
==== Front
Phys Imaging Radiat Oncol
Phys Imaging Radiat Oncol
Physics and Imaging in Radiation Oncology
2405-6316
Elsevier

S2405-6316(24)00101-5
10.1016/j.phro.2024.100631
100631
Short Communication
Comparison of image registration methods in patients with non-melanoma skin cancer treated with superficial brachytherapy
Szlag Marta marta.szlag@nio.gov.pl
⁎
Stankiewicz Magdalena
Kellas-Ślęczka Sylwia
Stąpór-Fudzińska Małgorzata
Cholewka Agnieszka
Pruefer Agnieszka
Wojcieszek Piotr
Maria Sklodowska-Curie National Research Institute of Oncology Gliwice branch Wybrzeże Armii Krajowej Street 15, 44-101 Gliwice, Poland
⁎ Corresponding author. marta.szlag@nio.gov.pl
17 8 2024
7 2024
17 8 2024
31 10063127 2 2024
14 8 2024
15 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The accumulated dose from sequential treatments of metachronous non-melanoma skin cancer can be assessed using image registration, although guidelines for selecting the appropriate algorithm are lacking. This study shows the impact of rigid (RIR), deformable (DIR) and deformable structure-based (SDIR) algorithms on the skin dose. DIR increased: the maximum dose (39.2 Gy vs 9.4 Gy), the dose to 0.1 cm3 (16.4 Gy vs 7.8 Gy) and the dose to 2 cm3 (7.6 Gy vs 5.7 Gy). RIR only affected the maximum dose, which increased to 17.0 Gy. SDIR correctly translated the dose maps, as none of the parameters changed significantly.

Keywords

Superficial brachytherapy
Deformable image registration
Skin cancer
==== Body
pmc1 Introduction

Metachronous lesions of non-melanoma skin cancer (NMSC) are usually treated separately using interstitial or superficial brachytherapy with the individual treatment plans [1], [2], [3], [4], [5]. When calculating consecutive plans for subsequent tumors, it is essential to consider the doses from previous treatments. Therefore, each dose map must be transferred to a common reference frame, such as the most recent computed tomography (CT) series, to obtain an accurate estimate of the accumulated dose. Image registration (IR) methods facilitate the transfer of doses across various treatment modalities and imaging sets [6], [7], [8], [9]. Although rigid and non-rigid (deformable) IR algorithms can effectively translate doses, there is a lack of published reports specifically addressing their application in superficial brachytherapy [10], [11], [12]. Additionally, comprehensive guidelines for accumulated dose-volume parameters are not well documented. In superficial brachytherapy, the skin is both the target and the organ where the dose must be carefully limited to minimize the risk of complications. Currently, only the maximum skin surface dose (Dmax) has been widely reported as a skin dose constraint, while other relevant parameters are often neglected [13], [14]. Hence, our research primarily emphasizes dose and volume metrics related to the skin, particularly Dmax.

The aim of this study was to evaluate three image registration algorithms for their potential application in skin dose translation. We investigated whether rigid registration provides an accurate match of the external contour of the patient's body, or whether deformation algorithms should be used for more accurate dose translation. Our study was specifically focused on the external contour of the patient's body and three dose-volume histogram (DVH) parameters calculated for this structure.

2 Materials and methods

2.1 Patient characteristic

Seven patients with metachronous NMSC treated from March 2015 to August 2021 with superficial high dose rate brachytherapy (HDR BT) were randomly selected for analysis. Due to the retrospective nature of the study, written informed consent from patients was not required. Each patient developed two to four lesions. Twenty-four lesions were included in the study (Supplementary Table S 1). Each lesion was treated separately with an individual mould applicator with the corresponding dose distribution. In the investigated group, twenty-four separate treatment plans were calculated and used for analysis. Treatment plans were calculated using the OncentraBrachy v.4.5–4.6 planning system (ELEKTA AB, Sweden). All plans were CT-based. Somatom Definition AS (Siemens Medical Solutions Inc., USA) and Discovery RT (GE Healthcare) were used for scanning. Slice thickness was 1.0 mm for Siemens CT and 1.25 mm for GE CT.

TG-43 (AAPM Task Group No. 43 Report) formalism was used for dose calculation. High-dose-rate brachytherapy source Iridium-192 (Ir-192) and microSelectron V3 HDR (Elekta AB, Sweden) was used for treatment. The external patient body was contoured automatically and manually corrected to eliminate the inaccuracy of the automatic volume recognition algorithm in the region of the applicator which was excluded from the external contour. No backscatter bolus was used during CT scanning and treatment. The dose specification point was located 0.2 – 0.5 cm below the skin. Specification depth varied depending on the skin thickness and the visibility of the tumour mass. The Groupe Européen de Curiethérapie (GEC) and the European Society for Radiotherapy & Oncology (ESTRO) recommendations were followed for prescription [15]. Treatment plans were calculated according to the internal, institutional protocol, which assumes delivering a total dose of 45 Gy in 9 fractions to obtain a biologically equivalent dose (BED) of 67.50 Gy (alpha/beta 10 Gy). For planning purposes, we assumed that the maximum skin surface dose (Dmax), delivered to the skin (external contour) should not exceed 200 % of the prescribed dose, and the maximal dose to the bone structures should be lower than 100 % of the reference dose.

2.2 Data analysis and workflow

For each patient, every BT plan, including the image data (CT volume), the structure set data, and the associated dose matrices, were exported from the OncentraBrachy, in the form of DICOM (Digital Imaging and Communications in Medicine) files, to the Velocity AI v.4.1. software (Varian Medical Systems Inc., Palo Alto) for image registration (IR) and dose map translation into the common reference frame. The most recent CT was chosen for each patient as a reference frame. All previous CTs were registered with the reference image using three different registration methods: rigid (RIR), deformable (DIR), and structure-based (SDIR) [16].

In this study, the external contour represents the patient’s skin. It is used for deformation guidance in the SDIR approach. Seventeen registrations completed with RIR, DIR and SDIR algorithms were collected and compared for the analysed patient group. Obtained registration matrices were used to convert the dose distributions to the more recent reference frame (Supplementary Fig. S 1). Selected dose-volume metrics for dose distribution before its translation to a new volume and after image registration, were compared and tested for statistical differences. Analysed metrics included: the maximum skin surface dose (Dmax) for the external contour, the dose delivered to 2 cm3 of the external contour (D2cm3) and the dose delivered to 0.1 cm3 of the external contour (D0.1cm3).

To evaluate and compare the accuracy of different registration methods, we assumed that the deformation of the dose map on the new volume should not change the value of the Dmax. The discrepancies between Dmax in the original dose map and the dose map translated to a new volume would rather be a result of the low accuracy of the registration algorithm. Other DVH parameters (expressed as absolute values) can vary significantly between deformed and original dose maps only in case of large organ shrinkage or enlargement. Given that significant volumetric changes in the patient's body are not observed in the head and neck region, especially in the scalp area, we assumed that D0.1cm3 and D2cm3 should not experience significant deviations from their original values.

Statistical analysis was described in Supplementary materials. The Dice Similarity Coefficient (DSC) was applied to evaluate IR accuracy [17], [18] (see Supplementary materials).

3 Results

Visual inspection of external contours, registered with DIR and SDIR methods, demonstrated that patient boundaries in the region of the applicator matched better when using SDIR (Fig. 1). The median non-registered values were: 9.4 Gy for Dmax, 7.8 Gy for D0.1cm3 and 5.7 Gy for D2cm3. DIR resulted in a significant increase (p = 0.003) in Dmax, which was 39.2 Gy after deformation (median for all patients). After RIR registration, the median Dmax also increased significantly from 9.4 Gy to 17.0 Gy (p = 0.02). The DIR method also significantly increased the values of the other parameters analysed. The median value for registered D0.1cm3 was 16.4 Gy, while for non-registered D0.1cm3 was 7.8 Gy (p = 0.002). The median DIR D2cm3 was 7.6 Gy and non-registered D2cm3 was 5.9 Gy. Differences were also statistically significant (p = 0.002). On the contrary, after RIR, the median for D0.1cm3 was 10.1 Gy and for D2cm3 it was 6.8 Gy. The statistical test did not confirm differences between those values and non-registered ones (p > 0.05 for both values). When the SDIR approach was used, none of the analysed parameters' original values changed significantly after translation to a new CT (p > 0.1). After SDIR, the median for Dmax was 11.7 Gy, for D0.1cm3 was 8.1 Gy and for D2cm3 was 5.8 Gy (Table 1).Fig. 1 Visual comparison using split screen displays of two CTs registered with DIR (deformable image registration) on the right and SDIR (structure-based image registration) on the left.

Table 1 The medians and ranges of dose parameters calculated for each dose map before and after registration with three different registration methods.

	non-reg	DIR	RIR	SDIR	
Dmax [Gy]	9.4 Gy (7.3 – 26.5)	39.2 Gy (12.2 – 40.0)
p = 0.003	17.0 Gy (6.2 – 39.9)
p = 0.02	11.7 Gy (7.2 – 28.8)
p = 0.18	
D0.1cm3[Gy]	7.8 Gy (6.3 – 14.3)	16.4 Gy (7.5 – 31.8)
p = 0.002	10.1 Gy (5.6 – 39.1)
p = 0.06	8.1 Gy (6.2 – 10.1)
p = 0.98	
D2cm3[Gy]	5.7 Gy (4.3 – 8.8)	7.6 Gy (5.3 – 13.3)
p = 0.002	6.8 Gy (4.5 – 20.9)
p = 0.13	5.8 Gy (4.9 – 7.9)
p = 0.69	
non-reg (non-registered) – parameter calculated based on the original dose map before its translation to a new volume; RIR – rigid image registration; DIR – deformable image registration; SDIR – structure-based image registration. p-values of statistical significance of Wilcoxon signed-rank test.

4 Discussion

The present study is the first to verify which image registration algorithms in brachytherapy of multifocal, metachronous skin cancer provide a relevant tool for dose translation to a new volume. We compared the accuracy of rigid, deformable and structure-based registration methods in terms of differences between selected DVH parameters. Our results showed significant differences between Dmax, for dose maps before and after translation when DIR was used. Visual investigation of the registration revealed that DIR incorrectly recognizes the surface of the patient body in the applicator region (Fig. 1). The skin surface after DIR was closer to the radioactive source, resulting in a higher maximum point dose to the external structure compared to the original dose.

The DIR method also overestimated D0.1cm3 and D2cm3 which were significantly higher after translation to a new volume. On the contrary, we did not observe significant changes in D0.1cm3 and D2cm3 parameters after RIR, except for Dmax, which was statistically different from its original value. Therefore, RIR can be an acceptable method of transferring the dose to the most recent CT volume, as long as we do not use the Dmax parameter to evaluate the accumulated dose or dose transferred onto the reference frame.

Based on the results of this study, we recommend using the volumetric parameter D0.1cm3 to estimate skin dose, rather than Dmax, (defined as the dose at a volume of 0.00 cm3 [13]). Our analysis showed that Dmax is susceptible to registration inaccuracies and should not be used for accumulated dose evaluation and comparison in multifocal skin cancer. Hence, D0.1cm3 may be a reasonable alternative to the maximum point dose parameter.

When the SDIR approach was used, none of the analysed parameters changed significantly after translation to a new CT series. SDIR supported by the structure copes better with the deformation problem. SDIR provides reliable results when the primary and secondary images show dramatic changes in the volume of the structures [1]. Researchers consider registration guided by structures to have the potential to improve the results of automatic DIR. Bosma et al proposed a contour-guidance algorithm that significantly increased contour overlap [19]. Importantly, it significantly decreased the registration error and the dose warping error compared to the algorithms without contour guidance.

Swamidas et al. compared the dose accumulation for the bladder and rectum by intensity-based and contour-based deformation algorithms [20]. The study confirmed that the contour-based approach resulted in more consistent deformations, which led to less dose degradation induced by DIR. However, in the same study, authors suggest that simple dose summation based on the DVH parameters provides a reasonably good estimate of the dose in OaRs. They admit that DIR based on image intensities should be avoided because of the risk of systematic underestimation of the dose due to implausible DIR [11], [20]. In our study of dose map translation for the external structure, SDIR also provides more accurate results than DIR and has a slight advantage over the RIR approach. Mohammadi et al. [21] demonstrated low registration uncertainty for dose mapping for a hybrid-based DIR algorithm (that considered both intensity and contours). The observed difference in accumulated dose between hybrid-based DIR and straight summation approaches was statistically significant for both the bladder and the rectum. In contrast to Swamidas et al. [20] the authors underline the potential that the hybrid-based DIR algorithm has for dose accumulation between brachytherapy fractions [21].

In the case of multifocal skin cancer, the dose distribution parameters analysed for the patient's external body contour (in particular Dmax) were most accurately transformed to a new volume using structure-based registration. In principle, due to the correct deformation of the patient's external body contour, the three analysed parameters did not change significantly after SDIR. The limitation of our work is that it only focuses on three parameters in the external contour of the patient's body. Once we have collected suitable research material, we plan to extend the study to other organs such as eyeballs, lenses, bones and salivary glands.

Our work has shown that the SDIR method applied to the external contour of the patient's body allows the dose distribution in this structure to be transferred without statistically significant differences, even in high-dose regions. Therefore, SDIR is suitable for image registration in superficial brachytherapy of metachronous lesions. However, further studies are needed to confirm its clinical application and the accuracy of dose translation in organs other than the patient's skin e.g. eyeballs, lenses, bones and salivary glands. The paper also shows that in the absence of deformation algorithms, the rigid method can be successfully applied within the limited scope presented in the paper.

CRediT authorship contribution statement

Marta Szlag: Conceptualization, Methodology, Investigation, Writing – original draft. Magdalena Stankiewicz: Writing – review & editing. Sylwia Kellas-Ślęczka: Writing – review & editing. Małgorzata Stąpór-Fudzińska: Validation. Agnieszka Cholewka: Formal analysis, Resources. Agnieszka Pruefer: Visualization, Resources. Piotr Wojcieszek: Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.phro.2024.100631.
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References

1 Ouhib Z. Kasper M. Calatayud J.P. Rodriguez S. Bhatnagar A. Pai S. Aspects of dosimetry and clinical practice of skin brachytherapy. The American Brachytherapy Society working group report Brachytherapy 14 2015 840 858 10.1016/j.brachy.2015.06.005 26319367
2 Szlag M. Kellas-Sleczka S. Wojcieszek P. Stankiewicz M. Cholewka A. Pruefer A. Advanced dose calculation algorithm in superficial brachytherapy – the impact of tissue inhomogeneity on treatment plan dosimetry J Contemp Brachytherapy 13 2021 441 446 10.5114/jcb.2021.106541 34484359
3 Brovchuk S. Park S.-J. Shepil Z. Romanenko S. Vaskevych O. High-dose-rate skin brachytherapy with interstitial, surface, or a combination of interstitial and surface mold technique J Contemp Brachytherapy 14 2022 107 114 10.5114/jcb.2022.114661 35494184
4 Scherf Ch. Licher J. Mletzko Ch. Trommel M. Tselis N. Chatzikonstantinou G. Individualized mould-based high-dose-rate brachytherapy for perinasal skin tumors: technique evaluation from a dosimetric point of view J Contemp Brachytherapy 13 2021 179 187 10.5114/jcb.2021.105286 33897792
5 Wojcieszek P. Szlag M. Cholewka A. Kellas-Sleczka S. Fijalkowski M. Bialas B. Individualized surface brachytherapy for the treatment of synchronous/metachronous multifocal basal cell cancer of the face Int J Radiat Oncol Biol Phys 99 Suppl 2 2017 E381 10.1016/j.ijrobp.2017.06.1514
6 Van Heerden L.E. Houweling A.C. Koedooder K. Van Kesteren Z. Van Wieringen N. Rasch C.R.N. Structure-based deformable image registration: added value for dose accumulation of external beam radiotherapy and brachytherapy in cervical cancer Radiother Oncol 123 2017 319 324 10.1016/j.radonc.2017.03.015 28372889
7 Van Heerden L.E. Visser J. Koedooder K. Rasch C.R.N. Pieters B.R. Be A. Role of deformable image registration for delivered dose accumulation of adaptive external beam radiation therapy and brachytherapy in cervical cancer J Contemp Brachytherapy 10 2018 542 550 10.5114/jcb.2018.79840 30662477
8 Xiong Y. Rabe M. Rippke C. Kawula M. Nierer L. Klüter S. Impact of daily plan adaptation on accumulated doses in ultra-hypofractionated magnetic resonance-guided radiation therapy of prostate cancer Phys Imaging Radiat Oncol 29 2024 100562 10.1016/j.phro.2024.100562
9 Ryckman J.M. Shelton J.W. Waller A.F. Schreibmann E. Latifi K. Diaz R. Anatomic structure-based deformable image registration of brachytherapy implants in the treatment of locally advanced cervix cancer Brachytherapy 15 5 2016 584 592 10.1016/j.brachy.2016.04.390 27263057
10 Yedekci Y. Gültekin M. Sarı S.Y. Yildiz F. Automatic contouring using deformable image registration for tandem-ring or tandem-ovoid brachytherapy J Contemp Brachytherapy 14 2022 1 8 10.5114/jcb.2022.112814 35233228
11 Swamidas J. Kirisits Ch. De Brabandere M. Hellebust T.P. Siebert F.-A. Tanderupet K. Image registration, contour propagation and dose accumulation of external beam and brachytherapy in gynecological radiotherapy Radiother Oncol 143 2020 1 11 10.1016/j.radonc.2019.08.023 31564555
12 Andersen E.S. Noe Ø.K. Sørensen T.S. Nielsen S.K. Fokdal L. Paludan M. Simple DVH parameter addition as compared to deformable registration for bladder dose accumulation in cervix cancer brachytherapy Radiother Oncol 107 2013 52 57 10.1016/j.radonc.2013.01.013 23490266
13 Gonzalez-Perez V. Rembielak A. Guinot JL H&N and Skin (HNS) GEC-ESTRO Working Group critical review of recommendations regarding prescription depth, bolus thickness and maximum dose in skin superficial brachytherapy with flaps and customized moulds Radiother Oncol 175 2022 122 132 10.1016/j.radonc.2022.08.022 36030932
14 Likhacheva A.O. Devlin P.M. Shirvani S.M. Barker C.A. Beron P. Bhatnagar A. Skin surface brachytherapy: a survey of contemporary practice patterns Brachytherapy 16 2017 223 229 10.1016/j.brachy.2016.10.006 27908679
15 Guinot J.L. Rembielak A. Perez-Calatayud J. Rodríguez-Villalba S. Skowronek J. Tagliaferri L. GEC-ESTRO ACROP ecommendations in skin brachytherapy Radiother Oncol 26 2018 377 385 10.1016/j.radonc.2018.01.013
16 Rigaud B. Simon A. Castelli J. Lafond C. Acosta O. Haigron P. Deformable image registration for radiation therapy: principle, methods, applications and evaluation Acta Oncol 58 2019 1225 1237 10.1080/0284186X.2019.1620331 31155990
17 Varadhan R. Karangelis G. Krishnan K. Hui S. A framework for deformable image registration validation in radiotherapy clinical applications J Appl Clin Med Phys 14 2013 192 213 10.1120/jacmp.v14i1.4066
18 Zou K.H. Warfield S.K. Bharatha A. Tempany C.M.C. Kaus M.R. Haker S.J. Statistical validation of image segmentation quality based on a spatial overlap index Acad Radiol 11 2004 178 189 10.1016/S1076-6332(03)00671-8 14974593
19 Bosma L.S. Ries M. de Senneville B.D. Raaymakers B.W. Zachiu C. Integration of operator-validated contours in deformable image registration for dose accumulation in radiotherapy Phys Imaging Radiat Oncol 27 2023 100483 10.1016/j.phro.2023.100483
20 Swamidas J. Mahantshetty U. Andersen E. Noe K.O. Sorensen T.S. Kallehauge J.F. Uncertainties of deformable image registration for dose accumulation of high-dose regions in bladder and rectum in locally advanced cervical cancer Brachytherapy 14 2015 953 962 10.1016/j.brachy.2015.08.011 26489919
21 Mohammadi R. Mahdavi S.R. Jaberi R. Siavashpour Z. Janani L. Meigooni A.S. Evaluation of deformable image registration algorithm for determination of accumulated dose for brachytherapy of cervical cancer patients J Contemp Brachytherapy 11 2019 469 478 10.5114/jcb.2019.88762 31749857
