RENORT: a project to analyze patterns of care in radiation oncology in Spain

PurposeRENORT is an application (app) developed to assess the role of radiotherapy in the treatment of cancer using the oncology information systems (OIS).Methods/PatientsThe RENORT app was used to analyze the data for all patients seen and/or treated at six radiation oncology departments in Spain in 2019. This app can be used to extract the demographic data, treatment sequence, disease status, and radiotherapy treatments from the ARIA and Mosaiq OIS.ResultsA total of 6564 treatments were performed at these six centers in 2019. Most patients (56.9%) were males (females 43.1%). The mean patient age was 64.9 years. The most common treatment types and sites were as follows: metastases/palliative care (25.9%), followed by breast (19.0%), genitourinary (13.7%), lung (10.1%), head and neck (6.0%), rectal (6.0%), gynecological (4.9%), and other (< 4%) cancers. Distribution by disease stage was as follows: breast cancer: 75.5% early stage (stages 0, I, and II); lung: 63.1% advanced stage (III and IV); and head and neck: 72.1% advanced. Treatment intent was curative in 76.5% of cases and palliative in 23.5%. The most common techniques were intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) (41.4%), followed by three-dimensional conformal radiation therapy (3D-CRT) (39.2%); stereotactic body radiotherapy (SBRT) (8.1%); brachytherapy (5.5%); radiosurgery (2.1%); fractionated stereotactic radiotherapy to the brain (1.4%); and intraoperative radiotherapy (1.4%). Hypofractionation was used in 62.3% of curative treatments (mean number of fractions = 16.5).ConclusionsRENORT is a free app that is available for the two main oncology information systems used in most radiation oncology departments. This app has demonstrated the capacity to extract data from these systems, which in turns allows for a comprehensive analysis and better understanding of the role of radiotherapy in the treatment of cancer.

Characterization of imaging performance of a novel helical kVCT for use in image-guided and adaptive radiotherapy.

ClearRT helical kVCT imaging for the Radixact helical tomotherapy system recently received FDA approval and is available for clinical use. The system is intended to enhance image fidelity in radiation therapy treatment planning and delivery compared to the prior MV-based onboard imaging approach. The purpose of this work was to characterize the imaging performance of this system and compare this performance with that of clinical systems used in image-guided and/or adaptive radiotherapy (ART) or computed tomography (CT) simulation, including Radixact MVCT, TomoTherapy MVCT, Varian TrueBeam kV OBI CBCT, and the Siemens SOMATOM Definition Edge kVCT. A CT image quality phantom was scanned across clinically relevant acquisition modes for each system to evaluate image quality metrics, including noise, uniformity, contrast, spatial resolution, and CT number linearity. Similar noise levels were observed for ClearRT and Siemens Edge, whereas noise for the other systems was ∼1.5-5 times higher. Uniformity was best for Siemens Edge, whereas most scans for ClearRT exhibited a slight "cupping" or "capping" artifact. The ClearRT and Siemens Edge performed best for contrast metrics, which included low-contrast visibility and contrast-to-noise ratio evaluations. Spatial resolution was best for TrueBeam and Siemens Edge, whereas the three kVCT systems exhibited similar CT number linearity. Overall, these results provide an initial indication that ClearRT image quality is adequate for image guidance in radiotherapy and sufficient for delineating anatomic structures, thus enabling its use for ART. ClearRT also showed significant improvement over MVCT, which was previously the only onboard imaging modality available on Radixact. Although the acquisition of these scans does come at the cost of additional patient dose, reported CTDI values indicate a similar or generally reduced machine output for ClearRT compared to the other systems while maintaining comparable or improved image quality overall.

New target volume delineation and PTV strategies to further personalise radiotherapy.

Target volume delineation uncertainty (DU) is arguably one of the largest geometric uncertainties in radiotherapy that are accounted for using planning target volume (PTV) margins. Geometrical uncertainties are typically derived from a limited sample of patients. Consequently, the resultant margins are not tailored to individual patients. Furthermore, standard PTVs cannot account for arbitrary anisotropic extensions of the target volume originating from DU. We address these limitations by developing a method to measure DU for each patient by a single clinician. This information is then used to produce PTVs that account for each patient's unique DU, including any required anisotropic component. We do so using a two-step uncertainty evaluation strategy that does not rely on multiple samples of data to capture the DU of a patient's gross tumour volume (GTV) or clinical target volume. For simplicity, we will just refer to the GTV in the following. First, the clinician delineates two contour sets; one which bounds all voxels believed to have a probability of belonging to the GTV of 1, while the second includes all voxels with a probability greater than 0. Next, one specifies a probability density function for the true GTV boundary position within the boundaries of the two contours. Finally, a patient-specific PTV, designed to account for all systematic errors, is created using this information along with measurements of the other systematic errors. Clinical examples indicate that our margin strategy can produce significantly smaller PTVs than the van Herk margin recipe. Our new radiotherapy target delineation concept allows DUs to be quantified by the clinician for each patient, leading to PTV margins that are tailored to each unique patient, thus paving the way to a greater personalisation of radiotherapy.

Selective Internal Radiation Therapy for Hepatocellular Carcinoma Across the Barcelona Clinic Liver Cancer Stages.

BACKGROUND: Hepatocellular carcinoma (HCC) is the second most common lethal cancer, and there is a need for effective therapies. Selective internal radiation therapy (SIRT) has been increasingly used, but is not supported by guidelines due to a lack of solid evidence. AIMS: Determine the efficacy and safety of SIRT in HCC across the Barcelona Clinic Liver Cancer (BCLC) stages A, B, and C. METHODS: Consecutive patients that received SIRT between 2006 and 2016 at two centers in Canada were evaluated. RESULTS: We analyzed 132 patients, 12 (9%), 62 (47%), and 58 (44%) belonged to BCLC stages A, B, and C; mean age was 61.2 (SD ± 9.2), and 89% were male. Median survival was 12.4 months (95% CI 9.6-16.6), and it was different across the stages: 59.7 (95% CI NA), 12.8 (95% CI 10.2-17.5), and 9.3 months (95% CI 5.9-11.8) in BCLC A, B, and C, respectively (p = 0.009). Independent factors associated with survival were previous HCC treatment (HR 2.01, 95% CI 1.23-3.27, p = 0.005), bi-lobar disease (HR 2.25, 95% CI 1.30-3.89, p = 0.003), ascites (HR 1.77, 95% CI 0.99-3.13, p = 0.05), neutrophil-to-lymphocyte ratio (HR 1.11, 95% CI 1.02-1.20, p = 0.01), Albumin-Bilirubin (ALBI) grade-3 (HR 2.69, 95% CI 1.22-5.92, p = 0.01), tumor thrombus (HR 2.95, 95% CI 1.65-5.24, p < 0.001), and disease control rate (HR 0.62, 95% CI 0.39-0.96, p = 0.03). Forty-four (33%) patients developed severe adverse events, and ALBI-3 was associated with higher risk of these events. CONCLUSIONS: SIRT has the potential to be used across the BCLC stages in cases with preserved liver function. When using it as a rescue treatment, one should consider variables reflecting liver function, HCC extension, and systemic inflammation, which are associated with mortality.

Prone Positioning With Deep Inspiration Breath Hold for Left Breast Radiotherapy.

BACKGROUND: With advances in treatment, outcomes for early-stage breast cancer are improving. We investigated the combination of prone position and deep inspiration breath hold to decrease cardiac doses for left-sided breast radiotherapy. MATERIAL AND METHODS: Fifteen patients with left-sided breast cancer were enrolled on a single-institution prospective study. Each patient underwent 2 prone positioned computed tomography simulation scans utilizing free breathing and breath-hold. Separate treatment plans for each computed tomography simulation scan were created using tangential fields, and heart and left lung doses were compared between free breathing and breath-hold plans. The technique with the lower mean dose for the heart was used for treatment. All patients were treated with a hypofractionated regimen of 40 to 42 Gy in 15 to 16 fractions, followed by a lumpectomy cavity boost of 10 Gy in 5 fractions when indicated. Wilcoxon paired signed rank tests and paired t tests were performed for statistical analysis of dosimetric endpoints. RESULTS: The median age of our patients was 58 years (range, 40-72 years). One patient was not able to tolerate prone positioning at simulation, leaving 14 patients with evaluable paired scans. The average mean heart dose with free breathing and with breath-hold was 0.93 Gy and 0.72 Gy, respectively (P = .0063). The average max heart dose with free breathing and with breath-hold was 15.70 Gy and 7.19 Gy, respectively (P = .001). The average mean left lung dose with free breathing and with breath-hold was 0.65 Gy and 0.88 Gy, respectively (P = .011). CONCLUSIONS: Our results indicate that breath-hold using the real-time position management system may provide additional cardiac dose reduction in patients receiving prone left-breast radiotherapy treated with tangential fields.

Conformal Avoidance of Normal Organs at Risk by Perfusion-Modulated Dose Sculpting in Tumor Single-Dose Radiation Therapy.

PURPOSE: Although 24 Gy single-dose radiation therapy (SDRT) renders >90% 5-year local relapse-free survival in human solid tumor lesions, SDRT delivery is not feasible in ∼50% of oligometastatic lesions owing to interference by dose/volume constraints of a serial organ at risk (OAR). Conformal OAR avoidance is based on a hypothetical model positing that the recently described SDRT biology specifically permits volumetric subdivision of the SDRT dose, such that high-intensity vascular drivers of SDRT lethality, generated within a major tumor subvolume exposed to a high 24 Gy dose (high-dose planning target volume [PTVHD]), would equilibrate SDRT signaling intensity throughout the tumor interstitial space, rendering bystander radiosensitization of a minor subvolume (perfusion-modulated dose sculpting PTV [PTVPMDS]), dose-sculpted to meet a serial OAR dose/volume constraint. An engineered PTVPMDS may thus yield tumor ablation despite PMDS dose reduction and conformally avoiding OAR exposure to a toxic dose. METHODS AND MATERIALS: Dose fall-off within the PTVPMDS penumbra of oligometastatic lesions was planned and delivered by intensity modulated inverse dose painting. SDRT- and SDRT-PMDS-treated lesions were followed with periodic positron emission tomography/computed tomography imaging to assess local tumor control. RESULTS: Cumulative baseline 5-year local relapse rates of oligometastases treated with 24 Gy SDRT alone (8% relapses, n = 292) were similar in moderate PTVPMDS dose-sculpted (23-18 Gy, n = 76, 11% relapses, P = .36) and extreme dose-sculpted (<18 Gy, n = 61, 14% relapses, P = .29) lesions, provided the major 24 Gy PTVHD constituted ≥60% of the total PTV. In contrast, 28% of local relapses occurred in 26 extreme dose-sculpted PTVPMDS lesions when PTVHD constituted <60% of the total PTV (P = .004), suggesting a threshold for the PTVPMDS bystander effect. CONCLUSION: The study provides compelling clinical support for the bystander radiosensitization hypothesis, rendering local cure of tumor lesions despite a ≥25% PTVPMDS dose reduction of the 24 Gy PTVHD dose, adapted to conformally meet OAR dose/volume constraints. The SDRT-PMDS approach thus provides a therapeutic resolution to otherwise radioablation-intractable oligometastatic disease.

Selective internal radiation therapy of hepatic tumors: Morphologic and functional imaging for voxel-based computer-aided dosimetry.

INTRODUCTION: Selective Internal Radiation Therapy (SIRT) is used for the treatment of hepatic tumors. The aim of this retrospective study was to compare two dosimetric approaches based on 99mTc-MAA SPECT/CT and 90Y PET/CT, using Simplicit90Y™ versus the supplier suggested method of activity calculation. MATERIAL AND METHODS: A total of 19 patients underwent 21 SIRT after baseline angiography and 99mTc-MAA SPECT/CT, followed by 90Y PET/CT. Overlap between 99mTc-MAA and 90Y-microspheres was quantified with different thresholds isocontours. The perfused volume and tumor absorbed dose were estimated using Simplicit90Y™ based on SPECT/CT and PET/CT, then compared with the supplier suggested method. These data were related to overall survival to evaluate their prognostic impact. RESULTS: The overlap between PET/CT and SPECT/CT was dependent on thresholds, decreasing with an increasing threshold. The overlap between the 99mTc-MAA and 90Y-microspheres biodistributions versus the tumor distribution on morphological imaging was suboptimal, in particular for small tumor volume. The tumor absorbed dose estimated after 90Y PET/CT was not different from tumor absorbed dose estimated after SPECT/CT. The Perfused lobe absorbed dose was significantly lower while the volume of the perfused lobe was significantly higher when estimated by Simplicit90Y™ compared to the supplier suggested conventional approach. A statistical parameter based on overlap between tumor and 90Y-microspheres distribution as well as tumoral dosimetry was significantly related to the overall survival. CONCLUSION: Post-treatment imaging remains paramount to estimate the irradiation dosimetry, due to an imperfect overlap. The perfused volume could be estimated from functional imaging, given its impact on dosimetry. Finally, survival seems related to tumoral overlap and dosimetry.

Use of radiomics in the radiation oncology setting: Where do we stand and what do we need?

Radiomics is a field that has been growing rapidly for the past ten years in medical imaging and more particularly in oncology where the primary objective is to contribute to personalised and predictive medicine. This short review aimed at providing some insights regarding the potential value of radiomics for cancer patients treated with radiotherapy. Radiomics may contribute to each stage of the patients' management: diagnosis, planning, treatment monitoring and post-treatment follow-up (toxicity and response). However, its applicability in clinical routine is currently hindered by several factors, including lack of automation, standardisation and harmonisation. A major effort must be carried out to automate the workflow, standardise radiomics good practices and carry out large-scale studies before any transfer to daily clinical practice.

[PET technology: Latest advances and potential impact on radiotherapy]. / Tomographie par émission de positons (TEP) pour la radiothérapie : technique et innovations.

Multimodal imaging has become a standard for planning radiation therapy via magnetic resonance imaging (MRI) or positron emission tomography (PET) in many cancers. However, its use is now old, and its impact has not been much discussed in light of technological improvements in imaging and advances in radiotherapy. However, in 20 years, the exclusive functional imaging has been replaced by hybrid imaging (functional and anatomical) with successive improvements (flight time, detector modifications, digitisation, etc.) have enabled us to go from centimetric resolution to the current 3 to 4mm resolution. This article will specifically review PET technology, its latest advances and the potential impact on radiotherapy, particularly head and neck cancers.

Initial clinical experience of Stereotactic Body Radiation Therapy (SBRT) for liver metastases, primary liver malignancy, and pancreatic cancer with 4D-MRI based online adaptation and real-time MRI monitoring using a 1.5 Tesla MR-Linac.

PURPOSE/OBJECTIVES: Recently a 1.5 Tesla MR Linac has been FDA approved and is commercially available. Clinical series describing treatment methods and outcomes for upper abdominal tumors using a 1.5 Tesla MR Linac are lacking. We present the first clinical series of upper abdominal tumors treated using a 1.5 Tesla MR Linac along with the acquisition of intra-treatment quantitative imaging. MATERIALS/METHODS: 10 patients with abdominal tumors were treated at our institution. Each patient enrolled in an IRB approved advanced imaging protocol. Both daily real-time adaptive and non-adaptive methods were used, and selection criteria are described. Adaptive plans were based on pre-beam motion-averaged or mid-position images derived from respiratory-correlated 4D-MRI. Quantitative intravoxel incoherent motion diffusion-weighted imaging and T2 mapping were acquired during plan adaptation. Real-time motion monitoring using cine MRI was performed during beam-on. RESULTS: Median patient age was 68.2, five patients were female. Tumor types included liver metastatic lesions from melanoma and sarcoma, primary liver hepatocellular carcinoma (HCC), and regional abdominal tumors included pancreatic metastatic lesions from renal cell carcinoma (RCC) along with two cases of recurrent pancreatic cancer. Doses included 30 Gy in 6 fractions, 33 Gy in 5 fractions, 50 Gy in 5 fractions, 45 Gy in 3 fractions, and 60 Gy in 3 fractions, depending on the location and clinical circumstances. Treatments were feasible and were successfully completed in all patients without significant acute toxicity, technical complications, or need for back up CT based treatment plans. CONCLUSIONS: We present a first clinical series of patients treated for pancreatic tumors, primary liver tumors, and secondary liver tumors with a 1.5 Tesla MR Linear accelerator using adapt-to-position and adapt-to-shape strategies. Treatments were well tolerated by all patients. Acquisition of fully quantitative MR imaging was feasible during the course of the treatment delivery workflow without extending overall treatment times.

Feasibility of Multiparametric Positron Emission Tomography/Magnetic Resonance Imaging as a One-Stop Shop for Radiation Therapy Planning for Patients with Head and Neck Cancer.

PURPOSE: Multiparametric positron emission tomography (PET)/magnetic resonance imaging (MRI) as a one-stop shop for radiation therapy (RT) planning has great potential but is technically challenging. We studied the feasibility of performing multiparametric PET/MRI of patients with head and neck cancer (HNC) in RT treatment position. As a step toward planning RT based solely on PET/MRI, a deep learning approach was employed to generate synthetic computed tomography (sCT) from MRI. This was subsequently evaluated for dose calculation and PET attenuation correction (AC). METHODS AND MATERIALS: Eleven patients, including 3 pilot patients referred for RT of HNC, underwent PET/MRI in treatment position after a routine fluorodeoxyglucose-PET/CT planning scan. The PET/MRI scan protocol included multiparametric imaging. A convolutional neural network was trained in a leave-one-out process to predict sCT from the Dixon MRI. The clinical CT-based dose plans were recalculated on sCT, and the plans were compared in terms of relative differences in mean, maximum, near-maximum, and near-minimum absorbed doses for different volumes of interest. Comparisons between PET with sCT-based AC and PET with CT-based AC were assessed based on the relative differences in mean and maximum standardized uptake values (SUVmean and SUVmax) from the PET-positive volumes. RESULTS: All 11 patients underwent PET/MRI in RT treatment position. Apart from the 3 pilots, full multiparametric imaging was completed in 45 minutes for 7 out of 8 patients. One patient terminated the examination after 30 minutes. With the exception of 1 patient with an inserted tracheostomy tube, all dosimetric parameters of the sCT-based dose plans were within ±1% of the CT-based dose plans. For PET, the mean difference was 0.4 ± 1.2% for SUVmean and -0.5 ± 1.0% for SUVmax. CONCLUSIONS: Performing multiparametric PET/MRI of patients with HNC in RT treatment position was clinically feasible. The sCT generation resulted in AC of PET and dose calculations sufficiently accurate for clinical use. These results are an important step toward using multiparametric PET/MRI as a one-stop shop for personalized RT planning.

A Multicenter, International Collaborative Study for American Joint Committee on Cancer Staging of Retinoblastoma: Part II: Treatment Success and Globe Salvage.

PURPOSE: To evaluate the ability of the American Joint Committee on Cancer (AJCC) 8th edition to predict local tumor control and globe salvage for children with retinoblastoma (RB). DESIGN: International, multicenter, registry-based retrospective case series. PARTICIPANTS: A total of 2854 eyes of 2097 patients from 18 ophthalmic oncology centers from 13 countries over 6 continents. METHODS: International, multicenter, registry-based data were pooled from patients enrolled between January 2001 and December 2013. All RB eyes with adequate records to allow tumor staging by the AJCC 8th edition criteria and follow-up to ascertain treatment outcomes were included. MAIN OUTCOME MEASURES: Globe-salvage rates were estimated by AJCC clinical (cTNMH) categories and tumor laterality. Local treatment failure was defined as use of enucleation or external beam radiation therapy (EBRT), with or without plaque brachytherapy or intra-arterial chemotherapy (IAC). RESULTS: Unilateral RB occurred in 1340 eyes (47%). Among the 2854 eyes, tumor categories were cT1 to cT4 in 696 eyes (24%), 1334 eyes (47%), 802 eyes (28%), and 22 eyes (1%), respectively. Of these, 1275 eyes (45%) were salvaged, and 1179 eyes (41%) and 400 eyes (14%) underwent primary and secondary enucleation, respectively. The 2- and 5-year Kaplan-Meier cumulative globe-salvage rates without the use of EBRT by cTNMH categories were 97% and 96% for category cT1a tumors, 94% and 88% for cT1b tumors, 68% and 60% for cT2a tumors, 66% and 57% for cT2b tumors, and 32% and 25% for cT3 tumors, respectively. Risk of local treatment failure increased with increasing cT category (P < 0.001). Cox proportional hazards regression analysis confirmed a higher risk of local treatment failure in categories cT1b (hazard ratio [HR], 3.5; P = 0.004), cT2a (HR, 15.1; P < 0.001), cT2b (HR, 16.4; P < 0.001), and cT3 (HR, 45.0; P < 0.001) compared with category cT1a. Use of plaque brachytherapy and IAC improved local tumor control in categories cT1a (P = 0.031) and cT1b (P < 0.001). CONCLUSIONS: Multicenter, international, internet-based data sharing validated the 8th edition AJCC RB staging to predict globe-salvage in a large, heterogeneous, real-world patient population with RB.

A motion prediction confidence estimation framework for prediction-based radiotherapy gating.

PURPOSE: Motion prediction can compensate for latency in image-guided radiotherapy and has been an active area of research. However, motion predictions are subject to error and variations. We have developed and evaluated a novel motion prediction confidence estimation framework to improve the efficacy and robustness of prediction-based radiotherapy gating decision-making. The specific scenario of adaptive gating in magnetic resonance imaging (MRI)-guided radiotherapy is studied as an example, but the method generalizes to other modalities and motion management setups. METHODS: The proposed prediction confidence estimator is based on a generic training/testing paradigm and consists of a weighted combination of three components: the prediction model's goodness of fit, variation in the prediction using a leave-one-out process and the velocity of the tracked target. Roughly, these terms quantify respectively the consistency between prediction and the training data, the robustness of model inference, and the stability due to target speed. The weight parameters and the action level in triggering beam-off decision are optimized. The method is assessed and validated in 8 healthy volunteer and 13 patient studies using a 0.35T MRI-guided radiotherapy system predicting 0.25-0.33 s ahead. The effect of the action level on the predicted gating decision accuracy, beam-on positive predictive value (PPV) and median distance between the predicted and ground-truth target centroids were evaluated. Statistical significance was evaluated using a paired t-test. The tradeoff between these performance metrics and gating duty cycle was assessed. RESULTS: Use of the confidence estimator threshold increased gating accuracy by up to 2.42%, increased PPV by up to 3.00%, and reduced the median centroid distance up to 0.28 mm. The confidence estimator threshold on average increased gating accuracy to 96.5% (P = 2.08 × 10-4 ), increased PPV to 96.7% (P = 1.46 × 10-5 ), reduced the median centroid distance to 0.54 mm (P = 1.71 × 10-5 ) at the cost of reducing the gating duty cycle by 14.3% to 48.5%. Hyperparameter tuning revealed that contrary to intuition, the velocity term offered only minimal performance improvement in some cases but also introduced potential stability issues. The combination of goodness of fit and leave-one-out prediction variation provided the most effective confidence estimator, yielding universally better performance in gating decisions. CONCLUSION: Confidence estimation utilizing prediction model fitness criterion and validation principles can complement prediction methods to guide MRI-guided radiotherapy gating. Results from both volunteer and patient studies showed improved gating quality.

Genomics models in radiotherapy: From mechanistic to machine learning.

Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.

Accurate 3D-dose-based generation of MLC segments for robotic radiotherapy.

Radiotherapy treatment planning requires accurate modeling of the delivered patient dose, including radiation scatter effects, multi-leaf collimator (MLC) leaf transmission, interleaf-leakage, etc. In fluence map optimization (FMO), a simple dose model is used to first generate an intermediate plan based on pencil-beams. In a second step (segmentation phase), this intermediate plan is then converted into a deliverable treatment plan with MLC segments. In this paper, we investigate novel approaches for the use of a clinical dose engine (CDE) for segmentation of FMO plans in robotic radiotherapy. Segments are sequentially added to the plan. Generation of each next segment is based on the total 3D dose distribution, resulting from already selected segments and the desired FMO dose, considering all treatment beams as candidates for delivery of the new segment. Three versions of the segmentation algorithm were investigated with differences in the integration of the CDE. The combined use of pencil-beams and segments in a segmentation method is non-trivial. Therefore, new methods were developed for the use of segment doses calculated with the CDE in combination with pencil-beams, used for the selection of new segments. For 20 patients with prostate cancer and 12 with liver cancer, segmented plans were compared with FMO plans. All three versions of the proposed segmentation algorithm could well mimic FMO dose distributions. Segmentation with a fully integrated CDE provided the best plan quality and lowest numbers of monitor units and segments at the cost of increased calculation time.

The emerging roles of artificial intelligence in cancer drug development and precision therapy.

Artificial intelligence (AI) has strong logical reasoning ability and independent learning ability, which can simulate the thinking process of the human brain. AI technologies such as machine learning can profoundly optimize the existing mode of anticancer drug research. But at present AI also has its relative limitation. In this paper, the development of artificial intelligence technology such as deep learning and machine learning in anticancer drug research is reviewed. At the same time, we look forward to the future of AI.

Evaluation of target volume margins for radiotherapy of prostate implanted with fiducial markers.

The planning target volume (PTV) depends on the method of radiotherapy guidance. This study aimed to measure the systemic and random errors using an online marker matching and offline bone structure matching to estimate PTVmarker, PTVbone, or PTVlaser for treatment verification and radiotherapy guidance, especially in centers lacking radiotherapy fiducial markers (FMs). Thirty patients with localized prostate cancer who were treated with FM-based dose escalation protocol were included. The initial set-up was done with laser marks and daily megavoltage images were acquired. The systematic and random errors were calculated. PTVmarker, defined as the sum of maximum marker migration, and PTV calculated to compensate for the difference between online marker matching and offline analysis of marker matching. PTVmarker was added to estimated PTV from online marker matching to obtain PTVlaser. PTVskin marks migration, was calculated and deducted from PTVlaser to acquire PTVbone. The mean maximum marker migration was 2 ± 1.2 mm. The resultant values of PTVmarker were 2.7 ± 0.6 mm, 3.3 ± 1.1 mm, and 4.4 ± 2.2 mm, in the lateral (lat.), longitudinal (long) & vertical (vert.) directions, respectively, whereas values of PTVlaser were 13 ± 0.6 mm, 17.7 ± 1.1 mm, and 15.8 ± 2.2 mm, and PTVbone were 5.9 ± 0.6 mm, 8.6 ± 1.1 mm, 7.2 ± 2.2 mm, respectively, in the lat., long., and vert. directions. Our results show that PTV needed with FM-based image guidance ranged between 3 and 4 mm in the three cardinal directions, was 10 mm smaller than that required with laser skin marks guidance, and narrower by 5 mm compared to that obtained by offline bone structure image matching.

Correlation of intensity-modulated radiation therapy at a specific radiation dose with the prognosis of nasal mucous damage after radiotherapy.

Objective of the present study was to investigate the tolerant radiation dose of nasal mucosa by observing and analyzing patients who received intensity-modulated radiation therapy (IMRT). Patients with nasopharyngeal carcinoma (N = 66) were selected for this study. The modified saccharin assay, endoscopy test, magnetic resonance imaging, and sino-nasal outcome test-20 (SNOT-20) survey were performed for the patients before and at 0 (T0), 3 (T1), 6 (T2), and 12 (T3) months after radiotherapy. The threshold doses of IMRT before radiotherapy and at T0, T1, T2, and T3 were determined as, respectively, 37 Gy, 37 Gy, 39 Gy, and 37 Gy for the saccharin test; 38 Gy, 37 Gy, 40 Gy, and 38 Gy for the endoscopy test; and 39 Gy, 37 Gy, 39 Gy, and 39 Gy for the nasal-related symptom scoring test. The modified saccharin assay, endoscopy test, and SNOT-20 survey revealed that a low dose (< threshold dose) of IMRT was associated with higher mucocilia transport rate (MRT), better endoscopy test score, and improved SNOT-20 score. The patients who received IMRT at a dose less than the threshold had the least damaged nasal mucosa morphology, and functional impairment scores were highest at T1 of IMRT. We conclude that nasal mucosa showed the most serious damage within 3 months after IMRT. If the radiation dose can be controlled within the threshold, the nasal mucosa can recover in the following few months, but recovery will be difficult otherwise.

The Feasibility of Implementing Deep Inspiration Breath-Hold for Pediatric Radiation Therapy.

PURPOSE: Radiation therapy delivery during deep inspiration breath-hold (DIBH) reduces the irradiation of the heart and lungs and is therefore recommended for adults with mediastinal lymphoma. However, no studies have addressed the use of DIBH in children. This pilot study investigates the feasibility of and compliance with DIBH in children. METHODS AND MATERIALS: Children from the age of 5 years were recruited to a training session to assess their ability to perform DIBH. No children received radiation therapy. The children were placed in a potential radiation therapy position. The DIBH was voluntary and monitored using an optical surface system providing visual feedback. Children who performed 3 stable DIBHs of 20 seconds each and remained motionless were deemed DIBH compliant. Compliance, equipment suitability, and coaching were further assessed in a semistructured interview. RESULTS: We included 33 children (18 healthy and 15 hospitalized children with cancer) with a mean age of 8.5 years (range, 5-15). A total of 28 (85%) children were DIBH compliant. Twenty children were deemed immediately DIBH compliant, and 8 were deemed conditionally DIBH compliant, as DIBH compliance was presumed with custom-made immobilization and/or additional DIBH training. Mean age of the DIBH-compliant and the non-DIBH-compliant children was 8.9 years (range, 5-15) and 6 years (range, 5-9), respectively. Only 1 of 15 hospitalized children was not DIBH compliant and only 1 of all 33 children was unable to grasp the DIBH concept. The available DIBH equipment was suitable for children, and 94% reported that they were happy with training and performing DIBH. CONCLUSIONS: This pilot study demonstrated that children from the age of 5 years can potentially comply with the DIBH technique and perform stable and reproducible DIBHs suitable for radiation therapy. Custom-made immobilization and adequate training will potentially increase DIBH compliance. A prospective clinical trial (NCT03315546), investigating the dosimetric benefit of radiation therapy delivery in DIBH compared with free breathing with pediatric patients, has been initiated.