Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy

AIMS

Delineation variations and organ motion produce difficult-to-quantify uncertainties in planned radiation doses to targets and organs at risk. Similar to manual contouring, most automatic segmentation tools generate single delineations per structure; however, this does not indicate the range of clinically acceptable delineations. This study develops a method to generate a range of automatic cardiac structure segmentations, incorporating motion and delineation uncertainty, and evaluates the dosimetric impact in lung cancer.

MATERIALS AND METHODS

Eighteen cardiac structures were delineated using a locally developed auto-segmentation tool. It was applied to lung cancer planning CTs for 27 curative (planned dose ≥50 Gy) cases, and delineation variations were estimated by using ten mapping-atlases to provide separate substructure segmentations. Motion-related cardiac segmentation variations were estimated by auto-contouring structures on ten respiratory phases for 9/27 cases that had 4D-planning CTs. Dose volume histograms (DVHs) incorporating these variations were generated for comparison.

RESULTS

Variations in mean doses (Dmean), defined as the range in values across ten feasible auto-segmentations, were calculated for each cardiac substructure. Over the study cohort the median variations for delineation uncertainty and motion were 2.20-11.09 Gy and 0.72-4.06 Gy, respectively. As relative values, variations in Dmean were between 18.7%-65.3% and 7.8%-32.5% for delineation uncertainty and motion, respectively. Doses vary depending on the individual planned dose distribution, not simply on segmentation differences, with larger dose variations to cardiac structures lying within areas of steep dose gradient.

CONCLUSION

Radiotherapy dose uncertainties from delineation variations and respiratory-related heart motion were quantified using a cardiac substructure automatic segmentation tool. This predicts the 'dose range' where doses to structures are most likely to fall, rather than single DVH curves. This enables consideration of these uncertainties in cardiotoxicity research and for future plan optimisation. The tool was designed for cardiac structures, but similar methods are potentially applicable to other OARs.

Federated Learning Survival Model and Potential Radiotherapy Decision Support Impact Assessment for Non-small Cell Lung Cancer Using Real-World Data

AIMS

The objective of this study was to develop a two-year overall survival model for inoperable stage I-III non-small cell lung cancer (NSCLC) patients using routine radiation oncology data over a federated (distributed) learning network and evaluate the potential of decision support for curative versus palliative radiotherapy.

METHODS

A federated infrastructure of data extraction, de-identification, standardisation, image analysis, and modelling was installed for seven clinics to obtain clinical and imaging features and survival information for patients treated in 2011-2019. A logistic regression model was trained for the 2011-2016 curative patient cohort and validated for the 2017-2019 cohort. Features were selected with univariate and model-based analysis and optimised using bootstrapping. System performance was assessed by the receiver operating characteristic (ROC) and corresponding area under curve (AUC), C-index, calibration metrics and Kaplan-Meier survival curves, with risk groups defined by model probability quartiles. Decision support was evaluated using a case-control analysis using propensity matching between treatment groups.

RESULTS

1655 patient datasets were included. The overall model AUC was 0.68. Fifty-eight percent of patients treated with palliative radiotherapy had a low-to-moderate risk prediction according to the model, with survival times not significantly different (p = 0.87 and 0.061) from patients treated with curative radiotherapy classified as high-risk by the model. When survival was simulated by risk group and model-indicated treatment, there was an estimated 11% increase in survival rate at two years (p < 0.01).

CONCLUSION

Federated learning over multiple institution data can be used to develop and validate decision support systems for lung cancer while quantifying the potential impact of their use in practice. This paves the way for personalised medicine, where decisions can be based more closely on individual patient details from routine care.

Current and projected gaps in the availability of radiotherapy in the Asia-Pacific region: a country income-group analysis

BACKGROUND

Cancer incidence and mortality is increasing rapidly worldwide, with a higher cancer burden observed in the Asia-Pacific region than in other regions. To date, evidence-based modelling of radiotherapy demand has been based on stage data from high-income countries (HIC) that do not account for the later stage at presentation seen in many low-income and middle-income countries (LMICs). We aimed to estimate the current and projected demand and supply in megavoltage radiotherapy machines in the Asia-Pacific region, using a national income-group adjusted model.

METHODS

Novel LMIC radiotherapy demand and outcome models were created by adjusting previously developed models that used HIC cancer staging data. These models were applied to the cancer case mix (ie, the incidence of each different cancer) in each LMIC in the Asia-Pacific region to estimate the current and projected optimal radiotherapy utilisation rate (ie, the proportion of cancer cases that would require radiotherapy on the basis of guideline recommendations), and to estimate the number of megavoltage machines needed in each country to meet this demand. Information on the number of megavoltage machines available in each country was retrieved from the Directory of Radiotherapy Centres. Gaps were determined by comparing the projected number of megavoltage machines needed with the number of machines available in each region. Megavoltage machine numbers, local control, and overall survival benefits were compared with previous data from 2012 and projected data for 2040.

FINDINGS

57 countries within the Asia-Pacific region were included in the analysis with 9·48 million new cases of cancer in 2020, an increase of 2·66 million from 2012. Local control was 7·42% and overall survival was 3·05%. Across the Asia-Pacific overall, the current optimal radiotherapy utilisation rate is 49·10%, which means that 4·66 million people will need radiotherapy in 2020, an increase of 1·38 million (42%) from 2012. The number of megavoltage machines increased by 1261 (31%) between 2012 and 2020, but the demand for these machines increased by 3584 (42%). The Asia-Pacific region only has 43·9% of the megavoltage machines needed to meet demand, ranging from 9·9-40·5% in LMICs compared with 67·9% in HICs. 12 000 additional megavoltage machines will be needed to meet the projected demand for 2040.

INTERPRETATION

The difference between supply and demand with regard to megavoltage machine availability has continued to widen in LMICs over the past decade and is projected to worsen by 2040. The data from this study can be used to provide evidence for the need to incorporate radiotherapy in national cancer control plans and to inform governments and policy makers within the Asia-Pacific region regarding the urgent need for investment in this sector.

FUNDING

The Regional Cooperative Agreement for Research, Development and Training Related to Nuclear Science and Technology for Asia and the Pacific (RCA) Regional Office (RCARP03).

Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy

BACKGROUND AND PURPOSE

Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segmentation tool for automatic delineation of cardiac structures and subsequent dose evaluation, with potential application in clinical settings and large-scale radiation-related cardiotoxicity studies.

MATERIALS AND METHODS

A recently developed hybrid method for automatic segmentation of 18 cardiac structures, combining deep learning, multi-atlas mapping and geometric segmentation of small challenging substructures, was independently validated on 30 lung cancer cases. These included anatomical and imaging variations, such as tumour abutting heart, lung collapse and metal artefacts. Automatic segmentations were compared with manual contours of the 18 structures using quantitative metrics, including Dice similarity coefficient (DSC), mean distance to agreement (MDA) and dose comparisons.

RESULTS

A comparison of manual and automatic contours across all cases showed a median DSC of 0.75-0.93 and a median MDA of 2.09-3.34 mm for whole heart and chambers. The median MDA for great vessels, coronary arteries, cardiac valves, sinoatrial and atrioventricular conduction nodes was 3.01-8.54 mm. For the 27 cases treated with curative intent (planned target volume dose ≥50 Gy), the median dose difference was -1.12 to 0.57 Gy (absolute difference of 1.13-3.25%) for the mean dose to heart and chambers; and -2.25 to 4.45 Gy (absolute difference of 0.94-6.79%) for the mean dose to substructures.

CONCLUSION

The novel hybrid automatic segmentation tool reported high accuracy and consistency over a validation set with challenging anatomical and imaging variations. This has promising applications in substructure dose calculations of large-scale datasets and for future studies on long-term cardiac toxicity.

Patterns of palliative radiotherapy fractionation for brain metastases patients in New South Wales, Australia

BACKGROUND AND PURPOSE

There is a paucity of studies examining variation in the use of palliative radiation therapy (RT) fractionation for brain metastases. The aim of this study is to assess variation in palliative RT fractionation given for brain metastases in New South Wales (NSW), Australia, and identify factors associated with variation.

MATERIALS AND METHODS

This is a population-based cohort of patients who received whole brain RT (WBRT) for brain metastases (2009-2014), as captured in the NSW Central Cancer Registry. A logistic regression model was used to identify factors associated with fractionation type.

RESULTS

Of the 2,698 patients that received WBRT, 1,389 courses (51%) were < 6 fractions, 1,050 courses (39%) were 6-10 fractions, and 259 courses (10%) were > 10 fractions. Older patients were more likely to be treated with shorter courses (P < 0.0001). Patients with primary lung cancers were more likely to receive shorter courses compared with other primary cancers (P < 0.0001). Patients without surgical excision were more likely to receive < 6 fractions compared to those who underwent surgical excision. Shorter courses were more likely to be delivered to patients with the most disadvantaged socioeconomic status (SES) compared with patients with the least disadvantaged SES (P < 0.0001). There were significant fluctuations in the proportion of courses using lower number of fractions over time from 2009 to 2014, but no apparent trend (P = 0.02). There was wide variation in the proportion of shorter courses across residence local health districts, ranging from 24% to 69% for < 6 fractions, 21% to 72% for 6-10 fractions, and 4% to 20% for > 10 fractions (P < 0.0001).

CONCLUSION

This study has identified significant unwarranted variations in fractionation for WBRT in NSW. Accelerating the uptake of shorter fractionation regimens, if warranted through evidence, should be prioritised to enhance evidence-based care.

The population benefit of evidence-based radiotherapy: 5-Year local control and overall survival benefits

BACKGROUND

To describe the population benefit of radiotherapy in a high-income setting if evidence-based guidelines were routinely followed.

METHODS

Australian decision tree models were utilized. Radiotherapy alone (RT) benefit was defined as the absolute proportional benefit of radiotherapy compared with no treatment for radical indications, and of radiotherapy over surgery alone for adjuvant indications. Chemoradiotherapy (CRT) benefit was the absolute incremental benefit of concurrent chemoradiotherapy over RT. Five-year local control (LC) and overall survival (OS) benefits were measured. Citation databases were systematically queried for benefit data. Meta-analysis and sensitivity analysis were performed.

FINDINGS

48% of all cancer patients have indications for radiotherapy, 34% curative and 14% palliative. RT provides 5-year LC benefit in 10.4% of all cancer patients (95% Confidence Interval 9.3, 11.8) and 5-year OS benefit in 2.4% (2.1, 2.7). CRT provides 5-year LC benefit in an additional 0.6% of all cancer patients (0.5, 0.6), and 5-year OS benefit for an additional 0.3% (0.2, 0.4). RT benefit was greatest for head and neck (LC 32%, OS 16%), and cervix (LC 33%, OS 18%). CRT LC benefit was greatest for rectum (6%) and OS for cervix (3%) and brain (3%). Sensitivity analysis confirmed a robust model.

INTERPRETATION

Radiotherapy provides significant 5-year LC and OS benefits as part of evidence-based cancer care. CRT provides modest additional benefits.

Abstract P5-14-11: An estimation of the population survival benefit of first-line chemotherapy and immunotherapy for breast cancer

Purpose:Randomized clinical trials describe the benefit of chemo-and immunotherapy for specific breast cancer patients with selected patient and disease characteristics. However, variability in practice occurs despite evidence-based guidelines [1]. The overall survival benefit for the whole population of breast cancer patients in Australia, if evidence-based guidelines for chemo-and immunotherapy were implemented, is unknown. Our study's purpose was to estimate the overall population survival benefit of routinely using evidence-based practice.

Methods and Materials:Decision trees with evidence-based indications for chemotherapy have been previously defined [2]. Each branch corresponds to a specific cohort who have, or do not have, defined indications for chemotherapy and/or immunotherapy. Chemo -and immunotherapy benefit was defined as the absolute incremental benefit of either chemotherapy and/or immunotherapy over no chemo- and/or immunotherapy for radical and palliative indications. Multiple electronic citation databases were systematically queried, including Medline and the Cochrane Library. In cases where there were multiple sources of the same level of evidence, hierarchical meta-analysis was performed. The benefits of chemo- and immunotherapy were estimated for 1, 5, 10-year survival. To assess the robustness of our estimates, sensitivity analyses were performed.

Results: The estimated 1-year, 5-year and 10-year absolute population-based overall survival benefits of optimally utilized chemo- and immunotherapy for breast cancer in Australia are 1.0% (95% CI, 0.9%-1.2%), 4.4% (95% CI, 4.3%-4.6%) and 5.2% (%-%), respectively. They are summarized in the Table 1.

Estimation of Population Survival Benefit for First Line Chemo- and Immuno TherapyBreast CancerProportion of all cancer in Australia1 year survival benefit (Sensitivity range)5 year survival benefit (Sensitivity range)10 year survival benefit (Sensitivity range)Stage I-II10.0%0.6% (0.6%-0.7%)4.8% (4.6%-5.0%)6.9% (6.7%- 7.2%)Stage III1.6%3.0% (3.0%-3.1%)6.1% (5.8%-6.3%)0%Stage IV0.5%5.3% (5.1%-5.5%)4.9% (4.7%-5.1%)0%Whole Breast Cancer population12.1%1.0% (0.9%-1.2)4.4% (4.3%-4.6%)5.2% (5.0%-5.4%)     

Conclusion: Chemo- and immunotherapy agents improves overall survival in breast cancer at 1-, 5- and 10-years. Chemo-and immunotherapy provides a modest survival benefit to this patient population in Australia when it is used in accordance with guideline recommendations. These outcomes may allow comparison of treatment outcomes in a jurisdiction against what would be considered optimal based on evidence.

1. Fong, A., et al., A comparison of systemic breast cancer therapy utilization in Canada (British Columbia), Scotland (Dundee), and Australia (Western Australia) with models of "optimal" therapy. Breast, 2012. 21(4): p. 562-9.

2. Ng, W., Estimating the optimal chemotherapy utilisation rate as an evidence-based benchmark in cancers of the breast, upper gastrointestinal tract, gynaecological tract, head and neck, kidney, bladder, thyroid and unknown primary., in University of NSW, Faculty of Medicine. 2010, UNSW: Sydney.

Citation Format: Delaney GP, Do V, Ng W, Barton MB. An estimation of the population survival benefit of first-line chemotherapy and immunotherapy for breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-14-11.

The Benefits of Providing External Beam Radiotherapy in Low- and Middle-income Countries

More than half of all cancer diagnoses worldwide occur in low- and middle-income countries (LMICs) and the incidence is projected to rise substantially within the next 20 years. Radiotherapy is a vital, cost-effective treatment for cancer; yet there is currently a huge deficit in radiotherapy services within these countries. The aim of this study was to estimate the potential outcome benefits if external beam radiotherapy was provided to all patients requiring such treatment in LMICs, according to the current evidence-based guidelines. Projected estimates of these benefits were calculated to 2035, obtained by applying the previously published Collaboration for Cancer Outcomes, Research and Evaluation (CCORE) demand and outcome benefit estimates to cancer incidence and projection data from the GLOBOCAN 2012 data. The estimated optimal radiotherapy utilisation rate for all LMICs was 50%. There were about 4.0 million cancer patients in LMICs who required radiotherapy in 2012. This number is projected to increase by 78% by 2035, a far steeper increase than the 38% increase expected in high-income countries. National radiotherapy benefits varied widely, and were influenced by case mix. The 5 year population local control and survival benefits for all LMICs, if radiotherapy was delivered according to guidelines, were estimated to be 9.6% and 4.4%, respectively, compared with no radiotherapy use. This equates to about 1.3 million patients who would derive a local control benefit in 2035, whereas over 615 000 patients would derive a survival benefit if the demand for radiotherapy in LMICs was met. The potential outcome benefits were found to be higher in LMICs. These results further highlight the urgent need to reduce the gap between the supply of, and demand for, radiotherapy in LMICs. We must attempt to address this 'silent crisis' as a matter of priority and the approach must consider the complex societal challenges unique to LMICs.

The Population Benefit of Radiotherapy for Malignant Brain Tumors: Local Control and Survival Estimates for Guideline-Based Use

OBJECTIVE

To estimate the population benefit of radiotherapy (RT) for primary malignant brain tumors if evidence-based guidelines were routinely followed.

METHODS

This study investigated 5-year local control (LC) and 2- and 5-year overall survival (OS) benefits. RT benefit was the absolute proportional benefit of RT alone over no RT for radical indications, and over surgery alone for adjuvant indications. Chemoradiotherapy (CRT) benefit was the absolute incremental benefit of concurrent chemotherapy and RT over RT alone. Decision tree models were adapted to define the incidence of each indication. Citation databases were systematically queried for the highest level of evidence defining indication benefits. Meta-analysis was performed if there were multiple sources of the same evidence level, and deterministic and probabilistic sensitivity analysis was also performed.

RESULTS

Among all patients with malignant brain tumors, 82% had indications for curative- or adjuvant-intent RT. The magnitude of benefit was based on level I or II evidence in 44% of all patients. A total of 25 relevant studies were used to quantify indication benefits. All RT benefit included in the model was irreplaceable. For malignant brain tumors, the estimated population benefit for RT alone was 9% for 5-year LC (95% CI, 7%-10%), 9% for 2-year OS (95% CI, 8%-11%), and 5% for 5-year OS (95% CI, 4%-5%). The incremental benefit of CRT was 1% for 5-year LC (95% CI, 0%-2%), 7% for 2-year OS (95% CI, 4%-11%), and 3% for 5-year OS (95% CI, 1%-5%). The model was robust in sensitivity analysis.

CONCLUSIONS

When optimally used, RT provides an important benefit for many patients with malignant brain tumors. The model provided a robust means for estimating the magnitude of this benefit.

A Population-based Model of Local Control and Survival Benefit of Radiotherapy for Lung Cancer

AIMS

To estimate the population-based locoregional control and overall survival benefits of radiotherapy for lung cancer if the whole population were treated according to evidence-based guidelines. These estimates were based on a published radiotherapy utilisation (RTU) model that has been used to estimate the demand and planning of radiotherapy services nationally and internationally.

MATERIALS AND METHODS

The lung cancer RTU model was extended to incorporate an estimate of benefits of radiotherapy alone, and of radiotherapy in conjunction with concurrent chemotherapy (CRT). Benefits were defined as the proportional gains in locoregional control and overall survival from radiotherapy over no radiotherapy for radical indications, and from postoperative radiotherapy over surgery alone for adjuvant indications. A literature review (1990-2015) was conducted to identify benefit estimates of individual radiotherapy indications and summed to estimate the population-based gains for these outcomes. Model robustness was tested through univariate and multivariate sensitivity analyses.

RESULTS

If evidence-based radiotherapy recommendations are followed for the whole lung cancer population, the model estimated that radiotherapy alone would result in a gain of 8.3% (95% confidence interval 7.4-9.2%) in 5 year locoregional control, 11.4% (10.8-12.0%) in 2 year overall survival and 4.0% (3.6-4.4%) in 5 year overall survival. For the use of CRT over radiotherapy alone, estimated benefits would be: locoregional control 1.7% (0.8-2.4%), 2 year overall survival 1.7% (0.5-2.8%) and 5 year overall survival 1.2% (0.7-1.9%).

CONCLUSIONS

The model provided estimates of radiotherapy benefit that could be achieved if treatment guidelines are followed for all cancer patients. These can be used as a benchmark so that the effects of a shortfall in the utilisation of radiotherapy can be better understood and addressed. The model can be adapted to other populations with known epidemiological parameters to ensure the planning of equitable radiotherapy services.

The potential for an enhanced role for MRI in radiation-therapy treatment planning

The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors.

The Development of a New Basic Treatment Equivalent Model to Assess Linear Accelerator Throughput

AIMS

The basic treatment equivalent (BTE) model was developed in 1996 in an attempt to improve the measurement of linear accelerator throughput in radiotherapy. This study aimed to assess the effect of treatment set-up and patient characteristics on fraction duration, to update the BTE model and to determine the better throughput measure between fields per hour and BTE per hour.

MATERIALS AND METHODS

Stopwatch measurements of the duration of each radiotherapy treatment fraction delivered on each linear accelerator in participating New South Wales radiation oncology departments over a 5-day period in 2003 were undertaken. Patient, equipment and staff data were collected to assess the effect of these variables on fraction duration. A new BTE equation was derived, including the most significant variables. Statistical comparison of fields and BTE per unit time was made to assess the better predictor of fraction duration.

RESULTS

Data collected on 27 linear accelerators in 13 departments included a total of 135 days of linear accelerator operation, 4316 fractions and 12 892 treatment fields. Seventeen factors significantly influenced fraction duration (P < 0.01). These accounted for 46% of the total variance in the models. The eight most influential predictors of prolonged fraction duration were included in the BTE model. These were as follows: high number of fields, high number of port films/electronic portal imaging, absence of automatic field-sequencing and multi-leaf collimation, high number of junctions, use of bolus and first fraction of a treatment course. The BTE per hour was shown to be a better predictor of throughput than fields per hour.

CONCLUSIONS

The BTE model is a better measure of linear accelerator throughput. It incorporates weightings for treatment and patient factors that significantly influenced fraction duration. This measure could be routinely collected by the radiation oncology departments and included in the electronic radiotherapy information systems.

Technology Enhancements and Changes in Radiotherapy Throughput in New South Wales

AIMS

To assess the effect that the age of linear accelerators and recent changes in technology have had on linear accelerator throughput in New South Wales, Australia.

MATERIALS AND METHODS

Duration was measured (time of patient entry into the treatment room to time of exit) of each radiotherapy treatment fraction delivered on each linear accelerator over a 5-day period. Patient-, treatment- and equipment-based variables were collected for all treatment fractions, and assessed for their effect on fraction duration. Comparisons were made between these data and similar productivity data collected from a study carried out in 1996. Since the sample sizes for both the study periods were large enough, the distributions of the means were assumed normal (Central Limit Theorem). Specific analyses were carried out to assess the affect that new technologies, such as automatic field-sequencing (AFS) and multi-leaf collimator (MLC), have had on fraction duration.

RESULTS

A total of 12 892 treatment fields and 4316 treatment fractions were delivered on 27 linear accelerators over 135 days. Comparison between the 2003 and 1996 productivity data showed an increase in the mean number of patients treated per hour by 11% and fields treated per hour by 31%. The mean number of fields treated per fraction increased by 15%. The mean fraction duration was reduced by 13% for linear accelerators of less than the median age of 7 years that were equipped with MLC/AFS, or both, compared with older linear accelerators without AFS and MLC. This reduction was more obvious for complex techniques, such as four-field breast treatments (27% decrease in fraction duration). The mean number of fields treated per hour was 43% more on the newer machines equipped with AFS and MLC.

CONCLUSIONS

An increase in productivity has been observed between the 1996 and 2003 study periods, as measured by patients or fields per hour, despite an increase in treatment complexity as measured by fields per fraction. The application of AFS and MLC, and the use of newer linear accelerators, significantly shortened the mean duration per fraction for the common treatment techniques.

Lung cancer patterns of care in south western Sydney, Australia

BACKGROUND

Lung cancer is the leading cause of cancer deaths in New South Wales (NSW). There is a significantly higher incidence of lung cancer in the South Western Sydney Area Health Service (SWSAHS) than the NSW average. The aim of this study was to document patterns of lung cancer care for SWSAHS residents.

METHODS

SWSAHS residents diagnosed with lung cancer in 1993 and 1996 were identified from the NSW Central Cancer Registry and their medical records reviewed.

RESULTS

The study population comprised 527 patients of median age 68 years. 12% did not see a lung cancer specialist, 9% did not have a pathological diagnosis, and 28% did not receive any active treatment throughout the course of their illness. The median survival was 6.7 months and the 5 year overall survival was 8% (95% CI 6 to 10). The rates of pathological diagnosis, specialist referral, and treatment decreased with older age and poorer performance status.

CONCLUSIONS

The management of lung cancer patients in SWSAHS is suboptimal. A significant proportion of patients are not receiving treatment. To improve patient care and outcomes, all lung cancer patients should be referred to a specialist for management, ideally in a multidisciplinary setting. Both consumers and general practitioners need to be educated about options available for the management of lung cancers and ageist and nihilistic attitudes need to be overcome.

An assessment of the Basic Treatment Equivalent (BTE) model as measure of radiotherapy workload

Current methods of linear accelerator workload analysis in radiation oncology use patients per hour or fields per hour as the basic unit of measurement but fail to take account of the variations in complexity of different treatment techniques. The Basic Treatment Equivalent (BTE) model of productivity assessment has been derived as a potentially better measure of workload because it includes a complexity factor. This model has now been tested prospectively in ten radiation oncology departments in New South Wales and compared with the numbers of fields and patients per hour. Over a 4-week period there were 50,115 fields administrated in 18,466 fractions in 441 hours of machine time in ten radiation oncology departments. The average productivity results for all departments were 4.18 patients, 11.25 fields and 5.66 BTE per hour. When compared with patients per hour and fields per hour, there was less variability of BTE per patient per hour in all departments, suggesting that most departments deliver radiation therapy in a consistent way, which is not appropriately reflected in the numbers of fields or patients per hour. Departments that were able to treat a high number of patients or fields per hour were able to do so because they used less complicated techniques or had a less complicated casemix of patients. The BTE model allows for variations in the complexity of treatment techniques, is simple to apply, and is reproducible under different conditions in different departments. Following revision of the model, an Australasian study is now proposed. The confirmation of our findings will have significant implications for resource utilization comparisons, patient time allocations, waiting list estimates and cost-benefit analysis.

Basic Treatment Equivalent (BTE): a new measure of linear accelerator workload

The measurement of linear accelerator workload in radiation oncology departments is usually based on the number of fields treated per unit time. However, this approach ignores variations in treatment complexity. This prospective study, was designed to measure treatment workload directly, taking into account the variations in complexity of different treatment techniques. From this, a model was to be developed, which would be simple to apply and reproducible, both within and between radiation oncology departments in Australasia. It would provide a realistic basis for assessing treatment costs and enable the comparison of patient throughput between departments. This paper describes the derivation of the model. Over a 4-week period in the Radiation Oncology Department of Westmead Hospital, all fractions of radiotherapy were timed. The data collected included: tumour site; treatment intent; number of fields; number of wedges, compensators and shielding blocks; fraction number; patient age; performance status; and need for general anaesthesia. Multivariate modelling was performed to identify factors that significantly affected fraction duration, so that these could be used to develop a model of resource utilization. The durations of 2371 fractions were measured in 219 patients. Seventy-five per cent of fractions were given with radical intent. The factors found to influence fraction duration on multivariate modelling were: number of fields; number of shielding blocks; first treatment fraction; need for anaesthesia; and performance status. The number of wedges and compensators were also found to be significant but were not included in the model in order to maintain simplicity. This was felt to be necessary if the model is to be applied to the widest possible variety of machines. A model of resources utilization called 'Basic Treatment Equivalent' (BTE) was derived, which incorporated these factors. When tested at Westmead Hospital, this model accurately reflected the predicted BTE value over a further 1-week study period. This model of linear accelerator use, which incorporates complexity has been derived and evaluated in one radiation oncology department. This requires further prospective testing before its widespread use. The model appears to reflect linear accelerator workload better than previous measures. An Australasian study to validate the model further will be undertaken. If adopted, this model has implications for comparative workload reports, diagnostic-related groups, waiting list calculations, and patient scheduling.

The equivalent simple treatment visit (ESTV) model does not measure radiation oncology productivity under Australian conditions

The measurement of workload in radiation oncology departments has been based on the number of patients treated per linear accelerator per unit time, or on the number of fields treated per linear accelerator per unit time. The Equivalent Simple Treatment Visit (ESTV) model was proposed to allow for the incorporation of a factor for complexity of treatment techniques, to permit more detailed comparisons than those offered by previous measures. This prospective study was designed to assess the suitability of the ESTV model as a measure of radiation oncology productivity within an Australian radiation oncology department. A calculated ESTV value was assigned to all treatment fractions delivered in our department over a 4-week period. Treatment fractions were then timed using a stopwatch, and average treatment times for simple, intermediate and complex techniques were calculated and analysed by multiple t-tests for statistical significance. Average treatment times were 8.1 minutes (standard deviation (SD) = 4.2) for 'simple' techniques, 14.1 minutes (SD = 4.4) for 'intermediate' techniques, and 11.8 minutes (SD = 5.6) for 'complex' techniques. These times were significantly different from each other (P < 0.05). Although ESTV attempts to allow for the incorporation of a complexity factor into productivity reporting, a revision of the model is necessary, given the inconsistency by which a 'complex' technique takes significantly less time than an 'intermediate' technique.

Split-course accelerated therapy in head and neck cancer: an analysis of toxicity

PURPOSE

To retrospectively assess a protocol of split-course accelerated radiation therapy (SCAT) for selected head and neck cancers.

METHODS AND MATERIALS

SCAT consisted of 1.8 Gy per fraction administered twice daily with a minimum gap between fractions of 6 h. The treatment protocol prescribed an initial 16 fractions followed by a planned 5 to 12 day break, and then a further 20 to 22 fractions for a total dose ranging from 64.8 to 72 Gy delivered in 5 to 6 weeks.

RESULTS

Twenty-eight patients received SCAT for histologically confirmed head and neck cancer between January 1987 and August 1991. All patients were followed up until December 1, 1993. The mean potential follow-up time was 4.2 years (range: 2.9-6.2 years). All patients completed the treatment protocol. Thirteen tumors were laryngeal in origin, eight hypopharyngeal, four paranasal sinus, and three oropharyngeal. There were no Stage I, three Stage II, nine Stage III, and 12 Stage IV tumors. Four tumors were not staged (two paranasal sinus cancers and two surgical recurrences). Early and late toxicities were moderate to severe. Confluent mucositis was experienced by 27 of the 28 patients (96%). One patient required a prolonged midtreatment break of 24 days. Nine patients (32%) required narcotic analgesia for pain relief. Eleven patients (39%) required hospitalization for nasogastric feeding or pain control. The median length of hospital stay was 14 days (range 7-98 days). The actuarial rate of severe late toxicity at 3 years was 47% (standard error (SE) = 13%). A complete tumor response was achieved in 86% of patients. The actuarial local control rate at 3 years was 43% (SE = 11%) and the actuarial survival rate at 3 years was 25% (SE = 8%).

CONCLUSION

Given the encouraging complete response rate and local control for such advanced tumors, SCAT for locoregionally advanced tumors merits further investigation. However, because of the significant late toxicity observed, the total dose, interfraction interval, and fractionation technique used should be reconsidered.