A fast radiotherapy paradigm for anal cancer with volumetric modulated arc therapy (VMAT)

Background/Purpose: Radiotherapy (RT) volumes for anal cancer are large and of moderate complexity when organs at risk ( OAR) such as testis, small bowel and bladder are at least partially to be shielded. Volumetric intensity modulated arc therapy (VMAT) might provide OAR-shielding comparable to step-and-shoot intensity modulated radiotherapy (IMRT) for this tumor entity with better treatment efficiency. Materials and methods: Based on treatment planning CTs of 8 patients, we compared dose distributions, comformality index (CI), homogeneity index ( HI), number of monitor units (MU) and treatment time (TTT) for plans generated for VMAT, 3D-CRT and step-and-shoot-IMRT (optimized based on Pencil Beam (PB) or Monte Carlo ( MC) dose calculation) for typical anal cancer planning target volumes (PTV) including inguinal lymph nodes as usually treated during the first phase (0-36 Gy) of a shrinking field regimen. Results: With values of 1.33 +/- 0.21/1.26 +/- 0.05/1.3 +/- 0.02 and 1.39 +/- 0.09, the CI's for IMRT (PB-Corvus/PB-Hyperion/MC-Hyperion) and VMAT are better than for 3D-CRT with 2.00 +/- 0.16. The HI's for the prescribed dose (HI36) for 3D-CRT were 1.06 +/- 0.01 and 1.11 +/- 0.02 for VMAT, respectively and 1.15 +/- 0.02/1.10 +/- 0.02/1.11 +/- 0.08 for IMRT (PB-Corvus/PB-Hyperion/MCHyperion). Mean TTT and MU's for 3D-CRT is 220s/225 +/- 11MU and for IMRT (PB-Corvus/PBHyperion/MC-Hyperion) is 575s/1260 +/- 172MU, 570s/477 +/- 84MU and 610s748 +/- 193MU while TTT and MU for two-arc-VMAT is 290s/268 +/- 19MU. Conclusion: VMAT provides treatment plans with high conformity and homogeneity equivalent to step-and-shoot-IMRT for this mono-concave treatment volume. Short treatment delivery time and low primary MU are the most important advantages

Fully automated treatment planning of spinal metastases - A comparison to manual planning of Volumetric Modulated Arc Therapy for conventionally fractionated irradiation

_Background:_ Planning for Volumetric Modulated Arc Therapy (VMAT) may be time consuming and its use is limited by available staff resources. Automated multicriterial treatment planning can eliminate this bottleneck. We compared automatically created (auto) VMAT plans generated by Erasmus-iCycle to manually created VMAT plans for treatment of spinal metastases. _Methods:_ Forty-two targets in 32 patients were analyzed. Lungs and kidneys were defined as organs at risk (OARs). Twenty-two patients received radiotherapy on kidney levels, 17 on lung levels, and 3 on both levels. _Results:_ All Erasmus-iCycle plans were clinically acceptable. When compared to manual plans, planning target volume (PTV) coverage of auto plans was significantly better. The Homogeneity Index did not differ significantly between the groups. Mean dose to OARs was lower in auto plans concerning both kidneys and the left lung. One hotspot (>110% of D50%) occurred in the spinal cord of one auto plan (33.2 Gy, D50%: 30 Gy). Treatment time was 7% longer in auto plans. _Conclusions:_ Erasmus-iCycle plans showed better target coverage and sparing of OARs at the expense of minimally longer treatment times (for which no constraint was set)

Automated VMAT planning for postoperative adjuvant treatment of advanced gastric cancer

Background: Postoperative/adjuvant radiotherapy of advanced gastric cancer involves a large planning target volume (PTV) with multi-concave shapes which presents a challenge for volumetric modulated arc therapy (VMAT) planning. This study investigates the advantages of automated VMAT planning for this site compared to manual VMAT planning by expert planners. Methods: For 20 gastric cancer patients in the postoperative/adjuvant setting, dual-arc VMAT plans were generated using fully automated multi-criterial treatment planning (autoVMAT), and compared to manually generated VMAT plans (manVMAT). Both automated and manual plans were created to deliver a median dose of 45 Gy to the PTV using identical planning and segmentation parameters. Plans were evaluated by two expert radiation oncologists for clinical acceptability. AutoVMAT and manVMAT plans were also compared based on dose-volume histogram (DVH) and predicted normal tissue complication probability (NTCP) analysis. Results: Both manVMAT and autoVMAT plans were considered clinically acceptable. Target coverage was similar (manVMAT: 96.6 ± 1.6%, autoVMAT: 97.4 ± 1.0%, p = 0.085). With autoVMAT, median kidney dose was reduced on average by > 25%; (for left kidney from 11.3 ± 2.1 Gy to 8.9 ± 3.5 Gy (p = 0.002); for right kidney from 9.2 ± 2.2 Gy to 6.1 ± 1.3 Gy (p <  0.001)). Median dose to the liver was lower as well (18.8 ± 2.3 Gy vs. 17.1 ± 3.6 Gy, p = 0.048). In addition, Dmax of the spinal cord was significantly reduced (38.3 ± 3.7 Gy vs. 31.6 ± 2.6 Gy, p <  0.001). Substantial improvements in dose conformity and integral dose were achieved with autoVMAT plans (4.2% and 9.1%, respectively; p <  0.001). Due to the better OAR sparing in the autoVMAT plans compared to manVMAT plans, the predicted NTCPs for the left and right kidney and the liver-PTV were significantly reduced by 11.3%, 12.8%, 7%, respectively (p ≤ 0.001). Delivery time and total number of monitor units were increased in autoVMAT plans (from 168 ± 19 s to 207 ± 26 s, p = 0.006) and (from 781 ± 168 MU to 1001 ± 134 MU, p = 0.003), respectively. Conclusions: For postoperative/adjuvant radiotherapy of advanced gastric cancer, involving a complex target shape, automated VMAT planning is feasible and can substantially reduce the dose to the kidneys and the liver, without compromising the target dose delivery

Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning

<p>Abstract</p> <p>Background</p> <p>Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined.</p> <p>Methods</p> <p>The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules.</p> <p>Results</p> <p>Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%.</p> <p>Conclusion</p> <p>The study demonstrated a feasible way to automatically perform parameter optimization of inverse treatment planning under guidance of prior knowledge without human intervention other than providing a set of constraints that have proven clinically useful in a given setting.</p

Analysis and Presentation of the Development Status of Vehicle Technologies for Electrification and Automation by Creating a Technology Calendar

The automotive industry is experiencing fundamental changes due to the current developments in electrification, connectivity and automation. Companies are therefore faced with the question of which technologies and products will be relevant in the future. This applies equally to OEMs and the entire supplier chain. With the technology calendar TKBW presented here, the expected technological developments of passenger cars are described until 2035 on the basis of more than 40 modules, i.e. technology groups, with almost 150 technologies in the areas of propulsion, connectivity and automation. It is thus significantly more comprehensive than other roadmaps and is aimed at small and medium-sized companies that need to strategically align themselves in the technology shift. Maturity of the technologies is characterized by technology and manufacturing readiness levels. This paper describes the methodology used (including roadmapping, Delphi survey and patent research) and explains by means of exemplary findings how the results can be used to find new technology and business opportunities. The work resulted in three products, which can be accessed at www.tkbw.de: a guideline describing the big picture, a module catalog presenting technology roadmaps for each module, and technology fact sheets as a structured reference book

An offline technique to evaluate residual motion of the diaphragm during deep inspiratory breath-hold from cone-beam CT datasets

Purpose: In radiation therapy, the computer-assisted deep inspiration breath-hold (DIBH) technique is one approach to deal with respiratory motion of tumors in the lung, liver, or upper abdomen. However, inter- and intra-breath-hold deviations from an optimal static tumor position might occur. A&nbsp;novel method is presented to noninvasively measure the diaphragm position and thus estimate its residual deviation (as surrogate for the tumor position) based on cone-beam computed tomography (CBCT) projection data using active breathing control during acquisition. Methods: The diaphragm dome (DD) position relative to the isocenter of a&nbsp;linear accelerator is known from the static (DIBH) planning CT. A ball-bearing phantom (BB) is placed at this position, a&nbsp;CBCT dataset is acquired, and in each projection the position of the projected BB is determined automatically based on thresholding. The position of the DD is determined manually in CBCT projections of a&nbsp;patient. The distance between DD and BB (ideal static setting) in craniocaudal direction is calculated for a&nbsp;given angle based on the distance in the projection plane and the relative position of the BB referring to the source and the detector. An angle-dependent correction factor is introduced which takes this geometrical setting into account. The accuracy of the method is assessed. Results: The method allows a&nbsp;CBCT projection-based estimation of the deviation between the DD and its optimal position as defined in the planning CT, i.e., the residual motion of the DD can be assessed. The error of this estimation is 2.2 mm in craniocaudal direction. Conclusions: The developed method allows an offline estimation of the inspiration depth (inter- and intra-breath-hold) over time. It will be useful as a&nbsp;reference for comparison to other methods of residual motion estimation, e.g., surface scanning

Radiation-induced optic neuropathy after stereotactic and image guided intensity-modulated radiation therapy (IMRT)

Background/purpose: To quantify the risk of radiation-induced optic neuropathy (RION) after stereotactic/image-guided positioning and intensity-modulated radiotherapy (IMRT) with ≥50 Gy to the anterior visual pathway (AVP). Methods: Patients irradiated with ≥50 Gy to the AVP using stereotactic/image-guided positioning between 2002 and 2011 in Mannheim were identified. Detailed dosimetric data were collected and patients or family members were retrospectively asked to rate visual acuity and visual disorders. Results: 125 patients fulfilled the eligibility criteria. Average maximum equivalent point dose (D max -EQD-2 [α/β=1.6] ) to the AVP was 53.1 ± 3.9 Gy. 99 patients received ≥50 Gy bilaterally (chiasm or both optic nerves), resulting in 224 (99x2 bilateral plus 26 unilateral) visual-fields-at-risk (VFAR) for RION. Eighty-two patients provided pre/post-IMRT visual status information (n = 151 VFARs). Permanent visual deterioration occurred in 18 (22%) patients. In seven, visual deterioration was possibly related to radiotherapy (two-sided deterioration in one patient) for a crude incidence of 8.5% (7/82 patients) and 5.3% (8/151 VFARs). Two cases were caused by chronic keratitis/conjunctivitis; in five patients RION could not be excluded (one two-sided). In one of 13 patients with D max -EQD-2 &gt; 58 Gy, RION could not be excluded. In all affected patients, visual acuity post-IMRT had decreased only mildly (1–2 points on the 5-point-scale). One patient with relevant baseline visual impairment (3/5) developed unilateral blindness (crude incidence of blindness on patient-/VFAR-level: 1.2% and 0.66%; competing risk-adjusted/actuarial 24-month incidence: patient/VFAR-level: 1.8% and 0.95%). Conclusion: Risk of RION was low in this cohort with accurate positioning and precise dosimetric information. Less conservative tolerance doses may be considered in patients with high risk of recurrence