Precision assessment of bowel motion quantification using 3D cine-MRI for radiotherapy.

Objective. The bowel is an important organ at risk for toxicity during pelvic and abdominal radiotherapy. Identifying regions of high and low bowel motion with MRI during radiotherapy may help to understand the development of bowel toxicity, but the acquisition time of MRI is rather long. The aim of this study is to retrospectively evaluate the precision of bowel motion quantification and to estimate the minimum MRI acquisition time.Approach. We included 22 gynaecologic cancer patients receiving definitive radiotherapy with curative intent. The 10 min pre-treatment 3D cine-MRI scan consisted of 160 dynamics with an acquisition time of 3.7 s per volume. Deformable registration of consecutive images generated 159 deformation vector fields (DVFs). We defined two motion metrics, the 50th percentile vector lengths (VL50) of the complete set of DVFs was used to measure median bowel motion. The 95th percentile vector lengths (VL95) was used to quantify high motion of the bowel. The precision of these metrics was assessed by calculating their variation (interquartile range) in three different time frames, defined as subsets of 40, 80, and 120 consecutive images, corresponding to acquisition times of 2.5, 5.0, and 7.5 min, respectively.Main results. For the full 10 min scan, the minimum motion per frame of 50% of the bowel volume (M50%) ranged from 0.6-3.5 mm for the VL50 motion metric and 2.3-9.0 mm for the VL95 motion metric, across all patients. At 7.5 min scan time, the variation in M50% was less than 0.5 mm in 100% (VL50) and 95% (VL95) of the subsets. A scan time of 5.0 and 2.5 min achieved a variation within 0.5 mm in 95.2%/81% and 85.7%/57.1% of the subsets, respectively.Significance. Our 3D cine-MRI technique quantifies bowel loop motion with 95%-100% confidence with a precision of 0.5 mm variation or less, using a 7.5 min scan time.

Ruptured infective native thoracic aortic aneurysm treated by endovascular repair as a bridge therapy to open repair.

We report the case of a 70-year-old woman who presented with a ruptured infective native thoracic aortic aneurysm (INTAA), associated with spondylodiscitis and posterior mediastinitis. She underwent a staged hybrid repair: urgent thoracic endovascular aortic repair was first performed as a bridge therapy in the context of septic shock. Allograft repair using cardiopulmonary bypass was performed five days later. Given the complexity of INTAA, multidisciplinary teamwork was paramount to determine the most appropriate treatment strategy, including procedure planning with multiple operators as well as perioperative care. Therapeutic alternatives are discussed.

Quantifying the reduction of respiratory motion by mechanical ventilation with MRI for radiotherapy.

BACKGROUND: Due to respiratory motion, accurate radiotherapy delivery to thoracic and abdominal tumors is challenging. We aimed to quantify the ability of mechanical ventilation to reduce respiratory motion, by measuring diaphragm motion magnitudes in the same volunteers during free breathing (FB), mechanically regularized breathing (RB) at 22 breaths per minute (brpm), variation in mean diaphragm position across multiple deep inspiration breath-holds (DIBH) and diaphragm drift during single prolonged breath-holds (PBH) in two MRI sessions. METHODS: In two sessions, MRIs were acquired from fifteen healthy volunteers who were trained to be mechanically ventilated non-invasively We measured diaphragm motion amplitudes during FB and RB, the inter-quartile range (IQR) of the variation in average diaphragm position from one measurement over five consecutive DIBHs, and diaphragm cranial drift velocities during single PBHs from inhalation (PIBH) and exhalation (PEBH) breath-holds. RESULTS: RB significantly reduced the respiratory motion amplitude by 39%, from median (range) 20.9 (10.6-41.9) mm during FB to 12.8 (6.2-23.8) mm. The median IQR for variation in average diaphragm position over multiple DIBHs was 4.2 (1.0-23.6) mm. During single PIBHs with a median duration of 7.1 (2.0-11.1) minutes, the median diaphragm cranial drift velocity was 3.0 (0.4-6.5) mm/minute. For PEBH, the median duration was 5.8 (1.8-10.2) minutes with 4.4 (1.8-15.1) mm/minute diaphragm drift velocity. CONCLUSIONS: Regularized breathing at a frequency of 22 brpm resulted in significantly smaller diaphragm motion amplitudes compared to free breathing. This would enable smaller treatment volumes in radiotherapy. Furthermore, prolonged breath-holding from inhalation and exhalation with median durations of six to seven minutes are feasible. TRIAL REGISTRATION: Medical Ethics Committee protocol NL.64693.018.18.

Evaluation of Ultra-low-dose Paediatric Cone-beam Computed Tomography for Image-guided Radiotherapy.

AIMS: In image-guided radiotherapy, daily cone-beam computed tomography (CBCT) is rarely applied to children due to concerns over imaging dose. Simulating low-dose CBCT can aid clinical protocol design by allowing visualisation of new scan protocols in patients without delivering additional dose. This work simulated ultra-low-dose CBCT and evaluated its use for paediatric image-guided radiotherapy by assessment of image registration accuracy and visual image quality. MATERIALS AND METHODS: Ultra-low-dose CBCT was simulated by adding the appropriate amount of noise to projection images prior to reconstruction. This simulation was validated in phantoms before application to paediatric patient data. Scans from 20 patients acquired at our current clinical protocol (0.8 mGy) were simulated for a range of ultra-low doses (0.5, 0.4, 0.2 and 0.125 mGy) creating 100 scans in total. Automatic registration accuracy was assessed in all 100 scans. Inter-observer registration variation was next assessed for a subset of 40 scans (five scans at each simulated dose and 20 scans at the current clinical protocol). This subset was assessed for visual image quality by Likert scale grading of registration performance and visibility of target coverage, organs at risk, soft-tissue structures and bony anatomy. RESULTS: Simulated and acquired phantom scans were in excellent agreement. For patient scans, bony atomy registration discrepancies for ultra-low-dose scans fell within 2 mm (translation) and 1° (rotation) compared with the current clinical protocol, with excellent inter-observer agreement. Soft-tissue registration showed large discrepancies. Bone visualisation and registration performance reached over 75% acceptability (rated 'well' or 'very well') down to the lowest doses. Soft-tissue visualisation did not reach this threshold for any dose. CONCLUSION: Ultra-low-dose CBCT was accurately simulated and evaluated in patient data. Patient scans simulated down to 0.125 mGy were appropriate for bony anatomy set-up. The large dose reduction could allow for more frequent (e.g. daily) image guidance and, hence, more accurate set-up for paediatric radiotherapy.

Online adaptive radiotherapy compared to plan selection for rectal cancer: quantifying the benefit.

BACKGROUND: To compare online adaptive radiation therapy (ART) to a clinically implemented plan selection strategy (PS) with respect to dose to the organs at risk (OAR) for rectal cancer. METHODS: The first 20 patients treated with PS between May-September 2016 were included. This resulted in 10 short (SCRT) and 10 long (LCRT) course radiotherapy treatment schedules with a total of 300 Conebeam CT scans (CBCT). New dual arc VMAT plans were generated using auto-planning for both the online ART and PS strategy. For each fraction bowel bag, bladder and mesorectum were delineated on daily Conebeam CTs. The dose distribution planned was used to calculate daily DVHs. Coverage of the CTV was calculated, as defined by the dose received by 99% of the CTV volume (D99%). The volume of normal tissue irradiated with 95% of the prescribed fraction dose was calculated by calculating the volume receiving 95% of the prescribed fraction or more dose minus the volume of the CTV. For each fraction the difference between the plan selection and online adaptive strategy of each DVH parameter was calculated, as well as the average difference per patient. RESULTS: Target coverage remained the same for online ART. The median volume of the normal tissue irradiated with 95% of the prescribed dose dropped from 642 cm3 (PS) to 237 cm3 (online-ART)(p < 0.001). Online ART reduced dose to the OARs for all tested dose levels for SCRT and LCRT (p < 0.001). For V15Gy of the bowel bag the median difference over all fractions of all patients was - 126 cm3 in LCRT, while the average difference per patient ranged from - 206 cm3 to - 40 cm3. For SCRT the median difference was - 62 cm3, while the range of the average difference per patient was - 105 cm3 to - 51 cm3. For V15Gy of the bladder the median difference over all fractions of all patients was 26% in LCRT, while the average difference per patient ranged from - 34 to 12%. For SCRT the median difference of V95% was - 8%, while the range of the average difference per patient was - 29 to 0%. CONCLUSIONS: Online ART for rectal cancer reduces dose the OARs significantly compared to a clinically implemented plan selection strategy, without compromising target coverage. TRIAL REGISTRATION: Medical Research Involving Human Subjects Act (WMO) does not apply to this study and was retrospectively approved by the Medical Ethics review Committee of the Academic Medical Center (W19_357 # 19.420; Amsterdam University Medical Centers, Location Academic Medical Center, Amsterdam, The Netherlands).

Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy.

To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, thus 3D dose distributions must be reconstructed from limited information. State-of-the-art methods achieve this by using 3D surrogate anatomies. These can however lack personalization and lead to coarse reconstructions. We present and validate a surrogate-free dose reconstruction method based on Machine Learning (ML). Abdominal planning CTs (n = 142) of recently-treated childhood cancer patients were gathered, their organs at risk were segmented, and 300 artificial Wilms' tumor plans were sampled automatically. Each artificial plan was automatically emulated on the 142 CTs, resulting in 42,600 3D dose distributions from which dose-volume metrics were derived. Anatomical features were extracted from digitally reconstructed radiographs simulated from the CTs to resemble historical radiographs. Further, patient and radiotherapy plan features typically available from historical treatment records were collected. An evolutionary ML algorithm was then used to link features to dose-volume metrics. Besides 5-fold cross validation, a further evaluation was done on an independent dataset of five CTs each associated with two clinical plans. Cross-validation resulted in mean absolute errors ≤ 0.6 Gy for organs completely inside or outside the field. For organs positioned at the edge of the field, mean absolute errors ≤ 1.7 Gy for [Formula: see text], ≤ 2.9 Gy for [Formula: see text], and ≤ 13% for [Formula: see text] and [Formula: see text], were obtained, without systematic bias. Similar results were found for the independent dataset. To conclude, we proposed a novel organ dose reconstruction method that uses ML models to predict dose-volume metric values given patient and plan features. Our approach is not only accurate, but also efficient, as the setup of a surrogate is no longer needed.

Automatic bi-objective parameter tuning for inverse planning of high-dose-rate prostate brachytherapy.

We present an automatic bi-objective parameter-tuning approach for inverse planning methods for high-dose-rate prostate brachytherapy, which aims to overcome the difficult and time-consuming manual parameter tuning that is currently required to obtain patient-specific high-quality treatment plans. We modelled treatment planning as a bi-objective optimization problem, in which dose-volume-based planning criteria related to target coverage are explicitly separated from organ-sparing criteria. When this model is optimized, a large set of high-quality plans with different trade-offs can be obtained. This set can be visualized as an insightful patient-specific trade-off curve. In our parameter-tuning approach, the parameters of inverse planning methods are automatically tuned, aimed to maximize the two objectives of the bi-objective planning model. By generating trade-off curves for different inverse planning methods, their maximally achievable plan quality can be insightfully compared. Automatic parameter tuning furthermore allows to construct standard parameter sets (class solutions) representing different trade-offs in a principled way, which can be directly used in current clinical practice. In this work, we considered the inverse planning methods IPSA and HIPO. Thirty-nine previously treated prostate cancer patients were included. We compared automatic parameter tuning, random parameter sampling, and the maximally achievable plan quality obtained by directly optimizing the bi-objective planning model with the state-of-the-art optimization software GOMEA. We showed that for each patient, a set of plans with a wide range of trade-offs could be obtained using automatic parameter tuning for both IPSA and HIPO. By tuning HIPO, better trade-offs were obtained than by tuning IPSA. For most patients, automatic tuning of HIPO resulted in plans close to the maximally achievable plan quality obtained by optimizing the bi-objective planning model directly. Automatic parameter tuning was shown to improve plan quality significantly compared to random parameter sampling. Finally, from the automatically-tuned plans, three class solutions were successfully constructed representing different trade-offs.

Dosimetric benefit of an adaptive treatment by means of plan selection for rectal cancer patients in both short and long course radiation therapy.

BACKGROUND: To compare target coverage and dose to the organs at risk in two approaches to rectal cancer: a clinically implemented adaptive radiotherapy (ART) strategy using plan selection, and a non-adaptive (non-ART) strategy. METHODS: The inclusion of the first 20 patients receiving adaptive radiotherapy produced 10 patients with a long treatment schedule (25x2Gy) and 10 patients with a short schedule (5X5Gy). We prepared a library of three plans with different anterior PTV margins to the upper mesorectum, and selected the most appropriate plan on daily Conebeam CT scans (CBCT). We also created a non-adaptive treatment plan with a 20 mm margin. Bowel bag, bladder and target volume were delineated on CBCT. Daily DHVs were calculated based on the dose distribution of the selected and non-adaptive plans. Coverage of the target volume was compared per fraction between the ART and non-ART plans, as was the dose to the bladder and small bowel, assessing the following dose levels: V15Gy, V30Gy, V40Gy, V15Gy and V95% for long treatment schedules, and V15Gy and V95% for short ones. RESULTS: Target volume coverage was maintained from 98.3% (non-ART) to 99.0% (ART)(p = 0.878). In the small bowel, ART appeared to have produced significant reductions in the long treatment schedule at V15Gy, V40Gy, V45Gy and V95% (p <  0.05), but with small absolute differences. The DVH parameters tested for the short treatment schedule did not differ significantly. In the bladder, all DVH parameters in both schedules showed significant reductions (p <  0.05), also with small absolute differences. CONCLUSIONS: The adaptive treatment maintained target coverage and reduced dose to the organs at risk. TRIAL REGISTRATION: Medical Research Involving Human Subjects Act (WMO) does not apply to this study and was retrospectively approved by the Medical Ethics review Committee of the Academic Medical Center, W19_194 # 19.233.

Dosimetric comparison of library of plans and online MRI-guided radiotherapy of cervical cancer in the presence of intrafraction anatomical changes.

BACKGROUND: Online magnetic resonance imaging (MRI)-guided radiotherapy of cervical cancer has the potential to further reduce dose to organs at risk (OAR) as compared to a library of plans (LOP) approach. This study presents a dosimetric comparison of an MRI-guided strategy with a LOP strategy taking intrafraction anatomical changes into account. METHODS: The 14 patients included in this study were treated with chemo radiation at our institute and received weekly MRIs after informed consent. The MRI-guided strategy consisted of treatment plans created on the weekly sagittal MRI with 3 mm and 5 mm planning target volume (PTV) margin for clinical target volume (CTV) cervix-uterus (MRI_3mm and MRI_5mm). The plans for the LOP strategy were based on interpolations of CTV cervix-uterus on pretreatment full and empty bladder scans. Dose volume histogram (DVH) parameters were compared for targets and OARs as delineated on the weekly transversal MRI, which was acquired on average 10 min after the sagittal MRI. RESULTS: For the MRI_5mm strategy D98% of the high-risk CTV was at least 95% for all weekly MRIs of all patients, while for the LOP and MRI_3mm strategy this requirement was not satisfied for at least one weekly MRI for 1 and 3 patients, respectively. The average reduction of the volume of the reference dose (95% of the prescribed dose) as compared to the LOP strategy was 464 cm3 for the MRI_3mm strategy, and 422 cm3 for the MRI_5mm strategy. The bowel bag constraint V40Gy < 350 cm3 was violated for 13 patients for the LOP strategy and for 5 patients for both MRI_3mm and MRI_5mm strategy. CONCLUSIONS: With online MRI-guided radiotherapy of cervical cancer considerable sparing of OARs can be achieved. If a new treatment plan can be generated and delivered within 10 min, an online MRI-guided strategy with a 5 mm PTV margin for CTV cervix-uterus is sufficient to account for intrafraction anatomical changes. TRIAL REGISTRATION: NL44492.018.13.

A novel amplitude binning strategy to handle irregular breathing during 4DMRI acquisition: improved imaging for radiotherapy purposes.

BACKGROUND: For radiotherapy of abdominal cancer, four-dimensional magnetic resonance imaging (4DMRI) is desirable for tumor definition and the assessment of tumor and organ motion. However, irregular breathing gives rise to image artifacts. We developed a outlier rejection strategy resulting in a 4DMRI with reduced image artifacts in the presence of irregular breathing. METHODS: We obtained 2D T2-weighted single-shot turbo spin echo images, with an interleaved 1D navigator acquisition to obtain the respiratory signal during free breathing imaging in 2 patients and 12 healthy volunteers. Prior to binning, upper and lower inclusion thresholds were chosen such that 95% of the acquired images were included, while minimizing the distance between the thresholds (inclusion range (IR)). We compared our strategy (Min95) with three commonly applied strategies: phase binning with all images included (Phase), amplitude binning with all images included (MaxIE), and amplitude binning with the thresholds set as the mean end-inhale and mean end-exhale diaphragm positions (MeanIE). We compared 4DMRI quality based on: Data included (DI); percentage of images remaining after outlier rejection. Reconstruction completeness (RC); percentage of bin-slice combinations containing at least one image after binning. Intra-bin variation (IBV); interquartile range of the diaphragm position within the bin-slice combination, averaged over three central slices and ten respiratory bins. IR. Image smoothness (S); quantified by fitting a parabola to the diaphragm profile in a sagittal plane of the reconstructed 4DMRI. A two-sided Wilcoxon's signed-rank test was used to test for significance in differences between the Min95 strategy and the Phase, MaxIE, and MeanIE strategies. RESULTS: Based on the fourteen subjects, the Min95 binning strategy outperformed the other strategies with a mean RC of 95.5%, mean IBV of 1.6 mm, mean IR of 15.1 mm and a mean S of 0.90. The Phase strategy showed a poor mean IBV of 6.2 mm and the MaxIE strategy showed a poor mean RC of 85.6%, resulting in image artifacts (mean S of 0.76). The MeanIE strategy demonstrated a mean DI of 85.6%. CONCLUSIONS: Our Min95 reconstruction strategy resulted in a 4DMRI with less artifacts and more precise diaphragm position reconstruction compared to the other strategies. TRIAL REGISTRATION: Volunteers: protocol W15_373#16.007; patients: protocol NL47713.018.14.

What Slows Down Phytoplasma Proliferation? Speculations on the Involvement of AtSEOR2 Protein in Plant Defence Signalling.

Considering the crude methods used to control phytoplasma diseases, a deeper knowledge on the defence mechanisms recruited by the plant to face phytoplasma invasion is required. Recently, we demonstrated that Arabidopsis mutants lacking AtSEOR1 gene showed a low phytoplasma titre. In wild type plants AtSEOR1 and AtSEOR2 are tied in filamentous proteins. Knockout of the AtSEOR1 gene may pave the way for an involvement of free AtSEOR2 proteins in defence mechanisms. Among the proteins conferring resistance against pathogenic bacteria, AtRPM1-interacting protein has been found to interact with AtSEOR2 in a high-quality, matrix-based yeast-two hybrid assay. For this reason, we investigated the expression levels of Arabidopsis AtRIN4, and the associated AtRPM1 and AtRPS2 genes in healthy and Chrysanthemum yellows-infected wild-type and Atseor1ko lines.

The alfa and beta of tumours: a review of parameters of the linear-quadratic model, derived from clinical radiotherapy studies.

BACKGROUND: Prediction of radiobiological response is a major challenge in radiotherapy. Of several radiobiological models, the linear-quadratic (LQ) model has been best validated by experimental and clinical data. Clinically, the LQ model is mainly used to estimate equivalent radiotherapy schedules (e.g. calculate the equivalent dose in 2 Gy fractions, EQD2), but increasingly also to predict tumour control probability (TCP) and normal tissue complication probability (NTCP) using logistic models. The selection of accurate LQ parameters α, ß and α/ß is pivotal for a reliable estimate of radiation response. The aim of this review is to provide an overview of published values for the LQ parameters of human tumours as a guideline for radiation oncologists and radiation researchers to select appropriate radiobiological parameter values for LQ modelling in clinical radiotherapy. METHODS AND MATERIALS: We performed a systematic literature search and found sixty-four clinical studies reporting α, ß and α/ß for tumours. Tumour site, histology, stage, number of patients, type of LQ model, radiation type, TCP model, clinical endpoint and radiobiological parameter estimates were extracted. Next, we stratified by tumour site and by tumour histology. Study heterogeneity was expressed by the I2 statistic, i.e. the percentage of variance in reported values not explained by chance. RESULTS: A large heterogeneity in LQ parameters was found within and between studies (I2 > 75%). For the same tumour site, differences in histology partially explain differences in the LQ parameters: epithelial tumours have higher α/ß values than adenocarcinomas. For tumour sites with different histologies, such as in oesophageal cancer, the α/ß estimates correlate well with histology. However, many other factors contribute to the study heterogeneity of LQ parameters, e.g. tumour stage, type of LQ model, TCP model and clinical endpoint (i.e. survival, tumour control and biochemical control). CONCLUSIONS: The value of LQ parameters for tumours as published in clinical radiotherapy studies depends on many clinical and methodological factors. Therefore, for clinical use of the LQ model, LQ parameters for tumour should be selected carefully, based on tumour site, histology and the applied LQ model. To account for uncertainties in LQ parameter estimates, exploring a range of values is recommended.

The effect of time interval between radiotherapy and hyperthermia on planned equivalent radiation dose.

PURPOSE: Thermoradiotherapy is an effective treatment for locally advanced cervical cancer. However, the optimal time interval between radiotherapy and hyperthermia, resulting in the highest therapeutic gain, remains unclear. This study aims to evaluate the effect of time interval on the therapeutic gain using biological treatment planning. METHODS: Radiotherapy and hyperthermia treatment plans were created for 15 cervical cancer patients. Biological modeling was used to calculate the equivalent radiation dose, that is, the radiation dose that results in the same biological effect as the thermoradiotherapy treatment, for different time intervals ranging from 0-4 h. Subsequently, the thermal enhancement ratio (TER, i.e. the ratio of the dose for the thermoradiotherapy and the radiotherapy-only plan) was calculated for the gross tumor volume (GTV) and the organs at risk (OARs: bladder, rectum, bowel), for each time interval. Finally, the therapeutic gain factor (TGF, i.e. TERGTV/TEROAR) was calculated for each OAR. RESULTS: The median TERGTV ranged from 1.05 to 1.16 for 4 h and 0 h time interval, respectively. Similarly, for bladder, rectum and bowel, TEROARs ranged from 1-1.03, 1-1.04 and 1-1.03, respectively. Radiosensitization in the OARs was much less than in the GTV, because temperatures were lower, fractionation sensitivity was higher (lower α/ß) and direct cytotoxicity was assumed negligible in normal tissue. TGFs for the three OARs were similar, and were highest (around 1.12) at 0 h time interval. CONCLUSION: This planning study indicates that the largest therapeutic gain for thermoradiotherapy in cervical cancer patients can be obtained when hyperthermia is delivered immediately before or after radiotherapy.

Measurement and analysis of the impact of time-interval, temperature and radiation dose on tumour cell survival and its application in thermoradiotherapy plan evaluation.

PURPOSE: Biological modelling of thermoradiotherapy may further improve patient selection and treatment plan optimisation, but requires a model that describes the biological effect as a function of variables that affect treatment outcome (e.g. temperature, radiation dose). This study aimed to establish such a model and its parameters. Additionally, a clinical example was presented to illustrate the application. METHODS: Cell survival assays were performed at various combinations of radiation dose (0-8 Gy), temperature (37-42 °C), time interval (0-4 h) and treatment sequence (radiotherapy before/after hyperthermia) for two cervical cancer cell lines (SiHa and HeLa). An extended linear-quadratic model was fitted to the data using maximum likelihood estimation. As an example application, a thermoradiotherapy plan (23 × 2 Gy + weekly hyperthermia) was compared with a radiotherapy-only plan (23 × 2 Gy) for a cervical cancer patient. The equivalent uniform radiation dose (EUD) in the tumour, including confidence intervals, was estimated using the SiHa parameters. Additionally, the difference in tumour control probability (TCP) was estimated. RESULTS: Our model described the dependency of cell survival on dose, temperature and time interval well for both SiHa and HeLa data (R2=0.90 and R2=0.91, respectively), making it suitable for biological modelling. In the patient example, the thermoradiotherapy plan showed an increase in EUD of 9.8 Gy that was robust (95% CI: 7.7-14.3 Gy) against propagation of the uncertainty in radiobiological parameters. This corresponded to a 20% (95% CI: 15-29%) increase in TCP. CONCLUSIONS: This study presents a model that describes the cell survival as a function of radiation dose, temperature and time interval, which is essential for biological modelling of thermoradiotherapy treatments.

Large scale, prospective screening of EGFR mutations in the blood of advanced NSCLC patients to guide treatment decisions.

BACKGROUND: In a significant percentage of advanced non-small-cell lung cancer (NSCLC) patients, tumor tissue is unavailable or insufficient for genetic analyses. We prospectively analyzed if circulating-free DNA (cfDNA) purified from blood can be used as a surrogate in this setting to select patients for treatment with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). PATIENTS AND METHODS: Blood samples were collected in 119 hospitals from 1138 advanced NSCLC patients at presentation (n = 1033) or at progression to EGFR-TKIs (n = 105) with no biopsy or insufficient tumor tissue. Serum and plasma were sent to a central laboratory, cfDNA purified and EGFR mutations analyzed and quantified using a real-time PCR assay. Response data from a subset of patients (n = 18) were retrospectively collected. RESULTS: Of 1033 NSCLC patients at presentation, 1026 were assessable; with a prevalence of males and former or current smokers. Sensitizing mutations were found in the cfDNA of 113 patients (11%); with a majority of females, never smokers and exon 19 deletions. Thirty-one patients were positive only in plasma and 11 in serum alone and mutation load was higher in plasma and in cases with exon 19 deletions. More than 50% of samples had <10 pg mutated genomes/µl with allelic fractions below 0.25%. Patients treated first line with TKIs based exclusively on EGFR positivity in blood had an ORR of 72% and a median PFS of 11 months. Of 105 patients screened after progression to EGFR-TKIs, sensitizing mutations were found in 56.2% and the p.T790M resistance mutation in 35.2%. CONCLUSIONS: Large-scale EGFR testing in the blood of unselected advanced NSCLC patients is feasible and can be used to select patients for targeted therapy when testing cannot be done in tissue. The characteristics and clinical outcomes to TKI treatment of the EGFR-mutated patients identified are undistinguishable from those positive in tumor.

3D radiobiological evaluation of combined radiotherapy and hyperthermia treatments.

PURPOSE: Currently, clinical decisions regarding thermoradiotherapy treatments are based on clinical experience. Quantification of the radiosensitising effect of hyperthermia allows comparison of different treatment strategies, and can support clinical decision-making regarding the optimal treatment. The software presented here enables biological evaluation of thermoradiotherapy plans through calculation of equivalent 3D dose distributions. METHODS: Our in-house developed software (X-Term) uses an extended version of the linear-quadratic model to calculate equivalent radiation dose, i.e. the radiation dose yielding the same effect as the thermoradiotherapy treatment. Separate sets of model parameters can be assigned to each delineated structure, allowing tissue specific modelling of hyperthermic radiosensitisation. After calculation, the equivalent radiation dose can be evaluated according to conventional radiotherapy planning criteria. The procedure is illustrated using two realistic examples. First, for a previously irradiated patient, normal tissue dose for a radiotherapy and thermoradiotherapy plan (with equal predicted tumour control) is compared. Second, tumour control probability (TCP) is assessed for two (otherwise identical) thermoradiotherapy schedules with different time intervals between radiotherapy and hyperthermia. RESULTS: The examples demonstrate that our software can be used for individualised treatment decisions (first example) and treatment optimisation (second example) in thermoradiotherapy. In the first example, clinically acceptable doses to the bowel were exceeded for the conventional plan, and a substantial reduction of this excess was predicted for the thermoradiotherapy plan. In the second example, the thermoradiotherapy schedule with long time interval was shown to result in a substantially lower TCP. CONCLUSIONS: Using biological modelling, our software can facilitate the evaluation of thermoradiotherapy plans and support individualised treatment decisions.

A biological modeling based comparison of two strategies for adaptive radiotherapy of urinary bladder cancer.

Background Adaptive radiotherapy is introduced in the management of urinary bladder cancer to account for day-to-day anatomical changes. The purpose of this study was to determine whether an adaptive plan selection strategy using either the first four cone beam computed tomography scans (CBCT-based strategy) for plan creation, or the interpolation of bladder volumes on pretreatment CT scans (CT-based strategy), is better in terms of tumor control probability (TCP) and normal tissue sparing while taking the clinically applied fractionation schedules also into account. Material and methods With the CT-based strategy, a library of five plans was created. Patients received 55 Gy to the bladder tumor and 40 Gy to the non-involved bladder and lymph nodes, in 20 fractions. With the CBCT-based strategy, a library of three plans was created, and patients received 70 Gy to the tumor, 60 Gy to the bladder and 48 Gy to the lymph nodes, in 30-35 fractions. Ten patients were analyzed for each adaptive plan selection strategy. TCP was calculated applying the clinically used fractionation schedules, as well as a rescaling of the dose from 55 to 70 Gy for the CT-based strategy. For rectum and bowel, equivalent doses in 2 Gy fractions (EQD2) were calculated. Results The CBCT-based strategy resulted in a median TCP of 75%, compared to 49% for the CT-based strategy, the latter improving to 72% upon rescaling the dose to 70 Gy. A median rectum V30Gy (EQD2) of 26% [interquartile range (IQR): 8-52%] was found for the CT-based strategy, compared to 58% (IQR: 55-73%) for the CBCT-based strategy. Also the bowel doses were lower with the CT-based strategy. Conclusions Whereas the higher total bladder TCP for the CBCT-based strategy is due to prescription differences, the adaptive strategy based on CT scans results in the lowest rectum and bowel cavity doses.