|Year : 2018 | Volume
| Issue : 3 | Page : 238-241
Calculation of dose volume parameters and indices in plan evaluation of HDR interstitial brachytherapy by MUPIT in carcinoma cervix
Jyoti Poddar, Ashutosh Das Sharma, U Suryanarayan, Sonal Patel Shah, Ankita Parikh, Vimesh Mehta, Tarun Kumar
Department of Radiotherapy, Gujarat Cancer and Research Institute, Ahmedabad, Gujarat, India
|Date of Web Publication||28-Jan-2019|
Dr. Jyoti Poddar
Department of Radiotherapy, Gujarat Cancer and Research Institute, Ahmedabad, Gujarat
Source of Support: None, Conflict of Interest: None
BACKGROUND: Evaluation of a HDR- interstitial brachytherapy plan is a challenging job. Owing to the complexities and diversity of the normalization and optimization techniques involved, a simple objective assessment of these plans is required. This can improve the radiation dose coverage of the tumour with decreased organ toxicity. AIM: To study and document the various dose volume indices and parameters required to evaluate a HDR interstitial brachytherapy plan by Volume normalization and graphical optimization using MUPIT (Martinez Universal Perineal Interstitial Template) in patients of carcinoma cervix. SETTINGS AND DESIGN: Single arm, retrospective study. METHODS AND MATERIALS: 35 patients of carcinoma cervix who received EBRT and HDR brachytherapy using MUPIT, were selected. The dose prescribed was 4 Gray/Fraction in four fractions (16Gy/4) treated twice daily, at least 6 hours apart. CTV and OARs were delineated on the axial CT image set. Volume normalization and graphical optimization was done for planning. Coverage Index (CI), Dose homogeneity index (DHI), Overdose index (OI), Dose non-uniformity ratio (DNR), Conformity Index (COIN) and dose volume parameters i.e. D2cc, D1cc, D0.1cc of rectum and bladder were evaluated. STATISTICAL ANALYSIS: SPSS version 16 was used. RESULTS AND CONCLUSION: CI was 0.95 ± 1.84 which means 95% of the target received 100% of the prescribed dose. The mean COIN was 0.841 ± 0.06 and DHI was 0.502 ± 0.11. D2cc rectum and bladder was 3.40 ± 0.56 and 2.95 ± 0.62 respectively which was within the tolerance limit of this organs. There should be an optimum balance between these indices for improving the quality of the implant and to yield maximum clinical benefit out of it, keeping the dose to the OARs in limit. Dose optimization should be carefully monitered and an institutional protocol should be devised for the acceptability criteria of these plans.
Keywords: Cervical carcinoma, dose volume indices, graphical optimization, interstitial brachytherapy, Martinez Universal Perineal Interstitial Template, volume normalization
|How to cite this article:|
Poddar J, Sharma AD, Suryanarayan U, Shah SP, Parikh A, Mehta V, Kumar T. Calculation of dose volume parameters and indices in plan evaluation of HDR interstitial brachytherapy by MUPIT in carcinoma cervix. Indian J Cancer 2018;55:238-41
|How to cite this URL:|
Poddar J, Sharma AD, Suryanarayan U, Shah SP, Parikh A, Mehta V, Kumar T. Calculation of dose volume parameters and indices in plan evaluation of HDR interstitial brachytherapy by MUPIT in carcinoma cervix. Indian J Cancer [serial online] 2018 [cited 2021 Jun 13];55:238-41. Available from: https://www.indianjcancer.com/text.asp?2018/55/3/238/250900
| » Introduction|| |
Since the inception of radiotherapy, the major goal of radiation oncologists has been to deliver homogeneous radiation dose to tumor volume and to spare the surrounding normal tissues as much as possible. Rapid progress in the field of imaging and planning systems has made it possible to visualize the target and isodose lines in spatial volume. Multiple plans can be generated for the same patient. The dose distribution in these plans can be visualized in the form of dose–volume histograms (DVHs) and isodose lines. The large volume of data contained in these histograms, lines, and curves may complicate the problem rather than simplifying it. This calls for a tool that can summate all data and help the user to quantitatively assess the quality of the treatment, in a simpler way. Using such tools, both in brachytherapy and external beam radiotherapy (EBRT), a choice can be made in favor of a plan over the others, which provides maximum and homogeneous target coverage and simultaneously saves the organs at risk (OARs). The normalization and optimization techniques are the tools which can serve this purpose.
Brachytherapy is an integral part of treatment of carcinoma cervix. It needs utmost precision during the placement of the applicator, planning, and plan evaluation. For cervical cancer patients, interstitial brachytherapy (ISBT) is best suited for those where the disease volume is high which cannot be encompassed by the standard intracavitary brachytherapy (ICBT) application, or the patients' anatomy is such that ICBT poses technical difficulties. In such patients, ISBT can improve the target coverage and reduce OAR doses by various normalization and optimization techniques. The multiple ways of optimization have made the dosimetric comparison and plan evaluation very heterogeneous. As very limited data of small subsets of patients are available, the complete advantage of ISBT in cervical cancer has not been drawn till now. Multiple studies have been done on ISBT dosimetry and optimization methods, but none of these studies have evaluated dosimetric and radiobiological indices in a comprehensive manner. There are various methods of optimization such as volume optimization (VO), geometric optimization (GO), graphical optimization (GrO), dose point optimization (DP), and inverse planning simulated annealing (IPSA).
All these dose optimization methods aim at having a uniform dose distribution and minimizing the high-dose regions inside the target volume (TV). GEC ESTRO (Groupe Europeen de Curietherapie-European Society for Radiotherapy and Oncology) has laid down certain parameters and indices to assess the quality of ISBT plan, for example, Dose Homogeneity Index (DHI), Coverage Index (CI), Overdose Volume Index (OI), dose non-uniformity ratio (DNR), and Conformity Index (COIN) which assist in objective assessment of the plan and identification of the hot spots, cold spots, target coverage, and dose to the OARs irrespective of the method of optimization.
This study was conducted with an aim to document the above said parameters and indices in ISBT plans in carcinoma cervix using volume normalization and GrO as the planning tool. It helped in improving the quality of the implants and also to devise an institutional protocol for acceptability of the plans, such that the use of optimization can be made uniform among all the users of an institution.
| » Materials and Methods|| |
In all, 35 patients of carcinoma cervix, who underwent external radiotherapy and HDR ISBT by MUPIT (Martinez Universal Perineal Interstitial Template), were selected for this dosimetric study. All patients had received radical radiotherapy with concomitant cisplatin chemotherapy up to a dose of 50 Gy in 25 fractions. It was followed by ISBT of a dose of 16 Gy in four fractions, treated twice daily, at least 6 h apart. Summation of dose was done in accordance with linear quadratic model.
Before the brachytherapy procedure, a pelvic examination was done under anesthesia to assess normal pelvic anatomy, residual disease, and its relationship with normal structures. The urinary bladder was catheterized with Urograffin dye pushed into its bulb. After assessing the vaginal length, the vaginal cylinder screwed to the template was inserted. The guide needle was inserted. With the template held to the perineum and cylinder screwed into place, 20-cm stainless steel needles with closed trocar tip were inserted depending on the area to be treated. Each needle was placed through the template under digital rectal examination guidance. The needles were then secured to the template with the screws. These were then reinforced with the template cover and template secured to the perineum by four corner stitches. A rectal tube was inserted into the ano-rectum as per our institutional protocol. Axial computed tomography (CT) scans of 2.5-mm slice thickness were taken for planning and were transferred to the brachytherapy treatment planning system. The dose computation algorithm used is based on TG-43 (Task group-43) as recommended by American Association of Physicists.
The clinical target volume (CTV) and the OAR, that is, rectum, bladder, and sigmoid colon were delineated as per the GEC-ESTRO contouring guidelines. Multiplanar reconstruction was used to reconstruct the implant geometry, which allows the view of the reconstructed implant in all the three planes, for example, axial, sagittal, and coronal. A negative offset from the tip of the needles was given which was calculated as (thickness of CT scan/2 – 0.6). Dwell position in each catheter was loaded for adequate CTV coverage (95% of CTV volume to receive 95% of prescribed dose – as per our institution protocol). The dose was normalized on dose points.
Kneschaurek et al. described a volume-based optimization technique for brachytherapy dose distribution. For volume-based optimization method, the dose points are generated 5 mm on the CTV surface and dose is prescribed to these points. The dose at these reference points can be calculated if the position of the sources is known (i.e., alternate dwell positions 1, 3, 5, etc.). VO allows three-dimensional dose optimization where the dose is prescribed to the whole target. Minimum dose is prescribed on the CTV and maximum dose received by the critical structures is noted. [Figure 1] and [Figure 2] show the interstitial plan and the DVH of a representative patient. All the interstitial needles inserted were loaded with 2.5-mm step size. Depending on the dose distribution inside, TV, step size, and dual time were altered. After a tentative plan was ready, the physicist had done GrO to reduce the non-homogeneity and to improve target coverage.
|Figure 1: The interstitial implant and target delineation on a axial CT image|
Click here to view
The DVH parameters were collected, including, V100, V150, V200 (volume receiving 100%, 150%, and 200% of the prescribed dose), maximum dose to 2 cc of bladder, rectum, and sigmoid colon (D2cc) for each plan. Maximum doses to 1 cc and 0.1 cc (D1cc and D0.1cc, respectively) were noted. The following indices were calculated: CI, DHI, OI, DNR, and COIN.
The above-mentioned indices are as follows:
- Coverage Index (CI):
CI is the fraction of the TV that receives the prescribed dose. This index gives an estimate of how much of the target received 100% of the dose.
(Ideal value of CI = 1).
- Dose homogeneity index (DHI):
DHI is the ratio of the TV receiving a dose approximately 1.0–1.5 times of the reference dose to the volume of the target that receives a dose equal to or greater than the reference dose.
(Ideal value of DHI = 1)
- Overdose volume index (OI):
This is the ratio of the TV which receives a dose ≥2.0 times of the reference dose to the volume of the target that receives a dose equal to the reference dose.
(Ideal OI = 0).
- Dose non-uniformity ratio (DNR):
This is the ratio of the TV which receives a dose equal to or greater than 1.5 times of the reference dose to the volume of the target which receives a dose equal to the reference dose
(Ideal DNR = 0).
- Conformity Index (COIN):
COIN describes how well the reference dose encompasses the TV and excludes non-target structures. The fraction of the TV, which is covered by the reference dose, is described by c1 and the fraction of the total volume covered by the reference dose that belongs to the TV by c2.
COIN = c1 × c2.
(Ideal COIN = 1).
Volume normalization followed by GrO is routinely used at our institute. All the indices and parameters stated above were calculated for each treatment plan which has helped in improving the quality of the implants and to standardize the acceptability criteria of the ISBT plans in carcinoma cervix.
| » Results|| |
Optimized plan generated for each patient by volume normalization and GrO was evaluated and all the above mentioned parameters were calculated. The data pertaining to dosimetric indices and DVH parameters are tabulated in [Table 1].
|Table 1: Dosimetric indices and DVH parameters based on volume optimization|
Click here to view
From the table, it is evident that the mean CI was found to be 0.95 ± 1.84 which means that 95% of the target received 100% of the prescribed dose. The coefficient of variation (CV) was 0.019 which shows the dispersion around the mean was less. The mean COIN was 0.841 ± 0.06 which denotes that the plan encompasses 84% of the TV and excludes the non-target structures. It should be as high as possible keeping OVI and DHI into account. The mean DHI was 0.502 ± 0.11. It means that 50% of the TV received homogeneous dose. The ideal values of DHI should be 1 and DNR be 0 which is not practically possible as the dose levels around the needles are very high. However, we found that the plan needs to be improved more on this dimension and decrease the areas receiving non-homogeneous dose, within the target. The mean OVI is 0.173 ± 0.07 which is well within limits. All these parameters are represented graphically in [Graph 1] for easy interpretation.
We found that though CI and OVI were according to the prescribed norms, DHI was 0.5. It means better dose homogeneity within TV needs to be achieved and to decrease non-homogeneous areas. There should be an optimum balance between CI, DHI and COIN for improving the quality of the implants in cervical cancers.
| » Discussion|| |
HDR ISBT treatment planning involves optimization methods to calculate the dwell time and dwell positions of the radioactive source along the specified applicator paths. The aim is to produce an acceptable plan within a reasonable time period respecting the dose constraints of OAR and ensuring adequate target coverage.
However, all the available optimization techniques fail to use the anatomic information. They are based entirely on the active dwell positions and dwell times. Hence, these methods approximate the anatomical shapes and do not suffice to the requirements of an ideal plan, that is, to maintain homogeneous dose coverage to the target and to spare the critical structures as much as possible. The various combinations of the normalization and optimization techniques are required to achieve the criteria of an ideal plan. Therefore, irrespective of the method of normalization and optimization used, the target value of all the above said indices and parameters must be achieved for achieving the desired outcomes. Few studies have been reported in literature, where different methods of normalization and optimization were used but the aim was to achieve the desired values of these indices.
Shwetha et al. studied four optimization methods for 10 patients of cervical cancer treated with interstitial implants. Four treatment plans were generated for each patient by GO, VO, GO followed by isodose reshapes (GO_IsoR) and VO followed by isodose reshapes (VO_IsoR) and were compared. GrO was mentioned as IsoR by the authors of this study. They concluded that COIN (mean 0.75) and HI (mean 0.58) were highest for VO_IsoR as compared to other optimization techniques. DNR was higher for GO and GO_IsoR as compared to VO and VO_IsoR. For OAR doses, they had calculated D5cc rectum and D5cc bladder doses which were the least in VO_ISoR. From the results, it was evident that VO_IsoR was a better mode of optimization as compared to others, though the number of patients in the study was small. We had followed the same method, that is, volume normalization followed by GrO.
Regarding GrO, it can be used in the end of the plan to address minor target coverage issues or to limit the dose to OARs. However, it should be used judiciously as it is highly user-dependent and can lead to generation of significant cold and hot spots with TV. This point was highlighted in a study done by Anbumani et al. where they did an analysis of 40 cervical cancer patients who had received ISBT. They did GO, DP, and GrO of all the patients and compared all the plans. They found that geometrical optimization produced more inhomogeneous dose distribution (mean DHI = 0.4494). D2cc bladder and rectum were least for graphically optimized plans. Hence, the authors concluded that GrO can be used to spare OARs. However, it can generate dose optimization which can fit to the geometrical i rregularities of the target but the plan may not suffice to all the above-mentioned indices. So GrO should be used with caution.
Sharma et al. did a study similar to our study, with interstitial implant using MUPIT in cervical cancer patients. They used geometrical and GrO and found the mean CI, DHI, and DNR were 0.86 ± 0.03, 0.69 ± 0.11, and 0.31 ± 0.09, respectively, while the mean OI and COIN were 0.08 ± 0.03 and 0.79 ± 0.05, respectively. The D2cc bladder and rectum doses were reported to be 76 ± 11 and 80 ± 17 Gy, respectively.
When we compared our results with that of this study, we found that if CI and COIN increased, DHI decreased. As we had focused more on increasing the CI, the DHI went down. The mean CI in our study was 0.95 ± 1.84. Review of literature suggests a CI of 0.95 to be acceptable for cervical and oropharyngeal implants. Major et al. had also suggested a CI of 0.95 for interstitial cervical implants. If attempts are made to further increase the CI, it increases at the cost of DHI, thereby increasing DNR and OI. Hence, an ideal plan should strike an optimum balance between all these parameters.
| » Conclusion|| |
As dose optimization contributes to local control and disease-free survival of the patient, it should be carefully monitored and a particular institutional protocol should be devised for the acceptability criteria of the plans such that the use of optimization can be made uniform among all the users in the institution. Clinical correlation of DVH parameters may help in improving the quality of implant by identifying the hot and cold spots in the target which would help in predicting clinical outcomes and treatment-related toxicity.
The CI should not be increased at the cost of DHI which would, in turn, increase the OVI. From the above study and the review of literature, it is clear that all the indices should be in a balance with respect to one another. This study suggests that the indices do represent the quality of the implant in terms of optimal target coverage, sparing of OAR with acceptable hotspots within the TV. This study was done as a part of good clinical practice to objectively analyze the treatment plan for improving it further.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| » References|| |
Kneschaurek P, Schiessl W, Wehrmann R. Volume based dose optimization in brachytherapy. Int J Radiat Oncol Biol Phys 1999;45:811-5.
Wu A, Ulin K, Sternick AS. A dose homogeneity index for evaluating 192
Ir interstitial breast implants. Med Phys 1988;15:104-7.
Anbumani S, Anchinevan P, Narayanaswamy AN. Treatment planning methods in high dose rate interstitial brachytherapy of carcinoma cervix: A dosimetric and radiobiological analysis. ISRN Oncol; 2014: Article ID125020.
Bahaduri Y, Constantinescu C, Ezzat M. 3D anatomy based planning optimization for HDR brachytherapy of cervix cancer. Saudi J Obstet Gynaecol 2009;11:1430.
Shwetha B, Ravikumar M, Katke A. Dosimetric comparison of various optimization techniques for high dose rate brachytherapy of interstitial cervix implants. J Appl Clin Med Phy 2010;11:225-30.
Sharma P, Sharma P, Swamidas J, Mahantshetty U. Dose optimization in gynecological 3D image based interstitial brachytherapy using martinez universal perineal interstitial template (MUPIT) – An institutional experience. J Med Phys 2014;39:197-202.
] [Full text]
Ahmad F, Alettia P, Charra-Brunaud C, Van Der Laarse R, Lapeyre M, Hoffstetter S, et al
. Influence of dose point and inverse optimization on interstitial cervical and oropharyngeal carcinoma brachytherapy. Radiother Oncol 2004;73:331-7.
Major T, Poglar C, Fodor J, Somogyi A, Németh G. Conformality and homogeneity of dose distribution in interstitial implants at idealized target volumes: A comparison between the Paris and dose-point optimized systems. Radiother Oncol. 2002;62:103-11.
[Figure 1], [Figure 2]