol 2011; May; 99 (02) 101-107
• 41 Bumm R, Siess M, Lange M, Siewert JR. Necessary prerequisites for the function of an oncological competence center. Information technology, documentation of findings and telecommunication. Dtsch Med Wochenschr 2002; Apr 26; 127 (17) 907-912