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Purpose: Robust optimization is becoming the gold standard for generating robust plans against various kinds of treatment uncertainties. Today, most robust optimization strategies use a pragmatic set of treatment scenarios (the so‐called uncertainty set) consisting of combinations of maximum errors, of each considered uncertainty source (such as tumor motion, setup and image‐conversion errors). This approach presents two key issues. First, a subset of considered scenarios is unnecessarily improbable which could potentially compromise the plan quality. Second, the resulting large uncertainty set leads to long plan computation times, which limits the potential for robust optimization as a standard clinical tool. In order to address these issues, a method is introduced which is able to preselect a limited set of relevant treatment error scenarios. Methods: Uncertainties due to systematic setup errors, image‐conversion errors and respiratory tumor motion are considered. A four‐dimensional (4D)‐equiprobability hypersurface is defined, which takes into account the joint probabilities of the above‐mentioned uncertainty sources. Only scenarios that lie on the predefined 4D hypersurface are considered, guaranteeing statistical consistency of the uncertainty set. In this regard, twelve scenarios are selected that cover maximum spatial displacements of the tumor during breathing. Subsequently, additional scenarios are considered (sampled from the aforementioned 4D hypersurface) in order to cover any estimated residual range errors. Two different scenario‐selection procedures were tested: (a) the maximum displacements (MD) method that only considers twelve scaled maximum displacement scenarios and (b) maximum displacements and residual range (MDR) method which, in addition to the scaled maximum displacement scenarios, considers additional maximum range uncertainty scenarios. The methods were tested for five lung cancer patients by performing comprehensive Monte Carlo robustness evaluations. Results: A plan computation time gain of 78% is achieved by applying the MD method, whilst obtaining a target robustness of D95 larger than 95% of the prescribed dose, for the worst‐case scenario. Additionally, the MD method has the potential to be fully automatic which makes it a promising candidate for fast automatic planning workflows. The MDR method produced plans with excellent target robustness (D99 larger than 95% of the prescribed dose, even for the worst‐case scenario), whilst still obtaining a significant plan computation time gain of 57%. Conclusions: Two scenario‐selection procedures were developed which achieved significant reduction of plan computation time and memory consumption, without compromising plan quality or robustness. [ABSTRACT FROM AUTHOR]

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• MANIV is a safe breathing-constraining technique that is well-tolerated by patients. • The volume-controlled mode reduces inter-session variation in tumour motion amplitude and stabilizes the respiratory rate, which may facilitate tracking strategies. • The shallow-controlled mode reduces the tumour motion amplitude while ensuring regular, rapid, and shallow breathing that may benefit margin strategies. • The slow-controlled mode repeats short end-inspiratory plateaus (>15 s), well tolerated by patients and potentially useful for gated delivery. Current motion mitigation strategies, like margins, gating, and tracking, deal with geometrical uncertainties in the tumour position, induced by breathing during radiotherapy (RT). However, they often overlook motion variability in amplitude, respiratory rate, or baseline position, when breathing spontaneously. Consequently, this may negatively affect the delivered dose conformality in comparison to the plan. We previously demonstrated on volunteers that 3 different modes of mechanically-assisted and non-invasive ventilation (MANIV) may reduce variability in breathing motion. The volume-controlled mode (VC) constraints the amplitude and respiratory rate (RR) in physiologic condition. The shallow-controlled mode (SH), derived from VC, increases the RR and decreases amplitude. The slow-controlled mode (SL) induces repeated breath holds with constrained ventilation pressure. In this study, we compared these mechanical ventilation modes to spontaneous breathing or breath hold and assessed their tolerance and effects on internal tumour motion in patients receiving RT. The VC and SH modes were evaluated in ten patients with lung or liver cancers (cohort A). The SL mode was evaluated in 12 left breast cancer patients (cohort B). After a training and simulation session, the patients underwent 2 MRI sessions to analyze the internal motion of breast and tumour. MANIV was well tolerated, without any adverse events or oxymetric changes, even in patients with respiratory comorbidities. In cohort A, when compared to spontaneous breathing (SP), VC reduced significantly inter-session variations of the tumour motion amplitude (p = 0.01), as well as intra- and inter-session variations of the RR (p < 0.05). As to SH, the RR increased, while its variations within and across sessions decreased when compared to SP (p < 0.001). SH reduced the median amplitude of the tumour motion by 6.1 mm or 38.2% (p ≤ 0.01) compared to VC. In cohort B, breast position stability over the end-inspiratory plateaus obtained spontaneously or with SL remained similar. Median duration of the plateaus in SL was 16.6 s. MANIV is a safe and well tolerated ventilation technique for patients receiving radiotherapy. MANIV could thus make current motion mitigation strategies less critical and more robust. Clinical implementation might be considered, provided the ventilation mode is carefully selected with respect to the treatment indication and patient individualities. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To compare the mid-position (MidP) strategy to the conventional internal target volume (ITV) for lung tumor management in helical TomoTherapy, using 4D Monte Carlo (MC) plan simulations. Materials and methods: For NSCLC patients treated by SBRT (n =8) or SIB-IMRT (n =7), target volumes and OARs were delineated on a contrast-enhanced CT, while 4D-CT was used to generate either ITV or MidP volumes with deformable registrations. PTV margins were added. Conformity indexes, volumetric and dosimetric parameters were compared for both strategies. Dose distributions were also computed using a 4D MC model (TomoPen) to assess how intra-fraction tumor motion affects tumor coverage, with and without interplay effect. Results: PTVs derived from MidP were on average 1.2 times smaller than those from ITV, leading to lower doses to OARs. Planned dose conformity to TVs was similar for both strategies. 4D MC computation showed that ITV ensured adequate TV coverage (D 95 within 1% of clinical requirements), while MidP failed in 3 patients of the SBRT group (D 95 to the TV lowered by 4.35%, 2.16% and 2.61%) due to interplay effect in one case and to breathing motion alone in the others. Conclusions: Compared to the ITV, the MidP significantly reduced PTV and doses to OARs. MidP is safe for helical delivery except for very small tumors (<5cc) with large-amplitude motion (>10mm) where the ITV might remain the most adequate approach. [Copyright &y& Elsevier]