From probability to practice: demystifying when lung shunt fraction matters in ⁹⁰Y selective internal radiation therapy

Summary 

Building on the commendable work by Thomas et al., this editorial proposes a simplified workflow for pretreatment identification of patients needing macroaggregated-albumin-based lung shunt fraction prior to the ⁹⁰Y treatment.

Key Results 

• Thomas et al. introduced a boundary lung shunt fraction metric and provided a quantitative framework for determining whether patient-specific macroaggregated-albumin-based lung shunt fraction is needed prior to the ⁹⁰Y treatment.

• Building on Thomas et al.’s foundational work, this editorial proposes a simplified, 2-variable calculation applicable in most clinical scenarios.

• The simplified workflow produces equivalent results in a small local streamlined ⁹⁰Y dataset and lowers the barrier to clinical adoption.

We read with great interest the article by Thomas et al., “When is patient-specific lung shunt fraction necessary in ⁹⁰Y selective internal radiation therapy of liver cancer.”¹ Conventional ⁹⁰Y selective internal radiation therapy (SIRT) workflow involves an asynchronous mapping session with selective arteriography and ^99mTc macroaggregated albumin (MAA) administration to calculate the lung shunt fraction (LSF) prior to the ⁹⁰Y treatment session. Recent evidence has suggested that a streamlined ⁹⁰Y SIRT workflow without the mapping session is safe with equivalent oncologic outcomes in selected patients. Thomas et al. provided a crucial quantitative framework for a decision typically made qualitatively—determining which patient requires a ^99mTc-MAA mapping session to calculate LSF.

The authors’ work is commendable. They introduced the LSF_bound metric: the minimum LSF value at which lung dose limits achievable target volume dose. By combining this new metric with SPECT/CT-derived LSF distribution data from a sizable cohort of 297 patients with 354 ⁹⁰Y SIRT cases, the authors showed that MAA-based SPECT/CT-derived LSF rarely exceeds LSF_bound and restricts the target volume dose (median ≤ 1%, maximum ≤ 4%) for most patients with liver malignancy (eg, hepatocellular carcinoma [HCC] ≤ 8 cm and non-HCC tumors without macrovascular invasion). Furthermore, using receiver operator characteristics analyses and clinically relevant probability thresholds, the authors demonstrated that prospective use of LSF_bound can maintain 100% sensitivity and > 80% specificity across a wide range of whole liver doses. Their results provided additional quantitative evidence for streamlining ⁹⁰Y SIRT by adopting the “no-MAA” workflow.^2,3 The reduced time-to-treatment⁴ and cost along with improved patient access and satisfaction is making ⁹⁰Y SIRT more attractive across different stages of HCC⁵ and non-HCC tumors amenable to locoregional options.

Although the authors’ approach was ingenious, the proposed clinical workflow using LSF_bound necessitates estimation of whole-liver dose limit (Liver_max) for the calculation of toxicity threshold ratio (TTR) and measurement of the masses of the liver and lungs. Requiring these variables adds complexity and may prove cumbersome in clinical practice. Building on Thomas et al.’s foundational work, we propose a simplification to promote its clinical adoption.

The authors define LSF_bound as

$${\mathit{LSF}}_{\mathit{bound}\_\mathit{Thomas}\mathrm{ }et\mathrm{ }al.}\left(\mathrm{\%}\right)=\frac{1}{\left(\mathit{TTR}\times {\mathit{ratio}}_{\mathit{live}{r}_{\mathit{lungs}}}\right)+1}\times 100$$ (1)

where $\mathit{TTR}={\mathit{Liver}}_{\mathit{max}}\left(Gy\right)/{\mathit{Lung}}_{\mathit{max}}\left(Gy\right)$, and ${\mathit{ratio}}_{{\mathit{liver}}_{\mathit{lungs}}}={\mathit{mass}}_{\mathit{liver}}\left(kg\right)/{\mathit{mass}}_{\mathit{lungs}}\left(kg\right)$.

By substituting Liver_max, where

$${\mathit{Liver}}_{\mathit{max}}\left(Gy\right)=\frac{{PV}_{\mathit{max}}\left(Gy\right)\times {\mathit{mass}}_{PV}\left(kg\right)}{{\mathit{mass}}_{\mathit{liver}}\left(kg\right)}$$ (2)

the equation for LSF_bound can be transformed into

$${\mathit{LSF}}_{\mathit{bound}}\left(\mathrm{\%}\right)=\frac{1}{\left(\frac{{PV}_{\mathit{max}}\left(Gy\right)\times {\mathit{mass}}_{PV}\left(kg\right)}{{\mathit{mass}}_{\mathit{lung}}\left(kg\right)\times {\mathit{Lung}}_{\mathit{max}}\left(Gy\right)}\right)+1}\times 100$$ (3)

Acknowledging 3 common clinical realities, this equation can be simplified. First, an adult’s lung mass is remarkably consistent—approximately 1 kg for most patients—as noted in reference standard and in the authors’ cohort.^1,6 Second, liver tissue density—typically 1.03 to 1.05 kg/L—may be approximated to 1 kg/L. Third, SPECT/CT-derived LSF (LSF_SPECT) provides more accurate assessments of LSF compared to planar imaging.⁷ Clinical guidelines suggest a lung dose limit (Lungs_max) of 20 Gy when using LSF_SPECT.⁸  Equation (1) reduces to a simpler equation (4) with 2 variables: perfused volume and target dose, which are required by the dose calculation to begin with:

$${\mathit{LSF}}_{\mathit{bound}\_\mathit{simplified}}\left(\mathrm{\%}\right)=\mathrm{ }\frac{1}{\left(\frac{{\mathit{PV}}_{\mathit{max}}\left(\mathit{Gy}\right)\times \mathit{PV}\left(\mathit{L}\right)}{20}\right)+1}\times 100$$ (4)

This simplified equation obviates the estimation of whole-liver dose limit and measurement of liver/lung masses. In cases where Lungs_max may be different because of prior radiation deposition (eg, occupational exposure, external radiation, SIRT), baseline pulmonary disease restricting lung radiation, or LSF_planar is used instead of LSF_SPECT, a different Lungs_max should be used in the denominator. In patients where mass_lung may be significantly different from 1 kg (eg, chest wall deformities, prior lung resection, small stature), patient-specific mass_lung should be calculated from cross-sectional imaging.⁹

The final simplification of the workflow involves interpretation of the calculated LSF_bound. The probabilistic density functions¹⁰ for each tumor category may be used to calculate the exact P_LSF>LSFbound. Alternatively, a standard probability threshold could be adopted. For example, by adopting a P_thresh of 3%, direct comparison of the calculated LSF_bound can be made to the 97th percentile LSF in each of the tumor categories (3.8% for HCC < 3 cm, 7.6% for HCC between 3 and 8 cm, 8.3% for HCC > 8 cm, 26.4% for macrovascular invasion [MVI], 7.3% for non-HCC).^1,10 If LSF_bound is greater than the 97th percentile LSF in the specific tumor category, the risk that LSF would limit the treatment plan is < 3% and MAA-based LSF determination is unnecessary. On the contrary, if LSF_bound is less than the 97th percentile LSF in the specific tumor category, the risk of LSF limiting the treatment plan is > 3% and MAA-based patient-specific LSF should be obtained. In clinical scenarios involving greater risk of radiation pneumonitis, LSF₉₉ may be used for stricter patient selection for the “no-MAA” workflow.

This logic leads to a straightforward workflow for clinical adoption: (1) determine if MAA administration is required for multicompartment dosimetry; (2) choose a desired target dose and estimate target perfused volume for dose and LSF_{bound_simplified} calculation; (3) calculate LSF_{bound_simplified}; and (4) if LSF_{bound_simplified} is greater than LSF₉₇ of the appropriate tumor category, proceed with “no-MAA” workflow. All patients not amenable to the “no-MAA” workflow should follow the conventional “map-treat” workflow (Figure 1).

Figure 1.

Simplified ⁹⁰Y SIRT treatment planning workflow based on the clinical workflow proposed by Thomas et al. published 5 February 2026 in Radiology Advances  https://doi.org/10.1093/radadv/umag007.

Applying this simplified approach to the example cases in the authors’ supplemental material yields equivalent results to their original calculation (Table 1).¹ Case 1’s LSF_{bound_simplified} is 29.4%, greater than the 97th percentile LSF at 3.8% in the specific category of HCC < 3 cm. As a result, the probability of the actual LSF and the Lungs_max restricting the perfused volume dose is less than 3%. Similarly, for cases 2 and 5, the LSF_{bound_simplified} at 12.9% and 15.2%, respectively, and are both greater than the 97th percentile LSF at 7.6% and 7.3% in the respective categories of HCC between 3 and 8 cm and non-HCC tumors. For case 3 with an HCC > 8 cm, the LSF_{bound_simplified} at 7.8% is less than the 97th percentile in that specific tumor category at 8.3%. As a result, the probability of the actual LSF and the Lungs_max restricting the perfused volume dose is greater than 3%. MAA-based patient-specific LSF should be obtained. For case 4 with MVI, the LSF_{bound_simplified} at 19.8% is less than the 97th percentile LSF at 26.4%. Similar to case 3, MAA-based mapping session is recommended. Such results demonstrate that the simplified equation (4) retains the core predictive utility in determining whether MAA-based patient-specific LSF is needed.

Table 1.

Comparison of LSF_bound Calculations in Example Cases from Thomas et al.*

	HCC < 3 cm	HCC 3–8 cm	HCC > 8 cm	MVI	Non-HCC
PV volume (mL)	95	330	780	540	360
Target PV dose (Gy)	505	410	305	150	310
LSFbound_simplified	29.4%	12.9%	7.8%	19.8%	15.2%
LSFbound_LiverMax	23.6%	13.9%	6.3%	14.4%	11.2%
LSFbound_LiverRx	30.5%	14.6%	6.7%	19.6%	12.6%
LSF97	3.8%	7.6%	8.3%	26.4%	7.3%
LSFbound_simplified < LSF97	No	No	Yes	Yes	No
PLSF>LSFbound_simplified	< 3%	< 3%	> 3%	> 3%	< 3%
PLSF>LSFbound	0%	0%	13%	18%	2%
PLSF>LSFbound_Thomas et al.	0%	0%	10%	13%	3%
Interpretation	Very low risk, MAA-based LSF can be omitted	Very low risk, MAA-based LSF can be omitted	Higher risk, MAA-based LSF should be obtained	Higher risk, MAA-based LSF should be obtained	Very low risk, MAA-based LSF can be omitted

Abbreviations: HCC = hepatocellular carcinoma, LSF = lung shunt fraction, LSF_bound = lung shunt fraction boundary where the maximal permitted lung dose starts to restrict the maximal dose to the perfused volume, LSF_{bound_LiverMax} calculated exactly as defined in Thomas et al. using estimated maximum mean dose to the liver, LSF_{bound_LiverRx} = lung shunt fraction boundary calculated using retrospectively determined mean dose to the liver as reported in Thomas et al., LSF_{bound_simplified} = lung shunt fraction boundary computed using the simplified equation (4), MAA = macroaggregated albumin, MVI = macrovascular invasion, PV = perfused volume.

^*Thomas et al. published 5 February 2026 in Radiology Advances  https://doi.org/10.1093/radadv/umag007.

The proposed workflows, original and simplified, have also been retrospectively applied to a local single-centered experience of “no-MAA” ⁹⁰Y SIRT. Institutional review board approval was obtained with written consent waived. From July 2024 to April 2026, 16 patients (3 female, 13 male; age 70.5 ± 2.8 [mean ± standard errors of the mean]) underwent 17 “no-MAA” radiation segmentectomy for 17 HCCs (15 < 3 cm, two 3–8 cm) using resin ⁹⁰Y microspheres. Perfused volumes were 149.0 ± 19.3 mL, accounting for 8.7 ± 1.3% of the total liver volume, with target perfused volume dose at 450 ± 53 Gy. LSF_{bound_LiverRx}, calculated using retrospectively determined mean dose to the liver, was 27.3 ± 2.5%; LSF_{bound_LiverMax}, calculated as defined by Thomas et al. using estimated mean doses to the liver, was 15.5 ± 1.0%; LSF_{bound_simplified}, calculated using (4), was 28.1 ± 2.4% (analysis of variance P < .0001; pairwise comparison demonstrated that LSF_{bound_LiverRx} and LSF_{bound_simplified} are equivalent, P = .5). None of the calculated LSF_bound values was smaller than LSF₉₇ for the respective tumor categories (3.8% for HCC < 3 cm, 7.6% for HCC 3–8 cm). Post ⁹⁰Y treatment SPECT/CT revealed clinical LSF at 6.2 ± 0.7% (maximum: 10.5%) and Lung_Rx 4.0 ± 0.7 Gy (maximum: 12.2 Gy). Pretreatment calculations of LSF_bound, original or simplified, would have provided quantitative confidence that MAA-based LSF determination was not necessary in these cases, validating a “no-MAA” approach.

It is important to note that this method, original or simplified, has limitations as noted in the authors’ article. The model’s probabilities rely on the authors’ single center dataset, which, although ample, had limited representation of subgroups like HCC with MVI and large HCC > 8 cm. Institutional and population specific probability density functions should be evaluated and used. Furthermore, the proposed workflow does not apply when MAA SPECT/CT is essential for multicompartment dosimetry. Finally, the conventional ⁹⁰Y SIRT workflow with separate mapping and treatment sessions should remain as the back-up option for patients not amenable to the streamlined workflow.

Ultimately, the study by Thomas et al. represents an important evolution in ⁹⁰Y SIRT. It moves the field from qualitative, population-based heuristics to quantitative, patient-specific probability determination. Instead of asking, “What is the LSF?”, they reframed the question to “Does LSF matter for this patient’s treatment plan?” This editorial builds on their excellent framework by demonstrating that their core insight can be distilled into a simpler, 2-variable calculation in most clinical scenarios. We hope this simplification lowers the barrier to clinical adoption, thereby empowering interventional radiologists to streamline ⁹⁰Y SIRT workflow for a broader patient population with quantitative confidence.

Funding

No funding was received during the preparation of this manuscript.

Conflicts of interest

N.L. receives funding from the Society of Interventional Radiology and the Radiological Society of North America, serves on the editorial board for Radiology Advances and Journal of Vascular and Interventional Radiology. S.K. reports no conflict of interests. T.F. reports no conflict of interests. N.J.R. receives support from Terumo Medical Corporation, Boston Scientific Corporation, and Inari Medical Incorporated.

Data availability

Data available on request.