Evaluating the feasibility of palliative radiotherapy planning for symptomatic bone metastases using diagnostic computed tomography

Introduction

Bone metastases pose a significant clinical challenge, often leading to a cascade of adverse effects that severely diminish patient’s quality of life (1). In addition to pain, metastatic disease may result in neurological and other debilitating symptoms, frequently necessitating urgent radiation therapy (1-4). Conventional radiotherapy workflows typically involve a multi-step process beginning with the initial consultation, followed by planning computed tomography (CT) simulation and treatment planning, and concluding with treatment delivery. This sequence can span up to two weeks, placing a considerable burden on the patients—particularly those experiencing intense symptoms requiring prompt palliative intervention.

Amid these clinical challenges, the use of diagnostic CT for dosimetric planning has emerged as a promising alternative (5-12). Although differences in Hounsfield units (HUs) between diagnostic CT and planning CT exist, diagnostic CT has shown promising potential in palliative treatment planning for metastatic bone disease, largely due to the relatively minor variation in HUs within the bone structures (7). As diagnostic CT images are often readily available to radiation oncologists during the initial consultation, this approach offers the compelling possibility of bypassing the planning CT simulation step—significantly reducing the time between consultation and radiation therapy.

Despite its potential, the use of diagnostic CT for radiation therapy treatment planning in bone metastases remains underexplored, particularly regarding its impact on key dosimetric parameters compared to plans generated from planning CT. The objective of the study is to (I) evaluate the reduction in time from initial consultation to treatment delivery; and (II) perform a dosimetric comparison between diagnostic CT-based treatment plans and original clinical plans. We present this article in accordance with the STROBE reporting checklist (available at https://apm.amegroups.com/article/view/10.21037/apm-25-40/rc).

Methods

Patient selection

Our study included 20 patients who received palliative radiotherapy (26 treatment plans) for symptomatic bone metastases at our institution treated between April 2020 and May 2023. Out of the entire patients in our database, four patients were excluded due to unavailable diagnostic CT scans, and three were excluded because the entire target volume was not within the diagnostic CT field of view, resulting in a total of 26 plans for 20 eligible patients for analysis. Table S1 illustrates the Dicom metadata of the diagnostic CT utilized in our retrospective study. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Mount Sinai Hospital (approval No. GCO# 18-0953, IRB STUDY# 18-00450) and was granted a waiver of informed consent.

Time analysis

The image acquisition dates of both the diagnostic CT and planning CT scans were recorded for time analysis. The reduction in time, resulting from the elimination of a separate planning CT simulation, was calculated from the date of the initial physician consultation to the date of CT simulation, since a dosimetrist could use the diagnostic CT for treatment planning.

Image registration and treatment planning

Bony anatomy was used for rigid registration between the diagnostic CT and the planning CT to propagate contours, including organs at risk (OARs) and target volumes, for treatment planning. Additionally, the clinically approved beam arrangements and administered monitor units (MUs) from the original plan were transferred to the diagnostic CT for dose calculation.

During diagnostic CT acquisition, patients were positioned on a curved couch top, whereas treatment delivery occurs on a flat couch top, potentially leading to significant anatomical variation between the two cases. As shown in Figure 1, particularly in larger patients, such discrepancy is more significant and can compromise the dose contributed from static lateral beams and reduce treatment accuracy. Furthermore, the limitation of using an anterior/posterior (AP/PA) field is the increased dose in the anterior side of the patient where organs-at-risk could potentially get higher dose as shown by the dose distribution in Figure 1. Therefore, in this study, six out of the total 26 plans (~23%) were re-planned to use primarily anterior or posterior beam directions. Similarly, the new beam arrangements (AP/PA) and administered MUs made on the planning CT are transferred back to the diagnostic CT for dose calculation and comparison.

Figure 1 Dose distribution comparison between treatment plans on diagnostic CTs (A,B) and planning CTs (C,D) using different beam arrangements for a patient treated to the sacrum. (A,C) Show original lateral beam arrangement, while (B,D) depict the anterior-posterior beam arrangements. The figure displays a transverse slice. CT, computed tomography.

Statistical analysis

Plan quality was quantitatively evaluated using the following three dosimetric metrics, followed by statistical analysis:

• Planning target volume (PTV) V95% (%): the percentage of the PTV receiving at least 95% of the prescribed dose.
• PTV mean dose (D_mean) (%) the mean dose delivered to the PTV, expressed as a percentage of the prescription dose.
• Global hotspots (%): the maximum dose of 0.03 cm³ volume within the patient, expressed as a percentage of the prescription dose.

Statistical significance was determined using a paired t-test, with a P value <0.05 considered significant, for both the decrease in PTV V95% coverage and the increase in hotspot percentage. The correlation between changes in coverage and hotspot values was also assessed using the following formula:

correlation(x,y)=∑(x−x¯)(y−y¯)∑(x−x¯)2(y−y¯)2[1]

Results

Patient and radiotherapy characteristics

The baseline characteristics of the 20 patients included in this study are summarized in Table 1. The median age of the cohort was 69 years (range, 49–88 years). The cohort consisted of an equal proportion of male and female patients. The most commonly treated site was spine, followed by hip. Other sites include base of skull sites. Furthermore, long bone includes sites such as femur and extremities include sites such as shoulder/clavicle. As demonstrated by Wong et al., there were no statistically significant differences in bone HU values between diagnostic and planning CT scans, supporting the feasibility of using diagnostic CT images for clinical treatment planning in palliative radiotherapy (7). All patients received three-dimensional conformal radiotherapy (3D CRT) using photon beam energies of either 6 megavolt (MV) (n=13) or 16 MV (n=7).

Time analyses

As shown in Table 2, among the 26 treatment plans, the average time between the initial consultation and CT simulation was 6.5 days [standard error (SE): 1.2 days], while the average time between CT simulation and treatment delivery was 4.5 days (SE: 0.8 day). Notably, 17 treatment plans (65.4%) spent at least half of the total waiting period between consultation and treatment awaiting a CT simulation appointment. By eliminating the CT simulation step, on average, an estimated 59% of the total time to treatment could be reduced per plan.

Evaluation of key clinical dose metrics

For the 20 patients included in this study, fields and target volumes from 26 clinically treated plans were successfully transferred to the corresponding plans calculated on diagnostic CT following rigid registration. Figure 2 illustrates the transferred target and OAR contours for a representative treatment plan. The corresponding dose distribution and the dose-volume histograms (DVHs) for both the target and OAR structures are shown in Figure 3. A DVH summarizes the dose distribution across target volumes and OARs. The x-axis shows relative dose (%), and the y-axis shows the percentage of volume receiving at least that dose. In Figure 3, the PTV (blue curves) maintains high volume until near the prescription dose, indicating excellent target coverage on both planning and diagnostic CT. OARs, such as esophagus, heart, lungs, and spinal cord, show rapid dose fall-off, reflecting effective sparing of the critical organs. DVH comparisons confirm consistency between imaging modalities and provide a clear assessment of plan quality. Among subgroup of spinal cases, the average esophagus max dose was comparable between diagnostic and planning CT-based plans (1,667 vs. 1,655 cGy), while the average mean dose was slightly lower in diagnostic plans (703 vs. 772 cGy), suggesting overall dose consistency across planning approaches (13).

Figure 2 Target contour transferred from diagnostic CTs (top row left: transverse, top row middle: coronal, top row right: sagittal) to planning CTs (bottom row left: transverse, bottom row middle: coronal, bottom row right: sagittal) and dose distribution following rigid registration and treatment planning. Note that planning CT is the top view and the diagnostic CT is the bottom view. CT, computed tomography.

Figure 3 DVH curves comparing the treatment plans on the planning CT and diagnostic CT with target volume and organs at risk. CT, computed tomography; DVH, dose volume histogram; PTV, planning target volume.

Key clinical dose evaluation metrics—including PTV V95%, D_mean, and hotspot (D_max) were compared in Table S2 and Figure 4. Among the 26 diagnostic CT plans, three had PTV V95% coverage below 95%. However, two of these were intentionally under-covered in the original clinical treatment plans, with V95% values of 61.9% and 63.0%, due to overlapping radiation fields. On average, PTV V95% coverage decreased by 1.33% (SE: 0.65%), and the mean dose decreased by 0.43% (SE: 0.51%). The global hotspot (D_max) across all patients averaged 111.3% (SE: 0.59%), reflecting an average increase of 1.95% (SE: 0.004%) compared to the corresponding clinical treatment plans. Both the reduction in V95% coverage and the increase in hotspot values were statistically significant, with one-tailed paired t-test P values of 0.01 and <0.001, respectively. The decrease in mean dose was not statistically significant (P=0.21). Additionally, a correlation coefficient of −0.08 was observed between changes in PTV V95% coverage and hotspot values, indicating that increased dose intensity does not necessarily improve target coverage. Subgroup analysis showed that the average target coverage (V95%) was slightly higher for spine sites (94.9%) compared to non-spine sites (90.6%), though both groups demonstrated high overall coverage in diagnostic CT-based plans.

Figure 4 Illustrates paired box plots of the dosimetric parameters utilized in this study for planning and diagnostic CT plans for the target volume. V95% represents the percentage of volume that receives at least 95% of the prescription dose. Dmean is the mean dose and Dmax is the max dose. CT, computed tomography.

Discussion

This study demonstrates that incorporating diagnostic CT into palliative radiotherapy treatment planning can significantly reduce the time from initial consultation to treatment delivery for patients with bone metastases by eliminating the need for a separate CT simulation visit (Figure 5). Given that patients with metastatic bone lesions often present with urgent clinical symptoms—such as severe pain, neurological compromise, or other complications requiring prompt intervention (1)—this streamlined approach is clinically useful and can offer an earlier option for treatment based on the clinical decisions made by the physician. It offers the potential for same-day treatment following consultation. Urgent radiotherapy with planning CT acquisition can be performed for these patients; however, this approach may increase the clinical workload. Potential time-saving maneuvers include direct contouring on the diagnostic CT, bypassing scheduling delays associated with CT simulation, and enabling same-day planning and treatment delivery. This study provides an independent validation of the feasibility, accuracy, and clinical utility of using diagnostic CT for radiotherapy planning for symptomatic bone metastases (3,5,6,8).

Figure 5 Conventional workflow requiring CT simulation vs. the proposed workflow. CT, computed tomography.

In recent years, there has been a deliberate shift away from prolonged palliative regimens (≥10 fractions) toward shorter, equally effective treatment courses (1–5 fractions) (14). However, in the context of fractionation, multiple fractions is recommended to allow for re-calcification leading to higher bone stability (15). This transition reduces the number of hospital visits and the associated healthcare costs, which is important for patients receiving palliative care. In this context, bypassing conventional CT simulation represents an additional opportunity to optimize treatment efficiency. Emerging technologies such as adaptive radiotherapy also offer opportunities for CT sim-free workflows and should be explored in future studies for palliative radiotherapy settings (16,17).

Moreover, in the wake of the coronavirus disease 2019 (COVID-19) pandemic, there has been heightened awareness among healthcare providers of the importance of minimizing in-person visits. This approach supports that objective by balancing the need to reduce exposure risks with the imperative to provide timely care for patients with urgent palliative needs. The feasibility of this workflow is supported by the dosimetric analysis conducted in this study. Beam arrangements transferred via rigid registration demonstrated that the dose distribution within each patient’s anatomy was reproduced, with only a 1.33% decrease in PTV V95% target coverage and a 1.80% increase in hotspot max dose. These variations were primarily attributed to anatomical differences between diagnostic CTs and planning CTs. The average V95% coverage across the 26 diagnostic CT-based plans remained adequate at 95.3% (SE: 0.19%), meeting the recommendations outlined in ICRU Report 50 (18). Our results suggest that diagnostic CT planning can achieve adequate target coverage (based on V95%) in selected cases; however, we acknowledge that additional plan quality metrics, such as conformity OAR sparing, were not fully evaluated and warrant further investigation. A limitation of this study is the absence of quantitative dose comparisons for OARs, as the patient cohort includes multiple treatment sites with varying OARs. As a result, only qualitative comparisons of DVHs were performed (e.g., see Figure 3).

Despite the promising benefits of this approach, it is important to acknowledge the limitations of this study. Specifically, out of 33 treatment plans across 27 patients, 7 plans (21%) were excluded from analysis due to missing or incomplete diagnostic CTs that failed to incorporate the target region. However, such issues can typically be identified during the initial consultation and may be avoided if patients undergo diagnostic imaging at the treating facility, where imaging protocols can be standardized to ensure adequate target coverage. Our study is limited by the absence of clinical outcome data (e.g., pain relief, re-irradiation, patient outcome), which should be addressed in future prospective studies evaluating the efficacy of CT simulation-free workflows.

AP/PA beam configurations may offer improved dose distribution and reproducibility by mitigating the inconsistencies introduced by using different couches during diagnostic imaging and treatment delivery. However, anatomical variations between the diagnostic CT and actual treatment positioning can introduce uncertainties in dose distribution. This raise concerns in patients with non-standard anatomy, in which they may require individualized planning considerations or more stringent eligibility criteria (surgery or resection changes and lateral size changes on treatment couch, etc.), as determined by the treating physician. The omission of the simulation step also necessitates the use of cone-beam CT (CBCT) for target alignment verification, which may increase the time patients spend on the treatment couch. In cases involving bone extremities, reproducing the patient’s natural posture from the diagnostic scan can be particularly challenging, potentially adding complexity, time, and resource demands on the day of treatment. As such, refining patient selection criteria will be a critical focus for future research and clinical implementation. Although 3D technique was utilized in this study, intensity modulated radiotherapy (IMRT) and stereotactic body radiotherapy (SBRT) offers more conformal dose to the target, while minimizing dose to the critical organs (19). However, limitation of these modern approaches may include increased clinical resources and treatment time allocation.

This study evaluated the feasibility of using diagnostic CTs for treatment planning to reduce treatment wait times for patients presenting with symptomatic bone metastases. In circumstances where access to CT simulation is constrained—whether due to equipment downtime, limited scheduling availability—this approach provides an alternative pathway for delivering timely and high-quality treatment without unnecessary delays.

Conclusions

Our study demonstrates the effectiveness of using diagnostic CT scans to develop 3D CRT plans for palliative treatment in patients with bone metastases. Through careful beam arrangement during the planning process, the need for strict patient selection criteria or additional compensation for couch differences between planning and diagnostic CT images can be minimized. This approach enables the bypassing of the traditional simulation step, leading to a substantial reduction in time to treatment. As a result, patients can receive faster symptom relief—an essential component of palliative care. These findings highlight a promising advancement in improving both the efficiency and accessibility of palliative radiotherapy.

Acknowledgments

During the preparation of this work the author(s) used ChatGPT in order to improve the language and readability of the first draft. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://apm.amegroups.com/article/view/10.21037/apm-25-40/rc

Data Sharing Statement: Available at https://apm.amegroups.com/article/view/10.21037/apm-25-40/dss

Peer Review File: Available at https://apm.amegroups.com/article/view/10.21037/apm-25-40/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-25-40/coif). K.D. serves as an unpaid editorial board member of Annals of Palliative Medicine from February 2024 to January 2026. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Mount Sinai Hospital (approval No. GCO# 18-0953, IRB STUDY# 18-00450) and was granted a waiver of informed consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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