Prediction of radiation-induced normal tissue complications in radiotherapy using functional image data

Predicting radiation pneumonitis with fuzzy clustering neural network using 4DCT ventilation image based dosimetric parameters

Background

To develop a fuzzy clustering neural network to predict radiation-induced pneumonitis (RP) using four-dimensional computed tomography (4DCT) ventilation image (VI) based dosimetric parameters for thoracic cancer patients.

Methods

The VI were retrospectively calculated from pre-treatment 4DCT data using a deformable image registration (DIR) and an improved VI algorithm. Similar to dose-volume histogram (DVH) of intensity modulated radiotherapy (IMRT), dose-function histogram (DFH) was derived from dose distribution and VI. Then, the dose-function metrics were calculated from DFH. For comparison, the dose-volume metrics were calculated from DVH. Correspondingly, two sets of feature vectors were formed from the dose-volume metrics and the dose-function metrics, respectively. For the feature vectors of each set, they were first pre-processed by principal component analysis (PCA) to reduce feature dimensions. Then, they were grouped to few clusters determined by fuzzy c-means (FCM) algorithm. Next, the neural network was trained to correlate the dosimetric parameters with RP based on the feature vectors of each cluster. Finally, the occurrence of RP was predicted by the neural network on the test data.

Results

Through PCA analysis, the top 5 principal components were selected. Their contribution is more than 98%, which is adequate to represent the original feature space of input data. Based on the clustering validity indexes, the optimal number of clusters is 4 and used for subsequent fuzzy clustering of the input data. After network training, the areas under the curve (AUC) of the prediction model is 0.77 using VI-based dosimetric parameters and 0.67 using structure-based dosimetric parameters.

Conclusions

Compared to the structure-based dosimetric features, the VI-based dosimetric features are more relevant to lung function and presented higher prediction accuracy of RP. The fuzzy clustering neural network improved the prediction accuracy of RP compared to the conventional neural network. The combination of VI-based dose-function metrics and fuzzy clustering neural network provides an effective predictive model for assessing lung toxicity risk after radiotherapy.

Functional lung imaging in radiation therapy for lung cancer: A systematic review and meta-analysis

RATIONALE

Advanced imaging techniques allow functional information to be derived and integrated into treatment planning.

METHODS

A systematic review was conducted with the primary objective to evaluate the ability of functional lung imaging to predict risk of radiation pneumonitis. Secondary objectives were to evaluate dose-response relationships on post treatment functional imaging and assess the utility in including functional lung information into treatment planning. A structured search for publications was performed following PRISMA guidelines and registered on PROSPERO.

RESULTS

814 articles were screened against review criteria and 114 publications met criteria. Methods of identifying functional lung included using CT, MRI, SPECT and PET to image ventilation or perfusion. Six studies compared differences between functional and anatomical lung imaging at predicting radiation pneumonitis. These found higher predictive values using functional lung imaging. Twenty-one studies identified a dose-response relationship on post-treatment functional lung imaging. Nineteen planning studies demonstrated the ability of functional lung optimised planning techniques to spare regions of functional lung. Meta-analysis of these studies found that mean (95% CI) functional volume receiving 20 Gy was reduced by 4.2% [95% CI: 2.3: 6.0] and mean lung dose by 2.2 Gy [95% CI: 1.2: 3.3] when plans were optimised to spare functional lung. There was significant variation between publications in the definition of functional lung.

CONCLUSION

Functional lung imaging may have potential utility in radiation therapy planning and delivery, although significant heterogeneity was identified in approaches and reporting. Recommendations have been made based on the available evidence for future functional lung trials.

Correlation of Regional Lung Ventilation and Gas Transfer to Red Blood Cells: Implications for Functional-Avoidance Radiation Therapy Planning

PURPOSE

To investigate the degree to which lung ventilation and gas exchange are regionally correlated, using the emerging technology of hyperpolarized (HP)-129Xe magnetic resonance imaging (MRI).

METHODS AND MATERIALS

Hyperpolarized-129Xe MRI studies were performed on 17 institutional review board-approved human subjects, including 13 healthy volunteers, 1 emphysema patient, and 3 non-small cell lung cancer patients imaged before and approximately 11 weeks after radiation therapy (RT). Subjects inhaled 1 L of HP-129Xe mixture, followed by the acquisition of interleaved ventilation and gas exchange images, from which maps were obtained of the relative HP-129Xe distribution in three states: (1) gaseous, in lung airspaces; (2) dissolved interstitially, in alveolar barrier tissue; and (3) transferred to red blood cells (RBCs), in the capillary vasculature. The relative spatial distributions of HP-129Xe in airspaces (regional ventilation) and RBCs (regional gas transfer) were compared. Further, we investigated the degree to which ventilation and RBC transfer images identified similar functional regions of interest (ROIs) suitable for functionally guided RT. For the RT patients, both ventilation and RBC functional images were used to calculate differences in the lung dose-function histogram and functional effective uniform dose.

RESULTS

The correlation of ventilation and RBC transfer was ρ = 0.39 ± 0.15 in healthy volunteers. For the RT patients, this correlation was ρ = 0.53 ± 0.02 before treatment and ρ = 0.39 ± 0.07 after treatment; for the emphysema patient it was ρ = 0.24. Comparing functional ROIs, ventilation and RBC transfer demonstrated poor spatial agreement: Dice similarity coefficient = 0.50 ± 0.07 and 0.26 ± 0.12 for the highest-33%- and highest-10%-function ROIs in healthy volunteers, and in RT patients (before treatment) these were 0.58 ± 0.04 and 0.40 ± 0.04. The average magnitude of the differences between RBC- and ventilation-derived functional effective uniform dose, fV20Gy, fV10Gy, and fV5Gy were 1.5 ± 1.4 Gy, 4.1% ± 3.8%, 5.0% ± 3.8%, and 5.3% ± 3.9%, respectively.

CONCLUSION

Ventilation may not be an effective surrogate for true regional lung function for all patients.

Which is the optimal threshold for defining functional lung in single-photon emission computed tomography lung perfusion imaging of lung cancer patients?

PURPOSE

The aim of this study was to investigate the optimal threshold for the functional lung (FL) definition of single-photon emission computed tomography (SPECT) lung perfusion imaging.

PATIENTS AND METHODS

Forty consecutive stage III non-small-cell lung cancer patients underwent SPECT lung perfusion scans and PET/CT scans for treatment planning, and the images were coregistered. Total lung and perfusion lung volumes corresponding to 10, 20, …, 60% of the maximum SPECT count were segmented automatically. The SPECT-weighted mean lung dose (SWMDx%) and the percentage of FL volume receiving more than 20 Gy (Fx%V20) of different thresholds were investigated using SPECT-weighted dose-volume histograms. Receiver-operator characteristic curves were used to identify SWMD and FV20 of different thresholds in predicting the incidence of radiation pneumonitis (RP).

RESULTS

Eleven (27.5%) patients developed RP (grades 1, 2, 3, and 4 were 10.0, 7.5, 7.5, and 2.5%, respectively) after treatment. The largest area under the receiver-operator characteristic curve was 0.881 for the ability of SWMD to predict RP with 20% as the threshold and 0.928 for the ability of FV20 with 20% as the threshold.

CONCLUSION

The SWMD20% and FV20 of FL using 20% of the maximum SPECT count as the threshold may be better predictors for the risk of RP.

Should regional ventilation function be considered during radiation treatment planning to prevent radiation-induced complications?

PURPOSE

To investigate the incorporation of pretherapy regional ventilation function in predicting radiation fibrosis (RF) in stage III nonsmall cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy.

METHODS

Thirty-seven patients with stage III NSCLC were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy (46-66 Gy; 2 Gy/fraction). Pretherapy regional ventilation images of the lung were derived from 4D computed tomography via a density change-based algorithm with mass correction. In addition to the conventional dose-volume metrics (V20, V30, V40, and mean lung dose), dose-function metrics (fV20, fV30, fV40, and functional mean lung dose) were generated by combining regional ventilation and radiation dose. A new class of metrics was derived and referred to as dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean lung dose); these were defined as the conventional dose-volume metrics computed on the functional lung. Area under the receiver operating characteristic curve (AUC) values and logistic regression analyses were used to evaluate these metrics in predicting hallmark characteristics of RF (lung consolidation, volume loss, and airway dilation).

RESULTS

AUC values for the dose-volume metrics in predicting lung consolidation, volume loss, and airway dilation were 0.65-0.69, 0.57-0.70, and 0.69-0.76, respectively. The respective ranges for dose-function metrics were 0.63-0.66, 0.61-0.71, and 0.72-0.80 and for dose-subvolume metrics were 0.50-0.65, 0.65-0.75, and 0.73-0.85. Using an AUC value = 0.70 as cutoff value suggested that at least one of each type of metrics (dose-volume, dose-function, dose-subvolume) was predictive for volume loss and airway dilation, whereas lung consolidation cannot be accurately predicted by any of the metrics. Logistic regression analyses showed that dose-function and dose-subvolume metrics were significant (P values ≤ 0.02) in predicting volume airway dilation. Likelihood ratio test showed that when combining dose-function and/or dose-subvolume metrics with dose-volume metrics, the achieved improvements of prediction accuracy on volume loss and airway dilation were significant (P values ≤ 0.04).

CONCLUSIONS

The authors' results demonstrated that the inclusion of regional ventilation function improved accuracy in predicting RF. In particular, dose-subvolume metrics provided a promising method for preventing radiation-induced pulmonary complications.

Use of 4-dimensional computed tomography-based ventilation imaging to correlate lung dose and function with clinical outcomes

PURPOSE

Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity.

METHODS AND MATERIALS

Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose-volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose-volume and ventilation-based dose-function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods.

RESULTS

A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose-function metrics (range P=.093-.250) than for their dose-volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose-function metrics (range, 0.569-0.620) than for their dose-volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose-function metrics compared to dose-volume metrics that approached significance (range, P=.118-.155).

CONCLUSIONS

To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests that incorporating ventilation-based functional imaging can improve prediction for radiation pneumonitis. We present an important first step toward validating the use of 4DCT-based ventilation imaging in thoracic treatment planning.

Functional dosimetric metrics for predicting radiation-induced lung injury in non-small cell lung cancer patients treated with chemoradiotherapy

Background

Radiation-induced lung injury (RILI) is an important dose-limiting toxicity during thoracic radiotherapy. The purpose of this study is to investigate single photon emission computed tomography (SPECT) perfusion-weighted functional dose-volume histogram (FDVH) for predicting RILI in non-small cell lung cancer (NSCLC) patients treated with definitive chemoradiotherapy.

Methods

Fifty-seven locally advanced NSCLC patients receiving chemoradiotherapy were enrolled prospectively. Patients had treatment scans and dose calculations to provide a standard dose-volume histogram (DVH). Fusion of SPECT and computed tomography scans provided perfusion-weighted FDVH and associated functional dosimetric parameters (relative volumes of functional lung receiving more than a threshold dose of 5 – 60 Gy at increments of 5 Gy [FV5 – FV60]). The predictive abilities of FDVH and DVH were calculated and compared based on the area under receiver operating characteristic (ROC) curve (AUC).

Results

The accumulative incidence of ≥ 2 grade RILI was 19.3% with a median follow-up of 12 months. Univariate analysis showed that the functional (FV5 – FV60) and standard (V5 – V40) parameters were associated with RILI (all value of p < 0.05). Close correlations between a variety of functional and standard parameters were found. By ROC curve analysis, functional metrics (AUCs were 0.784 – 0.869) provided similarly (p value 0.233 – 1.000) predictive outcome to standard metrics (AUCs were 0.695 – 0.902) in lower – median dose level parameters (FV5 – FV40). However, FDVH seemed to add some predictive value in higher dose level, the best statistical significance for comparing FV60 with V60 was 0.693 vs. 0.511 (p = 0.055).

Conclusions

Functional metrics are identified as reliable predictors for RILI, however, this observation still needs to be further verified using a larger sample size.

Functional and molecular image guidance in radiotherapy treatment planning optimization

Functional and molecular imaging techniques are increasingly being developed and used to quantitatively map the spatial distribution of parameters, such as metabolism, proliferation, hypoxia, perfusion, and ventilation, onto anatomically imaged normal organs and tumor. In radiotherapy optimization, these imaging modalities offer the promise of increased dose sparing to high-functioning subregions of normal organs or dose escalation to selected subregions of the tumor as well as the potential to adapt radiotherapy to functional changes that occur during the course of treatment. The practical use of functional/molecular imaging in radiotherapy optimization must take into cautious consideration several factors whose influences are still not clearly quantified or well understood including patient positioning differences between the planning computed tomography and functional/molecular imaging sessions, image reconstruction parameters and techniques, image registration, target/normal organ functional segmentation, the relationship governing the dose escalation/sparing warranted by the functional/molecular image intensity map, and radiotherapy-induced changes in the image intensity map over the course of treatment. The clinical benefit of functional/molecular image guidance in the form of improved local control or decreased normal organ toxicity has yet to be shown and awaits prospective clinical trials addressing this issue.

Functional dose-volume histograms for predicting radiation pneumonitis in locally advanced non-small cell lung cancer treated with late-course accelerated hyperfractionated radiotherapy

The aim of this study was to determine whether functional dose-volume histograms (FDVHs) are valuable for predicting radiation pneumonitis (RP), and to identify whether FDVHs have advantages over conventional dose-volume histograms (DVHs) for the prediction of RP in patients with locally advanced non-small cell lung cancer (LANSCLC). Fifty-seven patients with LANSCLC undergoing functional image-guided late-course accelerated hyperfractionated radiotherapy were enrolled. The grade of RP was evaluated according to the Common Toxicity Criteria 3.0. To identify predictive factors of RP, the FDVHs, including the volume of the functional lung receiving 5 Gy (FV(5)) through 50 Gy (FV(50)), mean perfusion-weighted lung dose (MPWLD) and functional normal tissue complication probability (FNTCP), were analyzed and compared to their counterparts [total lung receiving 5 Gy (V(5)) through 50 Gy (V(50)), mean lung dose (MLD) and normal tissue complication probability (NTCP)] derived from conventional DVHs. Univariate analysis revealed that V(5)-V(40), MLD, NTCP and FV(5)-FV(50), MPWLD, FNTCP were all statistically significant relative to the development of RP (all p<0.05). Multivariate analysis showed that only MLD and FV(15) were associated with RP (p=0.001 and 0.044, respectively). Receiver operator characteristic curve anaysis indicated that almost all of the FDVHs had larger areas under the curve compared to the DVHs, although no statistically significant difference was observed (p-value ranged from 0.066 to 0.951). FDVHs are valuable for predicting RP with the predictive efficiency equivalent to or slightly advantageous over conventional DVHs. More homogeneous studies involving larger numbers of patients are required to further assess the value of FDVHs for predicting RP.

Imaging of normal lung, liver and parotid gland function for radiotherapy

There is growing clinical evidence that functional imaging is useful for target volume definition and early assessment of tumour response to external beam radiotherapy. A subject that has perhaps received less attention, but is no less promising, is the application of functional imaging to the prediction or measurement of radiation adverse effects in normal tissues. In this manuscript, we review the current published literature describing the use of positron emission tomography (PET), four-dimensional computed tomography (4D-CT), single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) to study normal tissue function in the context of radiotherapy to the lung, liver and head & neck. Published results to date demonstrate that functional imaging can be used to preferentially avoid normal tissues not easily identifiable on solely anatomical images. It is also a potentially very powerful tool for the early detection of radiotherapy-induced normal tissue adverse effects and could provide valuable data for building predictive models of outcome. However, one of the major challenges to building useful predictive models is that, to date, there are very little data available with combined images of normal function, 3D delivered radiation dose and clinical outcomes. Prospective data collection through well-constructed studies which use established morbidity scores is clearly a priority if significant progress is to be made in this area.

Predicting Risk of Radiation-Induced Lung Injury

Radiation-induced lung injury (RILI) is the most common, dose-limiting complication of thoracic radio- and radiochemotherapy. Unfortunately, predicting which patients will suffer from this complication is extremely difficult. Ideally, individual phenotype- and genotype-based risk profiles should be able to identify patients who are resistant to RILI and who could benefit from dose escalation in chemoradiotherapy. This could result in better local control and overall survival. We review the risk predictors that are currently in clinical use--dosimetric parameters of radiotherapy such as normal tissue complication probability, mean lung dose, V20 and V30--as well as biomarkers that might individualize risk profiles. These biomarkers comprise a variety of proinflammatory and profibrotic cytokines and molecules including transforming growth factor beta1 that are implicated in development and persistence of RILI. Dosimetric parameters of radiotherapy show a low negative predictive value of 60% to 80%. Depending on the studied molecule, negative predictive value of biomarkers is approximately 50%. The predictive power of biomarkers might be increased if they are coupled with radiogenomics, e.g., genotyping analysis of single nucleotide polymorphisms in transforming growth factor beta1, transforming growth factor beta1 pathway genes, and other cytokines. Genetic variability and the complexity of RILI and its underlying molecular mechanisms make identification of biological risk predictors challenging. Further investigations are needed to develop more effective risk predictors of RILI.

Preserving Functional Lung Using Perfusion Imaging and Intensity-Modulated Radiation Therapy for Advanced-Stage Non–Small Cell Lung Cancer

PURPOSE

To assess quantitatively the impact of incorporating functional lung imaging into intensity-modulated radiation therapy planning for locally advanced non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

Sixteen patients with advanced-stage NSCLC who underwent radiotherapy were included in this study. Before radiotherapy, each patient underwent lung perfusion imaging with single-photon-emission computed tomography and X-ray computed tomography (SPECT-CT). The SPECT-CT was registered with simulation CT and was used to segment the 50- and 90-percentile hyperperfusion lung (F50 lung and F90 lung). Two IMRT plans were designed and compared in each patient: an anatomic plan using simulation CT alone and a functional plan using SPECT-CT in addition to the simulation CT. Dosimetric parameters of the two types of plans were compared in terms of tumor coverage and avoidance of normal tissues.

RESULTS

In incorporating perfusion information in IMRT planning, the median reductions in the mean doses to the F50 and F90 lung in the functional plan were 2.2 and 4.2 Gy, respectively, compared with those in the anatomic plans. The median reductions in the percentage of volume irradiated with >5 Gy, >10 Gy, and >20 Gy in the functional plans were 7.1%, 6.0%, and 5.1%, respectively, for F50 lung, and 11.7%, 12.0%, and 6.8%, respectively, for F90 lung. A greater degree of sparing of the functional lung was achieved for patients with large perfusion defects compared with those with relatively uniform perfusion distribution.

CONCLUSION

Function-guided IMRT planning appears to be effective in preserving functional lung in locally advanced-stage NSCLC patients.

A potential to reduce pulmonary toxicity: The use of perfusion SPECT with IMRT for functional lung avoidance in radiotherapy of non-small cell lung cancer

BACKGROUND AND PURPOSE

The study aimed to examine specific avoidance of functional lung (FL) defined by a single photon emission computerized tomography (SPECT) lung perfusion scan, using intensity modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3-DCRT) in patients with non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Patients with NSCLC underwent planning computerized tomography (CT) and lung perfusion SPECT scan in the treatment position using fiducial markers to allow co-registration in the treatment planning system. Radiotherapy (RT) volumes were delineated on the CT scan. FL was defined using co-registered SPECT images. Two inverse coplanar RT plans were generated for each patient: 4-field 3-DCRT and 5-field step-and-shoot IMRT. 3-DCRT plans were created using automated AutoPlan optimisation software, and IMRT plans were generated employing Pinnacle(3) treatment planning system (Philips Radiation Oncology Systems). All plans were prescribed to 64 Gy in 32 fractions using data for the 6 MV beam from an Elekta linear accelerator. The objectives for both plans were to minimize the volume of FL irradiated to 20 Gy (fV(20)) and dose variation within the planning target volume (PTV). A spinal cord dose was constrained to 46 Gy. Volume of PTV receiving 90% of the prescribed dose (PTV(90)), fV(20), and functional mean lung dose (fMLD) were recorded. The PTV(90)/fV(20) ratio was used to account for variations in both measures, where a higher value represented a better plan.

RESULTS

Thirty-four RT plans of 17 patients with stage I-IIIB NSCLC suitable for radical RT were analysed. In 6 patients with stage I-II disease there was no improvement in PTV(90), fV(20), PTV/fV(20) ratio and fMLD using IMRT compared to 3-DCRT. In 11 patients with stage IIIA-B disease, the PTV was equally well covered with IMRT and 3-DCRT plans, with IMRT producing better PTV(90)/fV(20) ratio (mean ratio - 7.2 vs. 5.3, respectively, p=0.001) and reduced fMLD figures compared to 3-DCRT (mean value - 11.5 vs. 14.3 Gy, p=0.001). This was due to reduction in fV(20) while maintaining PTV coverage.

CONCLUSION

The use of IMRT compared to 3-DCRT improves the avoidance of FL defined by perfusion SPECT scan in selected patients with locally advanced NSCLC. If the dose to FL is shown to be the primary determinant of lung toxicity, IMRT would allow for effective dose escalation by specific avoidance of FL.

The Role of Functional Imaging in the Diagnosis and Management of Late Normal Tissue Injury

Normal tissue injury after radiation therapy (RT) can be defined based on either clinical symptoms or laboratory/radiologic tests. In the research setting, functional imaging (eg, single-photon emission computed tomography [SPECT], positron-emission tomography [PET], and magnetic resonance imaging [MRI]) is useful because it provides objective quantitative data such as metabolic activity, perfusion, and soft-tissue contrast within tissues and organs. For RT-induced lung, heart, and parotid gland injury, pre- and post-RT SPECT images can be compared with the dose- and volume-dependent nature of regional injury. In the brain, SPECT can detect changes in perfusion and blood flow post-RT, and PET can detect metabolic changes, particularly to regions of the brain that have received doses above 40 to 50 Gy. On MRI, changes in contrast-enhanced images, T(1) and T(2) relaxation times, and pulmonary vascular resistance at different intervals pre- and post-RT show its ability to detect and distinguish different phases of radiation pneumonitis. Similarly, conventional and diffusion-weighted MRI can be used to differentiate between normal tissue edema, necrosis, and tumor in the irradiated brain, and magnetic resonance spectroscopy can measure changes in compounds, indicative of membrane and neuron disruption. The use of functional imaging is a powerful tool for early detection of RT-induced normal tissue injury, which may be related to long-term clinically significant injury.

The role of PET/CT scanning in radiotherapy planning

The introduction of functional data into the radiotherapy treatment planning process is currently the focus of significant commercial, technical, scientific and clinical development. The potential of such data from positron emission tomography (PET) was recognized at an early stage and was integrated into the radiotherapy treatment planning process through the use of image fusion software. The combination of PET and CT in a single system (PET/CT) to form an inherently fused anatomical and functional dataset has provided an imaging modality which could be used as the prime tool in the delineation of tumour volumes and the preparation of patient treatment plans, especially when integrated with virtual simulation. PET imaging typically using 18F-Fluorodeoxyglucose (18F-FDG) can provide data on metabolically active tumour volumes. These functional data have the potential to modify treatment volumes and to guide treatment delivery to cells with particular metabolic characteristics. This paper reviews the current status of the integration of PET and PET/CT data into the radiotherapy treatment process. Consideration is given to the requirements of PET/CT data acquisition with reference to patient positioning aids and the limitations imposed by the PET/CT system. It also reviews the approaches being taken to the definition of functional/tumour volumes and the mechanisms available to measure and include physiological motion into the imaging process. The use of PET data must be based upon a clear understanding of the interpretation and limitations of the functional signal. Protocols for the implementation of this development remain to be defined, and outcomes data based upon clinical trials are still awaited.

Dynamic ventilation imaging from four-dimensional computed tomography

A novel method for dynamic ventilation imaging of the full respiratory cycle from four-dimensional computed tomography (4D CT) acquired without added contrast is presented. Three cases with 4D CT images obtained with respiratory gated acquisition for radiotherapy treatment planning were selected. Each of the 4D CT data sets was acquired during resting tidal breathing. A deformable image registration algorithm mapped each (voxel) corresponding tissue element across the 4D CT data set. From local average CT values, the change in fraction of air per voxel (i.e. local ventilation) was calculated. A 4D ventilation image set was calculated using pairs formed with the maximum expiration image volume, first the exhalation then the inhalation phases representing a complete breath cycle. A preliminary validation using manually determined lung volumes was performed. The calculated total ventilation was compared to the change in contoured lung volumes between the CT pairs (measured volume). A linear regression resulted in a slope of 1.01 and a correlation coefficient of 0.984 for the ventilation images. The spatial distribution of ventilation was found to be case specific and a 30% difference in mass-specific ventilation between the lower and upper lung halves was found. These images may be useful in radiotherapy planning.