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BACKGROUND AND PURPOSE: Brain tumors are in general treated with a maximal safe resection followed by radiotherapy of remaining tumor including the resection cavity (RC) and chemotherapy. Anatomical changes of the RC during radiotherapy can have impact on the coverage of the target volume. The aim of the current study was to quantify the potential changes of the RC and to identify risk factors for RC changes. MATERIALS AND METHODS: Sixteen patients treated with pencil beam scanning proton therapy between October 2019 and April 2020 were retrospectively analyzed. The RC was delineated on pre-treatment computed tomography (CT) and magnetic resonance imaging, and weekly CT-scans during treatment. Isotropic expansions were applied to the pre-treatment RC (1-5 mm). The percentage of volume of the RC during treatment within the expanded pre-treatment volumes was quantified. Potential risk factors (volume of RC, time interval surgery-radiotherapy and relationship of RC to the ventricles) were evaluated using Spearman's rank correlation coefficient. RESULTS: The average variation in relative RC volume during treatment was 26.1% (SD 34.6%). An expansion of 4 mm was required to cover > 95% of the RC volume in > 90% of patients. There was a significant relationship between the absolute volume of the pre-treatment RC and the volume changes during treatment (Spearman's ρ = - 0.644; p = 0.007). CONCLUSION: RCs are dynamic after surgery. Potentially, an additional margin in brain cancer patients with an RC should be considered, to avoid insufficient target coverage. Future research on local recurrence patterns is recommended.
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Neoplasias Encefálicas , Radioterapia de Intensidad Modulada , Humanos , Estudios Retrospectivos , Terapia Combinada , Tomografía Computarizada por Rayos X , Planificación de la Radioterapia Asistida por Computador , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/radioterapia , Neoplasias Encefálicas/cirugía , Encéfalo/diagnóstico por imagen , Encéfalo/cirugía , Dosificación RadioterapéuticaRESUMEN
PURPOSE: 2-[18F]FDG PET/CT is of utmost importance for radiation treatment (RT) planning and response monitoring in lung cancer patients, in both non-small and small cell lung cancer (NSCLC and SCLC). This topic has been addressed in guidelines composed by experts within the field of radiation oncology. However, up to present, there is no procedural guideline on this subject, with involvement of the nuclear medicine societies. METHODS: A literature review was performed, followed by a discussion between a multidisciplinary team of experts in the different fields involved in the RT planning of lung cancer, in order to guide clinical management. The project was led by experts of the two nuclear medicine societies (EANM and SNMMI) and radiation oncology (ESTRO). RESULTS AND CONCLUSION: This guideline results from a joint and dynamic collaboration between the relevant disciplines for this topic. It provides a worldwide, state of the art, and multidisciplinary guide to 2-[18F]FDG PET/CT RT planning in NSCLC and SCLC. These practical recommendations describe applicable updates for existing clinical practices, highlight potential flaws, and provide solutions to overcome these as well. Finally, the recent developments considered for future application are also reviewed.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Fluorodesoxiglucosa F18 , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/radioterapia , Tomografía Computarizada por Tomografía de Emisión de Positrones , Tomografía de Emisión de Positrones/métodosRESUMEN
OBJECTIVE: As preservation of cognitive functioning increasingly becomes important in the light of ameliorated survival after intracranial tumor treatments, identification of eloquent brain areas would enable optimization of these treatments. METHODS: This cohort study enrolled adult intracranial tumor patients who received neuropsychological assessments pre-irradiation, estimating processing speed, verbal fluency and memory. Anatomical magnetic resonance imaging scans were used for multivariate voxel-wise lesion-symptom predictions of the test scores (corrected for age, gender, educational level, histological subtype, surgery, and tumor volume). Potential effects of histological and molecular subtype and corresponding WHO grades on the risk of cognitive impairment were investigated using Chi square tests. P-values were adjusted for multiple comparisons (p < .001 and p < .05 for voxel- and cluster-level, resp.). RESULTS: A cohort of 179 intracranial tumor patients was included [aged 19-85 years, median age (SD) = 58.46 (14.62), 50% females]. In this cohort, test-specific impairment was detected in 20-30% of patients. Higher WHO grade was associated with lower processing speed, cognitive flexibility and delayed memory in gliomas, while no acute surgery-effects were found. No grading, nor surgery effects were found in meningiomas. The voxel-wise analyses showed that tumor locations in left temporal areas and right temporo-parietal areas were related to verbal memory and processing speed, respectively. INTERPRETATION: Patients with intracranial tumors affecting the left temporal areas and right temporo-parietal areas might specifically be vulnerable for lower verbal memory and processing speed. These specific patients at-risk might benefit from early-stage interventions. Furthermore, based on future validation studies, imaging-informed surgical and radiotherapy planning could further be improved.
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Neoplasias Encefálicas , Glioma , Neoplasias Meníngeas , Femenino , Humanos , Adulto , Masculino , Estudios de Cohortes , Neoplasias Encefálicas/complicaciones , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/patología , Glioma/patología , Pruebas Neuropsicológicas , Imagen por Resonancia Magnética/métodosRESUMEN
OBJECTIVE: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data. METHODS: Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2Wvolume/T2Wentropy/ADCmean/SUVmean/TLG/CTmean-HU) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an 'independent' dataset. RESULTS: When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture). CONCLUSION: In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research. KEY POINTS: ⢠Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. ⢠However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. ⢠Predictive performance of our optimal model-combining clinical baseline variables with global quantitative tumour features-was encouraging (AUC 0.83), warranting further research in this direction on a larger scale.
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Tomografía Computarizada por Tomografía de Emisión de Positrones , Neoplasias del Recto , Quimioradioterapia , Fluorodesoxiglucosa F18 , Humanos , Imagen por Resonancia Magnética , Terapia Neoadyuvante , Tomografía de Emisión de Positrones , Neoplasias del Recto/diagnóstico por imagen , Neoplasias del Recto/terapia , Estudios Retrospectivos , Resultado del TratamientoRESUMEN
BACKGROUND AND PURPOSE: Reducing breathing motion in radiotherapy (RT) is an attractive strategy to reduce margins and better spare normal tissues. The objective of this prospective study (NCT03729661) was to investigate the feasibility of irradiation of non-small cell lung cancer (NSCLC) with visually guided moderate deep inspiration breath-hold (IBH) using nasal high-flow therapy (NHFT). MATERIAL AND METHODS: Locally advanced NSCLC patients undergoing photon RT were given NHFT with heated humidified air (flow: 40 L/min with 80% oxygen) through a nasal cannula. IBH was monitored by optical surface tracking (OST) with visual feedback. At a training session, patients had to hold their breath as long as possible, without and with NHFT. For the daily cone beam CT (CBCT) and RT treatment in IBH, patients were instructed to keep their BH as long as it felt comfortable. OST was used to analyze stability and reproducibility of the BH, and CBCT to analyze daily tumor position. Subjective tolerance was measured with a questionnaire at 3 time points. RESULTS: Of 10 included patients, 9 were treated with RT. Seven (78%) completed the treatment with NHFT as planned. At the training session, the mean BH length without NHFT was 39 s (range 15-86 s), and with NHFT 78 s (range 29-223 s) (p = .005). NHFT prolonged the BH duration by a mean factor of 2.1 (range 1.1-3.9s). The mean overall stability and reproducibility were within 1 mm. Subjective tolerance was very good with the majority of patients having no or minor discomfort caused by the devices. The mean inter-fraction tumor position variability was 1.8 mm (-1.1-8.1 mm;SD 2.4 mm). CONCLUSION: NHFT for RT treatment of NSCLC in BH is feasible, well tolerated and significantly increases the breath-hold duration. Visually guided BH with OST is stable and reproducible. We therefore consider this an attractive patient-friendly approach to treat lung cancer patients with RT in BH.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Contencion de la Respiración , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Humanos , Neoplasias Pulmonares/radioterapia , Estudios Prospectivos , Planificación de la Radioterapia Asistida por Computador , Reproducibilidad de los ResultadosRESUMEN
BACKGROUND: The presence of lymph node metastasis (LNmets) is a poor prognostic factor in oesophageal cancer (OeC) patients treated with neoadjuvant chemoradiotherapy (nCRT) followed by surgery. Tumour regression grade (TRG) in LNmets has been suggested as a predictor for survival. The aim of this study was to investigate whether TRG in LNmets is related to their location within the radiotherapy (RT) field. METHODS: Histopathological TRG was retrospectively classified in 2565 lymph nodes (LNs) from 117 OeC patients treated with nCRT and surgery as: (A) no tumour, no signs of regression; (B) tumour without regression; (C) viable tumour and regression; and (D) complete response. Multivariate survival analysis was used to investigate the relationship between LN location within the RT field, pathological TRG of the LN and TRG of the primary tumour. RESULTS: In 63 (54%) patients, viable tumour cells or signs of regression were seen in 264 (10.2%) LNs which were classified as TRG-B (n = 56), C (n = 104) or D (n = 104) LNs. 73% of B, C and D LNs were located within the RT field. There was a trend towards a relationship between LN response and anatomical LN location with respect to the RT field (p = 0.052). Multivariate analysis showed that only the presence of LNmets within the RT field with TRG-B is related to poor overall survival. CONCLUSION: Patients have the best survival if all LNmets show tumour regression, even if LNmets are located outside the RT field. Response in LNmets to nCRT is heterogeneous which warrants further studies to better understand underlying mechanisms.
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Quimioradioterapia , Neoplasias Esofágicas , Ganglios Linfáticos , Neoplasias Esofágicas/patología , Neoplasias Esofágicas/terapia , Humanos , Ganglios Linfáticos/patología , Estudios Retrospectivos , Resultado del TratamientoRESUMEN
OBJECTIVES: To explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation. METHODS: Sixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV42%) and total lesion glycolysis (TLG). These features, together with sex, age, mrTN-stage ("baseline parameters") and the CRT-surgery interval were analysed using multivariable stepwise logistic regression. Outcome was a good (TRG 1-2) versus poor histopathological response. Performance (AUC) to predict response was compared for different combinations of baseline ± quantitative imaging parameters and performance in an 'independent' dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV). RESULTS: The optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors. CONCLUSIONS: A multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial. KEY POINTS: ⢠A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. ⢠mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. ⢠Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.
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Quimioradioterapia/métodos , Fluorodesoxiglucosa F18/administración & dosificación , Imágenes de Resonancia Magnética Multiparamétrica/métodos , Terapia Neoadyuvante/métodos , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Radiofármacos/administración & dosificación , Neoplasias del Recto/diagnóstico por imagen , Neoplasias del Recto/terapia , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estadificación de Neoplasias , Estudios RetrospectivosRESUMEN
Background: Selective avoidance aims at sparing functional lung regions. Here, we preferentially direct radiation to irreversibly nonfunctional lung areas based on planning CT imaging to reduce functional lung damage.Materials and methods: For 12 stage I-IV NSCLC patients, 5 lung substructures were segmented on the planning CT, combining voxels <-900HU, -900HU to -801HU, -800HU to -701HU, -700HU to -601HU and ≥-600HU (Level 1 to 5). Two VMAT plans were optimized: a reference plan blinded from substructures and a selective avoidance plan (AV) imposing gradually stricter constraints on Level 1-5, based on previously validated associations between lung subvolume baseline density and density increase (ΔHU) after treatment. Characteristics of treatment plans were evaluated, including subvolumes, dose, and predicted ΔHU (with reported 95% CI reflecting prediction model uncertainty).Results: Segmented substructures were on average 477 cc, 1157 cc, 484 cc, 69 cc, and 123 cc (Level 1-5). AV plans could spare Level 3-5, e.g., mean dose decrease of 3.5 Gy (range 0.6 Gy; 6.0 Gy) for Level 5, p<.001. This significantly reduced the average lung mass with predicted ΔHU>20HU by 12.5 g (95% CI: 5.4-16.9) and 27.1 g (95% CI: 10.2-32.9) for a median and upper 10th percentile patient susceptibility for damage simulation, respectively.Conclusions: Lung damage avoidance based on CT density is feasible and easy to implement. A biomarker providing a reliable selection of patients with high susceptibility for lung damage will be crucial to show the clinical relevance of this avoidance planning strategy.
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Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Neoplasias Pulmonares/radioterapia , Traumatismos por Radiación/prevención & control , Planificación de la Radioterapia Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/patología , Femenino , Humanos , Pulmón/patología , Pulmón/efectos de la radiación , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Masculino , Persona de Mediana Edad , Dosificación Radioterapéutica , Radioterapia de Intensidad Modulada , Adulto JovenRESUMEN
Introduction: Inter-observer variability (IOV) in target volume delineation is a well-documented source of geometric uncertainty in radiotherapy. Such variability has not yet been explored in the context of adaptive re-delineation based on imaging data acquired during treatment. We compared IOV in the pre- and mid-treatment setting using expert primary gross tumour volume (GTV) and clinical target volume (CTV) delineations in locoregionally advanced head-and-neck squamous cell carcinoma (HNSCC) and (non-)small cell lung cancer [(N)SCLC]. Material and methods: Five and six observers participated in the HNSCC and (N)SCLC arm, respectively, and provided delineations for five cases each. Imaging data consisted of CT studies partly complemented by FDG-PET and was provided in two separate phases for pre- and mid-treatment. Global delineation compatibility was assessed with a volume overlap metric (the Generalised Conformity Index), while local extremes of IOV were identified through the standard deviation of surface distances from observer delineations to a median consensus delineation. Details of delineation procedures, in particular, GTV to CTV expansion and adaptation strategies, were collected through a questionnaire. Results: Volume overlap analysis revealed a worsening of IOV in all but one case per disease site, which failed to reach significance in this small sample (p-value range .063-.125). Changes in agreement were propagated from GTV to CTV delineations, but correlation could not be formally demonstrated. Surface distance based analysis identified longitudinal target extent as a pervasive source of disagreement for HNSCC. High variability in (N)SCLC was often associated with tumours abutting consolidated lung tissue or potentially invading the mediastinum. Adaptation practices were variable between observers with fewer than half stating that they consistently adapted pre-treatment delineations during treatment. Conclusion: IOV in target volume delineation increases during treatment, where a disparity in institutional adaptation practices adds to the conventional causes of IOV. Consensus guidelines are urgently needed.
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Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Neoplasias de Cabeza y Cuello/radioterapia , Neoplasias Pulmonares/radioterapia , Planificación de la Radioterapia Asistida por Computador/estadística & datos numéricos , Carcinoma Pulmonar de Células Pequeñas/radioterapia , Carcinoma de Células Escamosas de Cabeza y Cuello/radioterapia , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/patología , Fraccionamiento de la Dosis de Radiación , Neoplasias de Cabeza y Cuello/diagnóstico por imagen , Neoplasias de Cabeza y Cuello/patología , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Variaciones Dependientes del Observador , Tomografía de Emisión de Positrones , Planificación de la Radioterapia Asistida por Computador/métodos , Carcinoma Pulmonar de Células Pequeñas/diagnóstico por imagen , Carcinoma Pulmonar de Células Pequeñas/patología , Carcinoma de Células Escamosas de Cabeza y Cuello/diagnóstico por imagen , Carcinoma de Células Escamosas de Cabeza y Cuello/patología , Tomografía Computarizada por Rayos X , Resultado del Tratamiento , Carga Tumoral/efectos de la radiaciónRESUMEN
BACKGROUND: Tumour hypoxia is associated with increased radioresistance and poor response to radiotherapy. Pre-treatment assessment of tumour oxygenation could therefore give the possibility to tailor the treatment by calculating the required boost dose needed to overcome the increased radioresistance in hypoxic tumours. This study concerned the derivation of a non-linear conversion function between the uptake of the hypoxia-PET tracer 18F-HX4 and oxygen partial pressure (pO2). MATERIAL AND METHODS: Building on previous experience with FMISO including experimental data on tracer uptake and pO2, tracer-specific model parameters were derived for converting the normalised HX4-uptake at the optimal imaging time point to pO2. The conversion function was implemented in a Python-based computational platform utilising the scripting and the registration modules of the treatment planning system RayStation. Subsequently, the conversion function was applied to determine the pO2 in eight non-small-cell lung cancer (NSCLC) patients imaged with HX4-PET before the start of radiotherapy. Automatic segmentation of hypoxic target volumes (HTVs) was then performed using thresholds around 10 mmHg. The HTVs were compared to sub-volumes segmented based on a tumour-to-blood ratio (TBR) of 1.4 using the aortic arch as the reference oxygenated region. The boost dose required to achieve 95% local control was then calculated based on the calibrated levels of hypoxia, assuming inter-fraction reoxygenation due to changes in acute hypoxia but no overall improvement of the oxygenation status. RESULTS: Using the developed conversion tool, HTVs could be obtained using pO2 a threshold of 10 mmHg which were in agreement with the TBR segmentation. The dose levels required to the HTVs to achieve local control were feasible, being around 70-80 Gy in 24 fractions. CONCLUSIONS: Non-linear conversion of tracer uptake to pO2 in NSCLC imaged with HX4-PET allows a quantitative determination of the dose-boost needed to achieve a high probability of local control.
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Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Imidazoles , Neoplasias Pulmonares/diagnóstico por imagen , Planificación de la Radioterapia Asistida por Computador/métodos , Triazoles , Hipoxia Tumoral , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Radioisótopos de Flúor , Humanos , Neoplasias Pulmonares/radioterapia , Tomografía de Emisión de Positrones/métodos , RadiofármacosRESUMEN
BACKGROUND: Radiomic features retrieved from standard CT-images have shown prognostic power in several tumor sites. In this study, we investigated the prognostic value of pretreatment CT radiomic features to predict overall survival of esophageal cancer patients after chemoradiotherapy. MATERIAL AND METHODS: Two datasets of independent centers were analyzed, consisting of esophageal cancer patients treated with concurrent chemotherapy (Carboplatin/Paclitaxel) and 41.4Gy radiotherapy, followed by surgery if feasible. In total, 1049 radiomic features were calculated from the primary tumor volume. Recursive feature elimination was performed to select the 40 most relevant predictors. Using these 40 features and six clinical variables as input, two random forest (RF) models predicting 3-year overall survival were developed. RESULTS: In total 165 patients from center 1 and 74 patients from center 2 were used. The radiomics-based RF model yielded an area under the curve (AUC) of 0.69 (95%CI 0.61-0.77), with the top-5 most important features for 3-year survival describing tumor heterogeneity after wavelet filtering. In the validation dataset, the RF model yielded an AUC of 0.61 (95%CI 0.47-0.75). Kaplan Meier plots were significantly different between risk groups in the training dataset (p = .027) and borderline significant in the validation dataset (p = .053). The clinical RF model yielded AUCs of 0.63 (95%CI 0.54-0.71) and 0.62 (95%CI 0.49-0.76) in the training and validation dataset, respectively. Risk groups did not reach a significant correlation with pathological response in the primary tumor. CONCLUSIONS: A RF model predicting 3-year overall survival based on pretreatment CT radiomic features was developed and validated in two independent datasets of esophageal cancer patients. The radiomics model had better prognostic power compared to the model using standard clinical variables.
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Neoplasias Esofágicas/mortalidad , Neoplasias Esofágicas/terapia , Modelos Biológicos , Tomografía Computarizada por Rayos X/métodos , Adulto , Anciano , Anciano de 80 o más Años , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Área Bajo la Curva , Quimioradioterapia , Neoplasias Esofágicas/diagnóstico por imagen , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Estimación de Kaplan-Meier , Masculino , Persona de Mediana Edad , Pronóstico , Planificación de la Radioterapia Asistida por Computador , Estudios Retrospectivos , Análisis de SupervivenciaRESUMEN
PURPOSE: Nitroglycerin (NTG) is a vasodilating drug, which increases tumor blood flow and consequently decreases hypoxia. Therefore, changes in [18F] fluorodeoxyglucose positron emission tomography ([18F]FDG PET) uptake pattern may occur. In this analysis, we investigated the feasibility of [18F]FDG PET for response assessment to paclitaxel-carboplatin-bevacizumab (PCB) treatment with and without NTG patches. And we compared the [18F]FDG PET response assessment to RECIST response assessment and survival. METHODS: A total of 223 stage IV non-small cell lung cancer (NSCLC) patients were included in a phase II study (NCT01171170) randomizing between PCB treatment with or without NTG patches. For 60 participating patients, a baseline and a second [18F]FDG PET/computed tomography (CT) scan, performed between day 22 and 24 after the start of treatment, were available. Tumor response was defined as a 30 % decrease in CT and PET parameters, and was compared to RECIST response at week 6. The predictive value of these assessments for progression free survival (PFS) and overall survival (OS) was assessed with and without NTG. RESULTS: A 30 % decrease in SUVpeak assessment identified more patients as responders compared to a 30 % decrease in CT diameter assessment (73 % vs. 18 %), however, this was not correlated to OS (SUVpeak30 p = 0.833; CTdiameter30 p = 0.557). Changes in PET parameters between the baseline and the second scan were not significantly different for the NTG group compared to the control group (p value range 0.159-0.634). The CT-based (part of the [18F]FDG PET/CT) parameters showed a significant difference between the baseline and the second scan for the NTG group compared to the control group (CT diameter decrease of 7 ± 23 % vs. 19 ± 14 %, p = 0.016, respectively). CONCLUSIONS: The decrease in tumoral FDG uptake in advanced NSCLC patients treated with chemotherapy with and without NTG did not differ between both treatment arms. Early PET-based response assessment showed more tumor responders than CT-based response assessment (part of the [18F]FDG PET/CT); this was not correlated to survival. This might be due to timing of the [18F]FDG PET shortly after the bevacizumab infusion.
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Protocolos de Quimioterapia Combinada Antineoplásica/administración & dosificación , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/tratamiento farmacológico , Nitroglicerina/administración & dosificación , Adulto , Anciano , Bevacizumab/administración & dosificación , Carboplatino/administración & dosificación , Carcinoma de Pulmón de Células no Pequeñas/patología , Estudios de Factibilidad , Femenino , Fluorodesoxiglucosa F18 , Humanos , Neoplasias Pulmonares/patología , Masculino , Persona de Mediana Edad , Estadificación de Neoplasias , Países Bajos , Paclitaxel/administración & dosificación , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Radiofármacos , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Tasa de Supervivencia , Resultado del Tratamiento , Vasodilatadores/administración & dosificaciónRESUMEN
BACKGROUND: Cone-beam CT (CBCT) scans are typically acquired daily for positioning verification of non-small cell lung cancer (NSCLC) patients. Quantitative information, derived using radiomics, can potentially contribute to (early) treatment adaptation. The aims of this study were to (1) describe and investigate a methodology for feature selection of a longitudinal radiomics approach (2) investigate which time-point during treatment is potentially useful for early treatment response assessment. MATERIAL AND METHODS: For 90 NSCLC patients CBCT scans of the first two fractions of treatment (considered as 'test-retest' scans) were analyzed, as well as weekly CBCT images. One hundred and sixteen radiomic features were extracted from the GTV of all scans and subsequently absolute and relative differences were calculated between weekly CBCT images and the CBCT of the first fraction. Test-retest scans were used to determine the smallest detectable change (C = 1.96 * SD) allowing for feature selection by choosing a minimum number of patients for which a feature should change more than 'C' to be considered as relevant. Analysis of which features change at which moment during treatment was used to investigate which time-point is potentially relevant to extract longitudinal radiomics information for early treatment response assessment. RESULTS: A total of six absolute delta features changed for at least ten patients at week 2 of treatment and increased to 61 at week 3, 79 at week 4 and 85 at week 5. There was 93% overlap between features selected at week 3 and the other weeks. CONCLUSIONS: This study describes a feature selection methodology for longitudinal radiomics that is able to select reproducible delta radiomics features that are informative due to their change during treatment, which can potentially be used for treatment decisions concerning adaptive radiotherapy. Nonetheless, the prognostic value of the selected delta radiomic features should be investigated in future studies.
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Adenocarcinoma/diagnóstico por imagen , Carcinoma de Células Grandes/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Células Escamosas/diagnóstico por imagen , Tomografía Computarizada de Haz Cónico/métodos , Neoplasias Pulmonares/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Adulto , Anciano , Femenino , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Pronóstico , Estudios RetrospectivosRESUMEN
BACKGROUND: Hypoxia imaged by positron emission tomography (PET) is a potential target for optimization in radiotherapy. However, the implementation of this approach with respect to the conversion of intensities in the images into oxygenation and radiosensitivity maps is not straightforward. This study investigated the feasibility of applying two conversion approaches previously derived for 18F-labeled fluoromisonidazole (18F-FMISO)-PET images for the hypoxia tracer 18F-flortanidazole (18F-HX4). MATERIAL AND METHODS: Ten non-small-cell lung cancer patients imaged with 18F-HX4 before the start of radiotherapy were considered in this study. PET image uptake was normalized to a well-oxygenated reference region and subsequently linear and non-linear conversions were used to determine tissue oxygenations maps. These were subsequently used to delineate hypoxic volumes based partial oxygen pressure (pO2) thresholds. The results were compared to hypoxic volumes segmented using a tissue-to-background ratio of 1.4 for 18F-HX4 uptake. RESULTS: While the linear conversion function was not found to result in realistic oxygenation maps, the non-linear function resulted in reasonably sized sub-volumes in good agreement with uptake-based segmented volumes for a limited range of pO2 thresholds. However, the pO2 values corresponding to this range were significantly higher than what is normally considered as hypoxia. The similarity in size, shape, and relative location between uptake-based sub-volumes and volumes based on the conversion to pO2 suggests that the relationship between uptake and pO2 is similar for 18F-FMISO and 18F-HX4, but that the model parameters need to be adjusted for the latter. CONCLUSIONS: A non-linear conversion function between uptake and oxygen partial pressure for 18F-FMISO-PET could be applied to 18F-HX4 images to delineate hypoxic sub-volumes of similar size, shape, and relative location as based directly on the uptake. In order to apply the model for e.g., dose-painting, new parameters need to be derived for the accurate calculation of dose-modifying factors for this tracer.
Asunto(s)
Aorta/patología , Carcinoma de Pulmón de Células no Pequeñas/patología , Hipoxia/patología , Neoplasias Pulmonares/patología , Músculos/patología , Tomografía de Emisión de Positrones/métodos , Radioterapia Guiada por Imagen/métodos , Aorta/diagnóstico por imagen , Aorta/efectos de la radiación , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Fluorodesoxiglucosa F18 , Humanos , Hipoxia/diagnóstico por imagen , Hipoxia/radioterapia , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/radioterapia , Músculos/diagnóstico por imagen , Músculos/efectos de la radiación , Radiofármacos , Dosificación Radioterapéutica , Estándares de ReferenciaRESUMEN
BACKGROUND: Dose-guided adaptive radiation therapy (DGART) is the systematic evaluation and adaptation of the dose delivery during treatment for an individual patient. The aim of this study is to define quantitative action levels for DGART by evaluating changes in 3D dose metrics in breast cancer and correlate them with clinical expert evaluation. MATERIAL AND METHODS: Twenty-three breast cancer treatment plans were evaluated, that were clinically adapted based on institutional IGRT guidelines. Reasons for adaptation were variation in seroma, hematoma, edema, positioning or problems using voluntary deep inspiration breath hold. Sixteen patients received a uniform dose to the breast (clinical target volume 1; CTV1). Six patients were treated with a simultaneous integrated boost to CTV2. The original plan was copied to the CT during treatment (re-CT) or to the stitched cone-beam CT (CBCT). Clinical expert evaluation of the re-calculated dose distribution and extraction of dose-volume histogram (DVH) parameters were performed. The extreme scenarios were evaluated, assuming all treatment fractions were given to the original planning CT (pCT), re-CT or CBCT. Reported results are mean ± SD. RESULTS: DVH results showed a mean dose (Dmean) difference between pCT and re-CT of -0.4 ± 1.4% (CTV1) and -1.4 ± 2.1% (CTV2). The difference in V95% was -2.6 ± 4.4% (CTV1) and -9.8 ± 8.3% (CTV2). Clinical evaluation and DVH evaluation resulted in a recommended adaptation in 17/23 or 16/23 plans, respectively. Applying thresholds on the DVH parameters: Dmean CTV, V95% CTV, Dmax, mean lung dose, volume exceeding 107% (uniform dose) or 90% (SIB) of the prescribed dose enabled the identification of patients with an assumed clinically relevant dose difference, with a sensitivity of 0.89 and specificity of 1.0. Re-calculation on CBCT imaging identified the same plans for adaptation as re-CT imaging. CONCLUSIONS: Clinical expert evaluation can be related to quantitative DVH parameters on re-CT or CBCT imaging to select patients for DGART.
Asunto(s)
Neoplasias de la Mama/radioterapia , Técnicas de Apoyo para la Decisión , Imagenología Tridimensional/métodos , Órganos en Riesgo/efectos de la radiación , Planificación de la Radioterapia Asistida por Computador/métodos , Tomografía Computarizada de Haz Cónico/métodos , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Dosificación Radioterapéutica , Radioterapia de Intensidad Modulada/métodos , Estudios RetrospectivosRESUMEN
BACKGROUND: Standardization protocols and guidelines for positron emission tomography (PET) in multicenter trials are available, despite a large variability in image acquisition and reconstruction parameters exist. In this study, we investigated the compliance of PET scans to the guidelines of the European Association of Nuclear Medicine (EANM). From these results, we provide recommendations for future multicenter studies using PET. MATERIAL AND METHODS: Patients included in a multicenter randomized phase II study had repeated PET scans for early response assessment. Relevant acquisition and reconstruction parameters were extracted from the digital imaging and communications in medicine (DICOM) header of the images. The PET image parameters were compared to the guidelines of the EANM for tumor imaging version 1.0 recommended parameters. RESULTS: From the 223 included patients, 167 baseline scans and 118 response scans were available from 15 hospitals. Scans of 19% of the patients had an uptake time that fulfilled the Uniform Protocols for Imaging in Clinical Trials response assessment criteria. The average quality score over all hospitals was 69%. Scans with a non-compliant uptake time had a larger standard deviation of the mean standardized uptake value (SUVmean) of the liver than scans with compliant uptake times. CONCLUSIONS: Although a standardization protocol was agreed on, there was a large variability in imaging parameters. For future, multicenter studies including PET imaging a prospective central quality review during patient inclusion is needed to improve compliance with image standardization protocols as defined by EANM.
Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Neoplasias/diagnóstico por imagen , Neoplasias/radioterapia , Tomografía de Emisión de Positrones/métodos , Guías de Práctica Clínica como Asunto/normas , Garantía de la Calidad de Atención de Salud , Relación Dosis-Respuesta en la Radiación , Fluorodesoxiglucosa F18 , Humanos , Control de Calidad , RadiofármacosRESUMEN
BACKGROUND: Most solid tumors contain inadequately oxygenated (i.e., hypoxic) regions, which tend to be more aggressive and treatment resistant. Hypoxia PET allows visualization of hypoxia and may enable treatment adaptation. However, hypoxia PET imaging is expensive, time-consuming and not widely available. We aimed to predict hypoxia levels in non-small cell lung cancer (NSCLC) using more easily available imaging modalities: FDG-PET/CT and dynamic contrast-enhanced CT (DCE-CT). MATERIAL AND METHODS: For 34 NSCLC patients, included in two clinical trials, hypoxia HX4-PET/CT, planning FDG-PET/CT and DCE-CT scans were acquired before radiotherapy. Scans were non-rigidly registered to the planning CT. Tumor blood flow (BF) and blood volume (BV) were calculated by kinetic analysis of DCE-CT images. Within the gross tumor volume, independent clusters, i.e., supervoxels, were created based on FDG-PET/CT. For each supervoxel, tumor-to-background ratios (TBR) were calculated (median SUV/aorta SUVmean) for HX4-PET/CT and supervoxel features (median, SD, entropy) for the other modalities. Two random forest models (cross-validated: 10 folds, five repeats) were trained to predict the hypoxia TBR; one based on CT, FDG, BF and BV, and one with only CT and FDG features. Patients were split in a training (trial NCT01024829) and independent test set (trial NCT01210378). For each patient, predicted, and observed hypoxic volumes (HV) (TBR > 1.2) were compared. RESULTS: Fifteen patients (3291 supervoxels) were used for training and 19 patients (1502 supervoxels) for testing. The model with all features (RMSE training: 0.19 ± 0.01, test: 0.27) outperformed the model with only CT and FDG-PET features (RMSE training: 0.20 ± 0.01, test: 0.29). All tumors of the test set were correctly classified as normoxic or hypoxic (HV > 1 cm3) by the best performing model. CONCLUSIONS: We created a data-driven methodology to predict hypoxia levels and hypoxia spatial patterns using CT, FDG-PET and DCE-CT features in NSCLC. The model correctly classifies all tumors, and could therefore, aid tumor hypoxia classification and patient stratification.
Asunto(s)
Carcinoma de Pulmón de Células no Pequeñas/patología , Medios de Contraste/metabolismo , Fluorodesoxiglucosa F18/metabolismo , Neoplasias Pulmonares/patología , Tomografía de Emisión de Positrones/métodos , Tomografía Computarizada por Rayos X/métodos , Hipoxia Tumoral , Adenocarcinoma/diagnóstico por imagen , Adenocarcinoma/patología , Anciano , Biomarcadores de Tumor/metabolismo , Carcinoma de Células Grandes/diagnóstico por imagen , Carcinoma de Células Grandes/patología , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Células Escamosas/diagnóstico por imagen , Carcinoma de Células Escamosas/patología , Femenino , Estudios de Seguimiento , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Masculino , Imagen Multimodal/métodos , Pronóstico , Cintigrafía/métodos , Radiofármacos/metabolismoRESUMEN
BACKGROUND: Radiomic analyses of CT images provide prognostic information that can potentially be used for personalized treatment. However, heterogeneity of acquisition- and reconstruction protocols influences robustness of radiomic analyses. The aim of this study was to investigate the influence of different CT-scanners, slice thicknesses, exposures and gray-level discretization on radiomic feature values and their stability. MATERIAL AND METHODS: A texture phantom with ten different inserts was scanned on nine different CT-scanners with varying tube currents. Scans were reconstructed with 1.5 mm or 3 mm slice thickness. Image pre-processing comprised gray-level discretization in ten different bin widths ranging from 5 to 50 HU and different resampling methods (i.e., linear, cubic and nearest neighbor interpolation to 1 × 1 × 3 mm3 voxels) were investigated. Subsequently, 114 textural radiomic features were extracted from a 2.1 cm3 sphere in the center of each insert. The influence of slice thickness, exposure and bin width on feature values was investigated. Feature stability was assessed by calculating the concordance correlation coefficient (CCC) in a test-retest setting and for different combinations of scanners, tube currents and slice thicknesses. RESULTS: Bin width influenced feature values, but this only had a marginal effect on the total number of stable features (CCC > 0.85) when comparing different scanners, slice thicknesses or exposures. Most radiomic features were affected by slice thickness, but this effect could be reduced by resampling the CT-images before feature extraction. Statistics feature 'energy' was the most dependent on slice thickness. No clear correlation between feature values and exposures was observed. CONCLUSIONS: CT-scanner, slice thickness and bin width affected radiomic feature values, whereas no effect of exposure was observed. Optimization of gray-level discretization to potentially improve prognostic value can be performed without compromising feature stability. Resampling images prior to feature extraction decreases the variability of radiomic features.
Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Fantasmas de Imagen , Planificación de la Radioterapia Asistida por Computador/métodos , Tomógrafos Computarizados por Rayos X , Tomografía Computarizada por Rayos X/métodos , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Humanos , Neoplasias Pulmonares/radioterapiaRESUMEN
PURPOSE: Multiple imaging techniques are nowadays available for clinical in-vivo visualization of tumour biology. FDG PET/CT identifies increased tumour metabolism, hypoxia PET visualizes tumour oxygenation and dynamic contrast-enhanced (DCE) CT characterizes vasculature and morphology. We explored the relationships among these biological features in patients with non-small-cell lung cancer (NSCLC) at both the patient level and the tumour subvolume level. METHODS: A group of 14 NSCLC patients from two ongoing clinical trials (NCT01024829 and NCT01210378) were scanned using FDG PET/CT, HX4 PET/CT and DCE CT prior to chemoradiotherapy. Standardized uptake values (SUV) in the primary tumour were calculated for the FDG and hypoxia HX4 PET/CT scans. For hypoxia imaging, the hypoxic volume, fraction and tumour-to-blood ratio (TBR) were also defined. Blood flow and blood volume were obtained from DCE CT imaging. A tumour subvolume analysis was used to quantify the spatial overlap between subvolumes. RESULTS: At the patient level, negative correlations were observed between blood flow and the hypoxia parameters (TBR >1.2): hypoxic volume (-0.65, p = 0.014), hypoxic fraction (-0.60, p = 0.025) and TBR (-0.56, p = 0.042). At the tumour subvolume level, hypoxic and metabolically active subvolumes showed an overlap of 53 ± 36 %. Overlap between hypoxic sub-volumes and those with high blood flow and blood volume was smaller: 15 ± 17 % and 28 ± 28 %, respectively. Half of the patients showed a spatial mismatch (overlap <5 %) between increased blood flow and hypoxia. CONCLUSION: The biological imaging features defined in NSCLC tumours showed large interpatient and intratumour variability. There was overlap between hypoxic and metabolically active subvolumes in the majority of tumours, there was spatial mismatch between regions with high blood flow and those with increased hypoxia.