Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 

 
ORIGINAL ARTICLE
Ahead of print publication  

Radiobiological modelling of radiation-induced acute skin toxicity (dermatitis): A single institutional study of breast carcinoma


1 Centre for Medical Physics, Panjab University, Chandigarh; Department of Radiation Oncology, Max Superspeciality Hospital, Bathinda, Punjab, India
2 Centre for Medical Physics, Panjab University; Department of Radiotherapy, PGIMER, Chandigarh, Punjab, India
3 Department of Radiotherapy, PGIMER, Chandigarh, Punjab, India
4 Department of Radiation Oncology, Max Superspeciality Hospital, Bathinda, Punjab, India
5 Centre for Medical Physics, Panjab University, Chandigarh, Punjab, India
6 Department of Radiation Oncology, Sharda Hospital, Greator Noida, Uttar Pradesh, India
7 Department of Radiation Oncology, AIIMS, Bathinda, Punjab, India

Date of Submission14-Oct-2021
Date of Acceptance13-Dec-2021
Date of Web Publication11-Nov-2022

Correspondence Address:
Rajesh Vashistha,
Department of Radiation Oncology, Max Superspeciality Hospital, Bathinda - 151 001, Punjab
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.jcrt_1844_21

 > Abstract 


Purpose: The purpose of the study was to estimate the fitting parameters of the sigmoidal dose response (SDR) curve of radiation-induced acute dermatitis in breast cancer patients treated with intensity-modulated radiation therapy for calculation of normal tissue complication probability (NTCP).
Materials and Methods: Twenty-five breast cancer patients were enrolled to model the SDR curve for acute dermatitis. The acute radiation-induced (ARI) dermatitis toxicity was assessed weekly for all the patients, and their scores were determined using the common terminology criterion adverse events version 5.0. The radiobiological parameters n, m, TD50, and γ50 were derived using the fitted SDR curve obtained from breast cancer Patient's clinical data.
Results: ARI dermatitis toxicity in carcinoma of breast patients was calculated for the end point of acute dermatitis. The n, m, TD50, and γ50 parameters from the SDR curve of Grade-1 dermatitis are found to be 0.03, 0.04, 28.65 ± 1.43 (confidence interval [CI] 95%) and 1.02 and for Grade-2 dermatitis are found to be 0.026, 0.028, 38.65 ± 1.93 (CI. 95%) and 1.01 respectively.
Conclusion: This research presents the fitting parameters for NTCP calculation of Grade-1 and Grade-2 acute radiation-induced skin toxicity in breast cancer for the dermatitis end point. The presented nomograms of volume versus complication probability and dose versus complication probability assist radiation oncologists in establishing the limiting dose to reduce acute toxicities for different grades of acute dermatitis in breast cancer patients.

Keywords: Common terminology criterion adverse events and acute radiation toxicity, dermatitis, normal tissue complication probability



How to cite this URL:
Singh B, Singh G, Oinam AS, Singh M, Katake A, Kumar V, Vashistha R, Singh PK, Mahajan R. Radiobiological modelling of radiation-induced acute skin toxicity (dermatitis): A single institutional study of breast carcinoma. J Can Res Ther [Epub ahead of print] [cited 2022 Dec 9]. Available from: https://www.cancerjournal.net/preprintarticle.asp?id=361017




 > Introduction Top


Breast cancer is the second most common cancer-related cause of death in women.[1] Following breast-conserving surgery, women with early-stage breast cancer usually get adjuvant whole-breast irradiation (WBI). Despite the fact that WBI improves local control and overall survival, up to 48% of patients with traditional fractionated WBI, develop Grade-2 skin toxicity.[2],[3] Dermatitis, which can range from redness (erythema) to peeling of the skin (desquamation, dry or wet), ulceration, and necrosis, is one of the most prevalent acute side effects of breast cancer radiation.[4],[5],[6],[7],[8] Acute dermatitis has been attributed to radiation-induced injury to the epidermis of the skin. This range of dermatitis is referred to as “skin toxicity,” and it affects 74%–100% of patients after the standard 5–7-weeks course of breast cancer radiation.[9],[10] Skin damage caused by radiation is a common side effect of radiation therapy, and it commonly results in pain and weight loss. As a result, the quality of life (QOL) is affected, which can lead to treatment disruptions and poor treatment outcomes.[11] Acute radiation-induced dermatitis usually manifests itself during or shortly after the radiation therapy. Radiation therapy for breast, pelvic (e.g., anal cancer and vulvar cancer), and head-and-neck cancers causes the most acute radiation-caused dermatitis, while deeper tumors such as lung cancers have a lower incidence.[12] Clinical symptoms associated with this are commonly classified by common terminology criterion adverse events (CTCAE) version 5 for scoring of radiation morbidity.[13] The knowledge of radiobiological parameters for acute radiation-induced (ARI) dermatitis toxicity in radiation therapy treatment planning plays an important role for the estimation of normal tissue complication probability (NTCP).[14] The incidence of acute toxicity is common between external beam radiation therapy (EBRT) and chemotherapy. The effects of both treatment modalities are synergistic.[15] According to several studies and radiation oncologist's clinical experience, normal or healthy tissues present adjacent to the tumor get high doses as the target volume, resulting in normal tissue damage.[16],[17],[18] To compute the NTCP and Tumor Control Probability, most radiobiological models use dosimetric and volumetric data in the form of Dose Volume Histograms (DVHs) of the irradiated organs and tumor volumes in the treatment plans.[19],[20],[21] Rubin et al. initially published normal tissues and organs tolerance doses in the form of TD5/5 (5% complication in 5 years) and TD50/5 (50% complication in 5 years) for calculation of NTCP.[22] In the study of Emami et al., normal tissue tolerance doses were calculated for only a few selected normal organs using as a function of whole and partial organ volumes in the same form of TD5/5 and TD50/5. In these studies, doses were calculated for uniformly irradiated 1/3rd, 2/3rd, and the whole volume of organs using standard fractionation scheme, i.e., 1.8 Gy to 2.0 Gy per fraction.[23] Many radiobiological models have accumulated dose tolerance data for a wide range of normal tissues/organs, but clinical data for all tissues/organs remains unavailable. Furthermore, the radiobiological end points in these model were derived from clinical data on late tissue toxicity.[23],[24],[25] This study will focus on ARI dermatitis because there is a paucity of data on Grade-1 and Grade-2 skin toxicity for nonuniform irradiation. Acute tissue toxicity in terms of radiobiological endpoints for Grade-1 and Grade-2 toxicity of skin was examined for breast cancer patients treated with the intensity modulated radiation therapy (IMRT) technique. A number of parameters are required for mathematical modeling of the dose–response relationship curve in order to identify the dose constraints of the organ of interest for safe and well-tolerated doses.[23] The goal of this work is to compute the fitting parameters corresponding to the various radiobiological end points of ARI skin toxicity in breast cancer patients undergoing EBRT under inhomogeneous radiation conditions.


 > Materials and Methods Top


Patient selection

Twenty-five patients of breast cancer were selected for this study, and their characteristics are shown in [Table 1]. The selected patients have only breast primary toxicity site.
Table 1: Patient (n=25) characteristics

Click here to view


Patient simulation and delineation

All breast cancer patients were positioned supine on a breast board, during simulation with their left/right arm up and followed the same protocol before each fraction of treatment. A planning computed tomography (CT) scan of each patient was taken in a supine position using 16 slice CT scanner (Light Speed 16 Gold Seal, Wipro GE Healthcare Technologies, WI, USA) with slice thickness of 3.75 mm. Patients were immobilized with four clamps thermoplastic cast. All the patients were scanned from the lower border of mandible to 4 cm below the inframammary fold to include the primary site. The delineation of Organs at risk (OARs), gross tumor volume, nodes (if any), and clinical target volumes was performed on FOCAL SIM version 5.11 (Elekta Computerized Medical System [CMS], Maryland Heights, MO, USA) using ESTRO guidelines of breast cancer.[26] [Figure 1] shows the delineation of OARs along with target in different cross-section of the images. All CT images, along with the delineated structure sets, were exported to the CMS XiO version 5.10 (Elekta, Stockholm AB, Sweden) treatment planning system (TPS).
Figure 1: Delineated Organs at risk: Skin (maroon color), planning target volume (skyblue color) and Patient body (light brown color) over the axial (top left), coronal (bottom left), sagittal (bottom right), and 3D view (top right)

Click here to view


Treatment planning

CMS XiO version 5.10, TPS (Elekta, Stockholm AB, Sweden) was used to create the IMRT radiation therapy treatment plans of each breast cancer patients. The dose prescription regimens were chosen 50.4 Gy corresponding to the planning target volume (PTV) in 28 fractions followed by electron boost of 10 Gy in 5 fraction.[27] [Table 2] shows the dose-volume constraints of breast cancer patient for the PTV and OARs. The mean coverage to PTV by 95% of the prescribed dose was chosen as a plan evaluation parameter according to the international commission on radiation units and measurements 83.[28] All IMRT plans were made with seven fields of 6 MV X-rays beam with step and shoot delivery technique using superposition algorithm, having segmentation method of smart sequencing and minimum segment area of 2 cm2 for Elekta (Synergy Platform) linear accelerator equipped with 40 pairs of Multileaf collimators, and grid size of 2 mm was chosen for the dose calculation. To verify the IMRT treatment plan's dose delivery, a pretreatment patient-specific quality assurance (passing/failure criteria) procedure was performed for each patient with Omni Pro IMRT verification software version 1.77.0021 (Scanditronix Wellhofer, Freiburg, Germany) using 2D array of ion chamber I'mRT MatriXX (Scanditronix Wellhofer, Freiburg, Germany) consists of 1020 ion chambers. The gamma evaluation criterion was chosen as 3 mm for distance to agreement and 3% for dose difference.
Table 2: Dose volume constraints for breast cancer patients

Click here to view


Assessment of acute radiation-induced toxicitiy: Dermatitis

The radiobiological end point, dermatitis, was used to measure radiation-induced acute skin toxicity. A team of well-trained physicians and radiation oncologists evaluated the skin's immediate reactions. Each patient's acute radiation toxicities were graded using the CTCAE version 5.0.[13] [Table 3] shows how the grades are divided into five categories for toxicity evaluation. For a total of 6–8 weeks, this toxicity was documented once per week during radiation and 2 weeks after the end of the radiation therapy treatment.
Table 3: Common terminology criteria for adverse effects for scoring toxicity

Click here to view


Mathematical modeling

During the course of radiation therapy treatment, the clinical result of patients with various degrees of toxicity was associated with the given dose. The sigmoidal dose response (SDR) curve fitting was performed using the data of (i) mean and partial volume doses of OARs obtained from the DVHs, (ii) the number of fractions delivered, and (iii) the time of onset of acute radiation toxicities were used as input parameters for the SDR curve fitting. The NTCP of radiation-caused dermatitis was estimated using the radiobiological parameters n, m, TD50, and γ50 determined from the SDR.


 > Results Top


The acute toxicities of all 25 patients who underwent radiation treatment were clinically examined (during the treatment and also on a weekly basis). CTCAE version 5 criteria were used to record their responses. [Table 4] shows the number of individuals who presented with various degrees of acute toxicity.
Table 4: Acute radiation induced dermatitis toxicity patients with grading

Click here to view


Radiobiological modeling and its parameters

The changes of complication probability with change in dose and volume are plotted in the form of surface plot. [Figure 2] and [Figure 3] show the dose-response curve of Grade-1 and Grade-2 skin toxicity. In each of these Figures, (i) [Figure 2]a and [Figure 3]a represent the change of NTCP corresponding to the change of volume of irradiation of the OARs against dose received. (ii) [Figure 2]b and [Figure 3]b represent the nomogram of NTCP and volume of the partially irradiated OARs for three different tolerance doses corresponding to the 5%, 20%, and 50% complication; (iii) [Figure 2]c and [Figure 3]c show the complication probability as a function of dose for 1/3rd, 2/3rd, and whole volume of the OARs and showing threshold dose behavior for the NTCP; (iv) [Figure 2]d and [[Figure 2]d represents the surface plot of tolerance dose on one axis, partial volume on second axis against the complication probability on the third axis. The values of n, m, TD50, and γ50 parameters for Grade-1 and Grade-2 dermatitis are calculated from the fitted SDR curve is shown in [Table 5].
Figure 2: (a) Nomogram of partial volume as a function of dose for 5%, 20% and 50% complication (b)Nomogram of complication probability as a function of partial volume for partially irradiated OAR for three different tolerance doses (c)Nomogram of complication probability as a function of dose for 1/3rd, 2/3rd and whole volume of the OAR (d)Surface plot of tolerance dose on one axis, partial volume on second axis against the complication probability on the third axis

Click here to view
Figure 3: (a) Nomogram of partial volume as a function of dose for 5%, 20% and 50% complication (b)Nomogram of complication probability as a function of partial volume for partially irradiated OAR for three different tolerance doses (c)Nomogram of complication probability as a function of dose for 1/3rd, 2/3rd and whole volume of the OAR (d)Surface plot of tolerance dose on one axis, partial volume on second axis against the complication probability on the third axis

Click here to view
Table 5: Radiobiological parameters obtained from the sigmoidal dose response curve fitting

Click here to view



 > Discussion Top


It is a well-known fact that radiation therapy causes an impact on QOL.[29] The association between the doses received by the skin and incidence of patient-reported acute skin toxicity in the breast cancer patient population is still not known for Grade-1 and Grade-2 toxicity. This research has filled a significant knowledge gap. Despite the use of high radiation doses in breast cancer patients, the incidence of Grade-3 and Grade-4 acute radiation-caused dermatitis was found to be minimal. This is due to the use of IMRT, which is a conformal radiation technique.

In the study of Emami et al., dose-volume parameters based on normal tissue tolerance doses were given only for a few number of organs for different radiobiological end points and all these radiobiological endpoints were calculated based on the 2D radiation delivery technique for late tissue toxicity.[23] However, these dose-volume parameters and their associated normal tissue toxicity data are revised with the availability of recent clinical data and advanced radiation therapy techniques such as conformal radiotherapy, but there is nonavailability of radiobiological parameters for many normal tissues which can estimate NTCP.[30] The skin, normal tissue is one of them, and their acute toxicity have been studied in the present study for the end point of dermatitis. The tolerances doses of skin toxicity were calculated for the reference area of 10 cm2, 30 cm2, and 100 cm2 of these organs and were similar to the methodology used in Burman et al. as tolerance dose was calculated for skin.[31]

Burman et al. initially made an attempt for determining the complication probability of acute skin toxicity (necrosis and ulceration).[31] This model can predict the skin toxicity for the end point of necrosis/ulceration for Grade-3 or above. All the radiobiological parameters determined in this study were only for late radiation-induced effects. However, no radiobiological parameter and SDR curve were calculated for acute effects of radiation which can predict Grade-1, Grade-2 and above radiation-induced dermatitis.

Marks et al. in his study had provided quantitaive analysis of normal tissue effects in clinic data of dose-volume for various organs including skin for 3D-CRT irradiation technique corresponding to late toxicity but not given any radiobiological parameters for ARI toxicity in the skin for the end point of dermatitis.[32] Palma et al. determined NTCP model parameters utilizing the LKB model for radiation-induced dermatitis prediction using IMRT and proton therapy techniques in their study as per CTCAE version 5 protocol. Dermatitis toxicity of Grade-3 or higher was recorded, and no significant variations in dermatitis occurrence were seen for either of the utilized modalities. There are no radiobiological parameters determined in his study which can predict the Grade-1 and Grade-2 skin toxicity for the end point of dermatitis.[14]

The current study determined several radiobiological fitting parameters from the SDR curve of dermatitis. The parameter “n” value is individual to each organ and describes the dose-response relationship volumetric dependence. The complication probability curves for a tissue are affected by the parameter “n”. As the value of “n” increases, so does the volume dependence for the occurrence of complication.[32] The value of “n” is 0.03 for both Grade-1 and Grade-2 dermatitis, respectively, which is more than zero for the OAR skin as shown in [Figure 2]d and [Figure 3]d. Therefore, complication probability produced is having small volume dependence of the tissue being irradiated. The curves are shown in [Figure 2]b and [Figure 3]b are for Grade-1 and Grade-2 dermatitis and representing complication probability as a function of partial volume keeping the dose constant. The SDR curves of dermatitis for both grades show threshold type behavior of complication probability for any given dose. The complication probability is not varying with partial volume until a certain volume gets irradiated. At low partial volumes, the toxicity rises faster; as the dose increases, complication probability increases. As the TD50 values increase, the severity of complication also increases gradually for the radiobiological endpoint for different grades of toxicity.

[Figure 2]a and [Figure 3]a represent the partial volume as a function of dose, keeping the complication probability constant for dermatitis for both the grades corresponding to complication probability of 5, 20, and 50 percent. As the dose is increased for constant complication, the irradiated partial volume decreases.

The tolerance doses for 5%, 20%, and 50% complication of the irradiated tissues were calculated for whole, 2/3rd and 1/3rd uniform organ irradiation as shown in [Figure 2]c and [Figure 3]c. For any constant partial volume of skin, complication probability rises as the dose is increased.

Any dose volume-related complication probabilities can also be calculated using the nomogram diagram as shown in [Figure 2]d and [Figure 3]d. The SDR curve for normal tissue is the probability of causing complications in an organ as a function of dose.[33] The dose at which 50% response probability is achieved is TD50 and γ50 is the slope normalized at 50% complication for a given dose. The parameter “m” determines the slope of the curve for complication probability as a function of dose.[31] The slight variation in the “m” and TD50 changes the complication probability as shown in [Figure 2]c and [Figure 3]c representing the complication probability as a function of dose, keeping the partial volume constant for whole, 2/3rd, and 1/3rd volume of irradiation. As the dose is increased, complication probability is also increased for any fixed irradiated partial volume. This work is limited by (i) a small number of patients (n = 25) and a single institutional data set; (ii) dose volume histogram data are utilized to determine volumetric doses of OARs without spatial information. The spatial radiobiological response of OARs can be evaluated using voxel-based approaches, which is outside the scope of this work.[34],[35] The results of radiobiological parameters extracted from SDR curves can be used to estimate NTCP of acute dermatitis in breast cancer patients.


 > Conclusion Top


One of the most recurring complications of breast radiation therapy is acute dermatitis, which results as a response to therapeutic management. In this single-institution cohort, the rate and severity of acute dermatitis observed following IMRT are low. In this study, radiobiological parameters were derived successfully from SDR curve for Grade-1 and Grade-2 acute dermatitis of individual breast cancer patients. These parameters can be used to estimate the dependence of toxicity in this organ, which can predict the acute dermatitis in a large patient cohort. Using nomogram of Grade-1 and Grade-2 toxicity, any reader can manually calculate the dose volume-related complication probabilities of acute dermatitis.

There are inherent uncertainties associated with skin dose calculation at the body surface in commercial TPS; our results may vary depending on the algorithm used by the various TPS presented, which must be validated according to their clinics. After calculating the radiobiological parameters, it increasse the clinician's confidence in taking any clinical decisions during plan evaluation. In addition to it, our results need to be validated in a larger cohort of patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
 > References Top

1.
Libson S, Lippman M. A review of clinical aspects of breast cancer. Int Rev Psychiatry 2014;26:4-15.  Back to cited text no. 1
    
2.
Pignol JP, Olivotto I, Rakovitch E, Gardner S, Sixel K, Beckham W, et al. A multicenter randomized trial of breast intensity-modulated radiation therapy to reduce acute radiation dermatitis. J Clin Oncol 2008;26:2085-92.  Back to cited text no. 2
    
3.
Parekh A, Dholakia AD, Zabranksy DJ, Asrari F, Camp M, Habibi M, et al. Predictors of radiation-induced acute skin toxicity in breast cancer at a single institution: Role of fractionation and treatment volume. Adv Radiat Oncol 2018;3:8-15.  Back to cited text no. 3
    
4.
Berthelet E, Truong PT, Musso K, Grant V, Kwan W, Moravan V, et al. Preliminary reliability and validity testing of a new Skin Toxicity Assessment Tool (STAT) in breast cancer patients undergoing radiotherapy. Am J Clin Oncol 2004;27:626-31.  Back to cited text no. 4
    
5.
Knobf MT, Sun Y. A longitudinal study of symptoms and self-care activities in women treated with primary radiotherapy for breast cancer. Cancer Nurs 2005;28:210-8.  Back to cited text no. 5
    
6.
Wengström Y, Häggmark C, Strander H, Forsberg C. Perceived symptoms and quality of life in women with breast cancer receiving radiation therapy. Eur J Oncol Nurs 2000;4:78-88.  Back to cited text no. 6
    
7.
Cox JD, Stetz J, Pajak TF. Toxicity criteria of the Radiation Therapy Oncology Group (RTOG) and the European Organization for Research and Treatment of Cancer (EORTC) Int J Radiat Oncol Biol Phys 1995;31:1341-6.  Back to cited text no. 7
    
8.
Harper JL, Franklin LE, Jenrette JM, Aguero EG. Skin toxicity during breast irradiation: Pathophysiology and management. South Med J 2004;97:989-93.  Back to cited text no. 8
    
9.
Porock D, Kristjanson L. Skin reactions during radiotherapy for breast cancer: The use and impact of topical agents and dressings. Eur J Cancer Care (Engl) 1999;8:143-53.  Back to cited text no. 9
    
10.
Hymes SR, Strom EA, Fife C. Radiation dermatitis: Clinical presentation, pathophysiology, and treatment 2006. J Am Acad Dermatol 2006;54:28-46.  Back to cited text no. 10
    
11.
Wei J, Meng L, Hou X, Qu C, Wang B, Xin Y, et al. Radiation-induced skin reactions: mechanism and treatment. Cancer Manag Res 2019;11:167-77.  Back to cited text no. 11
    
12.
Jiang ZQ, Yang K, Komaki R, Wei X, Tucker SL, Zhuang Y, et al. Long-term clinical outcome of intensity-modulated radiotherapy for inoperable non-small cell lung cancer: The MD Anderson experience. Int J Radiat Oncol Biol Phys 2012;83:332-9.  Back to cited text no. 12
    
13.
Cancer Therapy Evaluation Program (CTEP). Common Terminology Criteria for Adverse Events (CTCAE).v. 5.0 [5x7]. Bethesda, Md: Cancer Therapy Evaluation Program; 2017. p. 155. Available from: https://ctep.cancer.gov/protocoldevelopment/electronic_applications/docs/ctcae_v5_quick_reference_5x7.pdf [Last accessed on 2017 Nov 17].  Back to cited text no. 13
    
14.
Palma G, Conson M, Xu T, Hahn SM, Durante M, Mohan R, et al. Severe radiation induced dermatitis after IMRT or proton therapy for thoracic cancer patients. Int J Radiat Oncol Biol Phys 2019;105:S6.  Back to cited text no. 14
    
15.
Huszno J, Budryk M, Kołosza Z, Nowara E. The risk factors of toxicity during chemotherapy and radiotherapy in breast cancer patients according to the presence of BRCA gene mutation. Contemp Oncol (Pozn) 2015;19:72-6.  Back to cited text no. 15
    
16.
Rubin P, Cassarett GW. Urinary tract: The kidney. Clin Radiat Pathol 1968;1:293-333.  Back to cited text no. 16
    
17.
Burnet NG, Thomas SJ, Burton KE, Jefferies SJ. Defining the tumour and target volumes for radiotherapy. Cancer Imaging 2004;4:153-61.  Back to cited text no. 17
    
18.
Warkentin B. Radiobiological modelling in radiation oncology. Med Phys 2008;35:1621.  Back to cited text no. 18
    
19.
Shanei A, Amouheidari A, Abedi I, Kazemzadeh A, Jaafari A. Radiobiological comparison of 3D conformal and intensity modulated radiation therapy in the treatment of left-sided breast cancer. Int J Radiat Res 2020;18:315-22.  Back to cited text no. 19
    
20.
Oinam AS, Singh L, Shukla A, Ghoshal S, Kapoor R, Sharma SC. Dose volume histogram analysis and comparison of different radiobiological models using in-house developed software. J Med Phys 2011;36:220-9.  Back to cited text no. 20
[PUBMED]  [Full text]  
21.
Kehwar TS. Analytical approach to estimate normal tissue complication probability using best fit of normal tissue tolerance doses into the NTCP equation of the linear quadratic model. J Cancer Res Ther 2005;1:168-79.  Back to cited text no. 21
    
22.
Rubin P, Casarett GW. Clinical radiation pathology as applied to curative radiotherapy. Cancer 1968;22:767-78.  Back to cited text no. 22
    
23.
Emami B, Lyman J, Brown A, Coia L, Goitein M, Munzenrider JE, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21:109-22.  Back to cited text no. 23
    
24.
Pastore F, Conson M, D'Avino V, Palma G, Liuzzi R, Solla R, et al. Dose-surface analysis for prediction of severe acute radio-induced skin toxicity in breast cancer patients. Acta Oncol 2016;55:466-73.  Back to cited text no. 24
    
25.
Niemierko A, Goitein M. Modeling of normal tissue response to radiation: The critical volume model. Int J Radiat Oncol Biol Phys 1993;25:135-45.  Back to cited text no. 25
    
26.
Offersen BV, Boersma LJ, Kirkove C, Hol S, Aznar MC, Biete A, et al. ESTRO consensus guideline on target volume delineation for elective radiation therapy of early stage breast cancer. Radiother Oncol 2015;114:3-10.  Back to cited text no. 26
    
27.
Romestaing P, Lehingue Y, Carrie C, Coquard R, Montbarbon X, Ardiet JM, et al. Role of a 10-Gy boost in the conservative treatment of early breast cancer: Results of a randomized clinical trial in Lyon, France. J Clin Oncol 1997;15:963-8.  Back to cited text no. 27
    
28.
Gregoire V, Mackie TR. Dose prescription, reporting and recording in intensity-modulated radiation therapy: A digest of the ICRU Report 83. Imaging Med 2011;3:367.  Back to cited text no. 28
    
29.
Liu L, Meers K, Capurso A, Engebretson TO, Glicksman AS. The impact of radiation therapy on quality of life in patients with cancer. Cancer Pract 1998;6:237-42.  Back to cited text no. 29
    
30.
Bentzen SM, Constine LS, Deasy JO, Eisbruch A, Jackson A, Marks LB, et al. Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC): An introduction to the scientific issues. Int J Radiat Oncol Biol Phys 2010;76:S3-9.  Back to cited text no. 30
    
31.
Burman C, Kutcher GJ, Emami B, Goitein M. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123-35.  Back to cited text no. 31
    
32.
Marks LB, Yorke ED, Jackson A, Ten Haken RK, Constine LS, Eisbruch A, et al. Use of normal tissue complication probability models in the clinic. Int J Radiat Oncol Biol Phys 2010;76:S10-9.  Back to cited text no. 32
    
33.
Stavreva N, Stavrev P, Warkentin B, Fallone BG. Derivation of the expressions for $γ$50 and D50 for different individual TCP and NTCP models. Phys Med Biol 2002;47:3591.  Back to cited text no. 33
    
34.
Singh G, Oinam AS, Kamal R, Handa B, Kumar V, Rai B. Voxel based BED and EQD2 evaluation of the radiotherapy treatment plan. J Med Phys 2018;43:155-61.  Back to cited text no. 34
[PUBMED]  [Full text]  
35.
Singh G, Kamal R, Thaper D, Oinam AS, Handa B, Kumar V, et al. Voxel based evaluation of sequential radiotherapy treatment plans with different dose fractionation schemes. Br J Radiol 2020;93:20200197.  Back to cited text no. 35
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

 
Top
 
 
  Search
 
     Search Pubmed for
 
    -  Singh B
    -  Singh G
    -  Oinam AS
    -  Singh M
    -  Katake A
    -  Kumar V
    -  Vashistha R
    -  Singh PK
    -  Mahajan R
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  >Abstract>Introduction>Materials and Me...>Results>Discussion>Conclusion>Article Figures>Article Tables
  In this article
>References

 Article Access Statistics
    Viewed537    
    PDF Downloaded2    

Recommend this journal