The clonogenic assay measures the capacity of single cells to form colonies in vitro. It is widely used to identify and quantify self-renewing mammalian cells derived from in vitro cultures as well ...as from ex vivo tissue preparations of different origins. Varying research questions and the heterogeneous growth requirements of individual cell model systems led to the development of several assay principles and formats that differ with regard to their conceptual setup, 2D or 3D culture conditions, optional cytotoxic treatments and subsequent mathematical analysis. The protocol presented here is based on the initial clonogenic assay protocol as developed by Puck and Marcus more than 60 years ago. It updates and extends the 2006 Nature Protocols article by Franken et al. It discusses different strategies and principles to analyze clonogenic growth in vitro and presents the clonogenic assay in a modular protocol framework enabling a diversity of formats and measures to optimize determination of clonogenic growth parameters. We put particular focus on the phenomenon of cellular cooperation and consideration of how this can affect the mathematical analysis of survival data. This protocol is applicable to any mammalian cell model system from which single-cell suspensions can be prepared and which contains at least a small fraction of cells with self-renewing capacity in vitro. Depending on the cell system used, the entire procedure takes ~2-10 weeks, with a total hands-on time of <20 h per biological replicate.
Despite aggressive management consisting of maximal safe surgical resection followed by external beam radiation therapy (60 Gy/30 fractions) with concomitant and adjuvant temozolomide, approximately ...90% of WHO grade IV gliomas (glioblastomas, GBM) will recur locally within 2 years. For patients with recurrent GBM, no standard of care exists. Thanks to the continuous improvement in radiation science and technology, reirradiation has emerged as feasible approach for patients with brain tumors. Using stereotactic radiosurgery (SRS) or stereotactic radiotherapy (SRT), either hypofractionated or conventionally fractionated schedules, several studies have suggested survival benefits following reirradiation of patients with recurrent GBM; however, there are still questions to be answered about the efficacy and toxicity associated with a second course of radiation. We provide a clinical overview on current status and recent advances in reirradiation of GBM, addressing relevant clinical questions such as the appropriate patient selection and radiation technique, optimal dose fractionation, reirradiation tolerance of the brain and the risk of radiation necrosis.
Pancreatic ductal adenocarcinoma (PDAC) is a highly devastating disease with poor prognosis and rising incidence. Late detection and a particularly aggressive biology are the major challenges which ...determine therapeutic failure. In this review, we present the current status and the recent advances in PDAC treatment together with the biological and immunological hallmarks of this cancer entity. On this basis, we discuss new concepts combining distinct treatment modalities in order to improve therapeutic efficacy and clinical outcome - with a specific focus on protocols involving radio(chemo)therapeutic approaches.
Purpose
To demonstrate a proof‐of‐concept for fast cone‐beam CT (CBCT) intensity correction in projection space by the use of deep learning.
Methods
The CBCT scans and corresponding projections were ...acquired from 30 prostate cancer patients. Reference shading correction was performed using a validated method (CBCTcor), which estimates scatter and other low‐frequency deviations in the measured CBCT projections on the basis of a prior CT image obtained from warping the planning CT to the CBCT. A convolutional neural network (ScatterNet) was designed, consisting of an attenuation conversion stage followed by a shading correction stage using a UNet‐like architecture. The combined network was trained in 2D, utilizing pairs of measured and corrected projections of the reference method, in order to perform shading correction in projection space before reconstruction. The number of patients used for training, testing, and evaluation was 15, 7, and 8, respectively. The reconstructed CBCTScatterNet was compared to CBCTcor in terms of mean and absolute errors (ME and MAE) for the eight evaluation patients (not included in the network training). Volumetric modulated arc photon therapy (VMAT) and intensity‐modulated proton therapy (IMPT) plans were generated on CBCTcor. Dose was recalculated on CBCTScatterNet to evaluate its dosimetric accuracy. Single‐field uniform dose proton plans were utilized for proton range comparison of CBCTScatterNet and CBCTcor.
Results
The CBCTScatterNet showed no cupping artifacts and a considerably smaller MAE and ME with respect to CBCTcor than the uncorrected CBCT (on average 144 Hounsfield units (HU) vs 46 HU for MAE and 138 HU vs −3 HU for ME). The pass‐rates using a 2% dose‐difference criterion at 50% dose cut‐off, were close to 100% for the VMAT plans of all patients when comparing CBCTScatterNet to CBCTcor. For IMPT plans pass‐rates were clearly lower, ranging from 15% to 81%. Proton range differences of up to 5 mm occurred.
Conclusions
Using a deep convolutional neural network for CBCT intensity correction was shown to be feasible in the pelvic region for the first time. Dose calculation accuracy on CBCTScatterNet was high for VMAT, but unsatisfactory for IMPT. With respect to the reference technique (CBCTcor), the neural network enabled a considerable increase in speed for intensity correction and might eventually allow for on‐the‐fly shading correction during CBCT acquisition.
Lung, breast, and esophageal cancer represent three common malignancies with high incidence and mortality worldwide. The management of these tumors critically relies on radiotherapy as a major part ...of multi-modality care, and treatment-related toxicities, such as radiation-induced pneumonitis and/or lung fibrosis, are important dose limiting factors with direct impact on patient outcomes and quality of life. In this review, we summarize the current understanding of radiation-induced pneumonitis and pulmonary fibrosis, present predictive factors as well as recent diagnostic and therapeutic advances. Novel candidates for molecularly targeted approaches to prevent and/or treat radiation-induced pneumonitis and pulmonary fibrosis are discussed.
In presence of inter-fractional anatomical changes, clinical benefits are anticipated from image-guided adaptive radiotherapy. Nowadays, cone-beam CT (CBCT) imaging is mostly utilized during ...pre-treatment imaging for position verification. Due to various artifacts, image quality is typically not sufficient for photon or proton dose calculation, thus demanding accurate CBCT correction, as potentially provided by deep learning techniques. This work aimed at investigating the feasibility of utilizing a cycle-consistent generative adversarial network (cycleGAN) for prostate CBCT correction using unpaired training. Thirty-three patients were included. The network was trained to translate uncorrected, original CBCT images (CBCT
) into planning CT equivalent images (CBCT
). HU accuracy was determined by comparison to a previously validated CBCT correction technique (CBCT
). Dosimetric accuracy was inferred for volumetric-modulated arc photon therapy (VMAT) and opposing single-field uniform dose (OSFUD) proton plans, optimized on CBCT
and recalculated on CBCT
. Single-sided SFUD proton plans were utilized to assess proton range accuracy. The mean HU error of CBCT
with respect to CBCT
decreased from 24 HU for CBCT
to -6 HU. Dose calculation accuracy was high for VMAT, with average pass-rates of 100%/89% for a 2%/1% dose difference criterion. For proton OSFUD plans, the average pass-rate for a 2% dose difference criterion was 80%. Using a (2%, 2 mm) gamma criterion, the pass-rate was 96%. 93% of all analyzed SFUD profiles had a range agreement better than 3 mm. CBCT correction time was reduced from 6-10 min for CBCT
to 10 s for CBCT
. Our study demonstrated the feasibility of utilizing a cycleGAN for CBCT correction, achieving high dose calculation accuracy for VMAT. For proton therapy, further improvements may be required. Due to unpaired training, the approach does not rely on anatomically consistent training data or potentially inaccurate deformable image registration. The substantial speed-up for CBCT correction renders the method particularly interesting for adaptive radiotherapy.
Abstract Background and purpose To prospectively assess the prognostic value of tumour hypoxia determined by dynamic 18 FFluoromisonidazole (dynFMISO) PET/CT, and to evaluate both feasibility and ...toxicity in patients with locally advanced squamous cell carcinomas of the head and neck (LASCCHN) treated with dynFMISO image-guided dose escalation (DE) using dose-painting by contours. Patients and methods We present a planned interim analysis of a randomized phase II trial. N = 25 patients with LASCCHN received baseline dynFMISO PET/CT to derive hypoxic volumes (HV). Patients with tumour hypoxia were randomized into standard radiochemotherapy (stdRT) (70 Gy/35 fractions) or DE (77 Gy/35 fractions) to the HV. Patients with non-hypoxic tumours were treated with stdRT. Loco-regional control (LRC) in hypoxic patients randomized to stdRT was compared to non-hypoxic patients. Feasibility and toxicity were analysed for patients in the DE arm and compared to stdRT. Results With a mean follow-up of 27 months, LRC in hypoxic patients receiving stdRT ( n = 10) was significantly worse compared to the non-hypoxic group ( n = 5) (2y-LRC 44.4% versus 100%, p = 0.048). The respective LRC for the DE group ( n = 10) was 70.0%. Treatment compliance as well as acute and late toxicity did not show significant differences between the DE and the standard dose arms. Conclusion Tumour hypoxia determined by baseline dynFMISO PET/CT is associated with a high risk of local failure in patients with LASCCHN. First data suggest that DE to HV is feasible without excess toxicity.
Resistance against radio(chemo)therapy-induced cell death is a major determinant of oncological treatment failure and remains a perpetual clinical challenge. The underlying mechanisms are manifold ...and demand for comprehensive, cancer entity- and subtype-specific examination. In the present study, resistance against radiotherapy was systematically assessed in a panel of human head-and-neck squamous cell carcinoma (HNSCC) cell lines and xenotransplants derived thereof with the overarching aim to extract master regulators and potential candidates for mechanism-based pharmacological targeting. Clonogenic survival data were integrated with molecular and functional data on DNA damage repair and different cell fate decisions. A positive correlation between radioresistance and early induction of HNSCC cell senescence accompanied by NF-κB-dependent production of distinct senescence-associated cytokines, particularly ligands of the CXCR2 chemokine receptor, was identified. Time-lapse microscopy and medium transfer experiments disclosed the non-cell autonomous, paracrine nature of these mechanisms, and pharmacological interference with senescence-associated cytokine production by the NF-κB inhibitor metformin significantly improved radiotherapeutic performance in vitro and in vivo. With regard to clinical relevance, retrospective analyses of TCGA HNSCC data and an in-house HNSCC cohort revealed that elevated expression of CXCR2 and/or its ligands are associated with impaired treatment outcome. Collectively, our study identifies radiation-induced tumor cell senescence and the NF-κB-dependent production of distinct senescence-associated cytokines as critical drivers of radioresistance in HNSCC whose therapeutic targeting in the context of multi-modality treatment approaches should be further examined and may be of particular interest for the subgroup of patients with elevated expression of the CXCR2/ligand axis.
Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to ...automatically extract relevant features from the patient's image and perform a binary classification of the occurrence of a given clinical endpoint. In this work, a 2D-CNN and a 3D-CNN for the binary classification of distant metastasis (DM) occurrence in head and neck cancer patients were extended to perform time-to-event analysis. The newly built CNNs incorporate censoring information and output DM-free probability curves as a function of time for every patient. In total, 1037 patients were used to build and assess the performance of the time-to-event model. Training and validation was based on 294 patients also used in a previous benchmark classification study while for testing 743 patients from three independent cohorts were used. The best network could reproduce the good results from 3-fold cross validation Harrell's concordance indices (HCIs) of 0.78, 0.74 and 0.80 in two out of three testing cohorts (HCIs of 0.88, 0.67 and 0.77). Additionally, the capability of the models for patient stratification into high and low-risk groups was investigated, the CNNs being able to significantly stratify all three testing cohorts. Results suggest that image-based deep learning models show good reliability for DM time-to-event analysis and could be used for treatment personalisation.
•Heart exposure is a major cardiac risk factor in left-sided breast cancer survivors.•Deep inspiration breath-hold (DIBH) significantly reduces the exposure of the heart.•Patients with high ...cardiovascular risk and favourable tumour prognosis benefit most.•Risk modelling showed that age has only minor impact on the related cardiac risk.
Aim of the current comparative modelling study was to estimate the individual radiation-induced risk for death of ischaemic heart disease (IHD) under free breathing (FB) and deep inspiration breath-hold (DIBH) in a real-world population.
Eighty-nine patients with left-sided early breast cancer were enrolled in the prospective SAVE-HEART study. For each patient three-dimensional conformal treatment plans were created in FB and DIBH and corresponding radiation-induced risks of IHD mortality were estimated based on expected survival, individual IHD risk factors and the relative radiation-induced risk.
With the use of DIBH, mean heart doses were reduced by 35% (interquartile range: 23–46%) as compared to FB. Mean expected years of life lost (YLL) due to radiation-induced IHD mortality were 0.11 years in FB, and 0.07 years in DIBH. YLL were remarkably independent of age at treatment in patients with a favourable tumour prognosis. DIBH led to more pronounced reductions in YLL in patients with high baseline risk (0.08 years for upper vs 0.02 years for lower quartile), with favourable tumour prognosis (0.05 years for patients without vs 0.02 years for those with lymph-node involvement), and in patients with high mean heart doses in FB (0.09 years for doses >3 Gy vs 0.02 years for doses <1.5 Gy).
Ideally, the DIBH technique should be offered to all patients with left-sided breast cancer. However, highest benefits are expected for patients with a favourable tumour prognosis, high mean heart dose or high baseline IHD risk, independent of their age.
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