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Session Item

Tuesday
December 01
09:15 - 10:30
Clinical Stream 2
ESTRO-ESGO: This house believes that lymph node dissection can be omitted in FIGO stage IB1/2(<4 cm)iN1(imaging) cervical cancer
According to the new ESGO/ESTRO/ESP guidelines, in patients with FIGO stage 2009 IB1 (< 4 cm) cervical cancer with unequivocally pathological pelvic lymphnodes (PLNs) on imaging, definitive radiochemotherapy is recommended to avoid multimodality treatment. In addition, para-aortic lympnode dissection (PALND) may be considered in patients with negative PALNs on imaging to ensure node negative disease. Alternatively, especially in patients with extensive pelvic node disease, elective PAO node irradiation can be applied. Since then, much debate has taken place in the MTBs about how to treat this specific patient group. The value of imaging and surgical staging, and the PROs and CONs of specific treatment options, will be discussed in this joint debate.
Joint Debate
Clinical
08:00 - 08:40
Do’s and don’ts in automated treatment planning – optimising conditions and expectations \r
SP-0008

Abstract

Do’s and don’ts in automated treatment planning – optimising conditions and expectations \r
Authors: HEIJMEN|, BEN(1)*[b.heijmen@erasmusmc.nl];SHARFO|, A(1);ROSSI|, L(1);PENNINKHOF|, J(1);DIRKX|, M(1);BREEDVELD|, S(1);
(1)ERASMUS MC CANCER INSTITUTE ROTTERDAM, RADIATION ONCOLOGY, ROTTERDAM, THE NETHERLANDS;
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Abstract Text
Abstract text

Recently, many publications have appeared on development and validation of algorithms for automated treatment planning. Apart from large reductions in treatment planning workload, also significant increases in plan quality have been reported, depending on the applied algorithm and performed study. Clinical implementation of these algorithms is not trivial. Apart from technical/algorithmic issues, also logistical and organizational aspects need to be carefully addressed for making clinical use a success. This lecture will focus on measures and conditions for effective, efficient and safe clinical use of automated planning.