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Skin dose enhancement from the application of skin-care creams using FF and FFF photon beams in radiotherapy: A Monte Carlo phantom evaluation

  • Received: 03 March 2020 Accepted: 21 April 2020 Published: 21 April 2020
  • Skin-care cream is commonly applied to relieve skin redness in radiotherapy. However, using cream on the patient under the photon field would increase the skin dose in delivery. The aim of this study is to evaluate the dependences of skin dose enhancement on different beam and cream variables using Monte Carlo simulation. Using a solid water phantom with water-equivalent bolus, PMMA layer and cream layer, we irradiated it by 6 MV photon beams. Skin doses were calculated by varying the beam quality (flattening-filter (FF) and flattening-filter-free (FFF)), beam angle (0°–80°), skin-care cream type (water-based and silicon-based) and cream thickness (0–3 mm) using the EGSnrc Monte Carlo code. The densities of the water- and silicon-based cream were 0.92 and 1.14 g/cm3. The dose enhancement factor (DEF) defined as the ratio of the skin dose with skin-care cream to the skin dose without cream was calculated. It is found that the FF photon beam had higher DEF value than the FFF. For the water-based cream of 3 mm, the DEF for the FF beam was about 22.1% higher than that of the FFF. While for the silicon-based cream with the same thickness, the DEF was 24.2% higher. DEF value also increased with the beam angle. The DEF values were from 1.4 to 2.52 (water-based cream) and 1.42 to 2.68 (silicon-based cream) when the beam angle was increased from 20° to 80° using the 6 MV FF beams. Similarly, for the 6 MV FFF beams, the DEF values increased from 1.29 to 2.07 and 1.30 to 2.18 for the water- and silicon-based cream. These simulation results showed that the skin dose enhancement increased with an increase of beam angle, cream thickness, cream density, and the irradiation of FFF photon beams.

    Citation: Megha Sharma, James C. L. Chow. Skin dose enhancement from the application of skin-care creams using FF and FFF photon beams in radiotherapy: A Monte Carlo phantom evaluation[J]. AIMS Bioengineering, 2020, 7(2): 82-90. doi: 10.3934/bioeng.2020008

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  • Skin-care cream is commonly applied to relieve skin redness in radiotherapy. However, using cream on the patient under the photon field would increase the skin dose in delivery. The aim of this study is to evaluate the dependences of skin dose enhancement on different beam and cream variables using Monte Carlo simulation. Using a solid water phantom with water-equivalent bolus, PMMA layer and cream layer, we irradiated it by 6 MV photon beams. Skin doses were calculated by varying the beam quality (flattening-filter (FF) and flattening-filter-free (FFF)), beam angle (0°–80°), skin-care cream type (water-based and silicon-based) and cream thickness (0–3 mm) using the EGSnrc Monte Carlo code. The densities of the water- and silicon-based cream were 0.92 and 1.14 g/cm3. The dose enhancement factor (DEF) defined as the ratio of the skin dose with skin-care cream to the skin dose without cream was calculated. It is found that the FF photon beam had higher DEF value than the FFF. For the water-based cream of 3 mm, the DEF for the FF beam was about 22.1% higher than that of the FFF. While for the silicon-based cream with the same thickness, the DEF was 24.2% higher. DEF value also increased with the beam angle. The DEF values were from 1.4 to 2.52 (water-based cream) and 1.42 to 2.68 (silicon-based cream) when the beam angle was increased from 20° to 80° using the 6 MV FF beams. Similarly, for the 6 MV FFF beams, the DEF values increased from 1.29 to 2.07 and 1.30 to 2.18 for the water- and silicon-based cream. These simulation results showed that the skin dose enhancement increased with an increase of beam angle, cream thickness, cream density, and the irradiation of FFF photon beams.



    For a convex function σ:IRR on I with ν1,ν2I and ν1<ν2, the Hermite-Hadamard inequality is defined by [1]:

    σ(ν1+ν22)1ν2ν1ν2ν1σ(η)dησ(ν1)+σ(ν2)2. (1.1)

    The Hermite-Hadamard integral inequality (1.1) is one of the most famous and commonly used inequalities. The recently published papers [2,3,4] are focused on extending and generalizing the convexity and Hermite-Hadamard inequality.

    The situation of the fractional calculus (integrals and derivatives) has won vast popularity and significance throughout the previous five decades or so, due generally to its demonstrated applications in numerous seemingly numerous and great fields of science and engineering [5,6,7].

    Now, we recall the definitions of Riemann-Liouville fractional integrals.

    Definition 1.1 ([5,6,7]). Let σL1[ν1,ν2]. The Riemann-Liouville integrals Jϑν1+σ and Jϑν2σ of order ϑ>0 with ν10 are defined by

    Jϑν1+σ(x)=1Γ(ϑ)xν1(xη)ϑ1σ(η)dη,   ν1<x (1.2)

    and

    Jϑν2σ(x)=1Γ(ϑ)ν2x(ηx)ϑ1σ(η)dη,  x<ν2, (1.3)

    respectively. Here Γ(ϑ) is the well-known Gamma function and J0ν1+σ(x)=J0ν2σ(x)=σ(x).

    With a huge application of fractional integration and Hermite-Hadamard inequality, many researchers in the field of fractional calculus extended their research to the Hermite-Hadamard inequality, including fractional integration rather than ordinary integration; for example see [8,9,10,11,12,13,14,15,16,17,18,19,20,21].

    In this paper, we consider the integral inequality of Hermite-Hadamard-Mercer type that relies on the Hermite-Hadamard and Jensen-Mercer inequalities. For this purpose, we recall the Jensen-Mercer inequality: Let 0<x1x2xn and μ=(μ1,μ2,,μn) nonnegative weights such that ni=1μi=1. Then, the Jensen inequality [22,23] is as follows, for a convex function σ on the interval [ν1,ν2], we have

    σ(ni=1μixi)ni=1μiσ(xi), (1.4)

    where for all xi[ν1,ν2] and μi[0,1], (i=¯1,n).

    Theorem 1.1 ([2,23]). If σ is convex function on [ν1,ν2], then

    σ(ν1+ν2ni=1μixi)σ(ν1)+σ(ν2)ni=1μiσ(xi), (1.5)

    for each xi[ν1,ν2] and μi[0,1], (i=¯1,n) with ni=1μi=1. For some results related with Jensen-Mercer inequality, see [24,25,26].

    In view of above indices, we establish new integral inequalities of Hermite-Hadamard-Mercer type for convex functions via the Riemann-Liouville fractional integrals in the current project. Particularly, we see that our results can cover the previous researches.

    Theorem 2.1. For a convex function σ:[ν1,ν2]RR with x,y[ν1,ν2], we have:

    σ(ν1+ν2x+y2)2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1)+σ(ν2)σ(x)+σ(y)2. (2.1)

    Proof. By using the convexity of σ, we have

    σ(ν1+ν2u+v2)12[σ(ν1+ν2u)+σ(ν1+ν2v)], (2.2)

    and above with u=1η2x+1+η2y, v=1+η2x+1η2y, where x,y[ν1,ν2] and η[0,1], leads to

    σ(ν1+ν2x+y2)12[σ(ν1+ν2(1η2x+1+η2y))+σ(ν1+ν2(1+η2x+1η2y))]. (2.3)

    Multiplying both sides of (2.3) by ηϑ1 and then integrating with respect to η over [0,1], we get

    1ϑσ(ν1+ν2x+y2)12[10ηϑ1σ(ν1+ν2(1η2x+1+η2y))dη+10ηϑ1σ(ν1+ν2(1+η2x+1η2y))dη]=12[2ϑ(yx)ϑν1+ν2x+y2ν1+ν2y((ν1+ν2x+y2)w)ϑ1σ(w)dw+2ϑ(yx)ϑν1+ν2xν1+ν2x+y2(w(ν1+ν2x+y2))ϑ1σ(w)dw]=2ϑ1Γ(ϑ)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)],

    and thus the proof of first inequality in (2.1) is completed.

    On the other hand, we have by using the Jensen-Mercer inequality:

    σ(ν1+ν2(1η2x+1+η2y))σ(ν1)+σ(ν2)(1η2σ(x)+1+η2σ(y)) (2.4)
    σ(ν1+ν2(1+η2x+1η2y))σ(ν1)+σ(ν2)(1+η2σ(x)+1η2σ(y)). (2.5)

    Adding inequalities (2.4) and (2.5) to get

    σ(ν1+ν2(1η2x+1+η2y))+σ(ν1+ν2(1+η2x+1η2y))2[σ(ν1)+σ(ν2)][σ(x)+σ(y)]. (2.6)

    Multiplying both sides of (2.6) by ηϑ1 and then integrating with respect to η over [0,1] to obtain

    10ηϑ1σ(ν1+ν2(1η2x+1+η2y))dη+10ηϑ1σ(ν1+ν2(1+η2x+1η2y))dη2ϑ[σ(ν1)+σ(ν2)]1ϑ[σ(x)+σ(y)].

    By making use of change of variables and then multiplying by ϑ2, we get the second inequality in (2.1).

    Remark 2.1. If we choose ϑ=1, x=ν1 and y=ν2 in Theorem 2.1, then the inequality (2.1) reduces to (1.1).

    Corollary 2.1. Theorem 2.1 with

    ϑ=1 becomes [24, Theorem 2.1].

    x=ν1 and y=ν2 becomes:

    σ(ν1+ν22)2ϑ1Γ(ϑ+1)(ν2ν1)ϑ[Jϑν1+σ(ν1+ν22)+Jϑν2σ(ν1+ν22)]σ(ν1)+σ(ν2)2,

    which is obtained by Mohammed and Brevik in [10].

    The following Lemma linked with the left inequality of (2.1) is useful to obtain our next results.

    Lemma 2.1. Let σ:[ν1,ν2]RR be a differentiable function on (ν1,ν2) and σL[ν1,ν2] with ν1ν2 and x,y[ν1,ν2]. Then, we have:

    2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)=(yx)410ηϑ[σ(ν1+ν2(1η2x+1+η2y))σ(ν1+ν2(1+η2x+1η2y))]dη. (2.7)

    Proof. From right hand side of (2.7), we set

    ϖ1ϖ2:=10ηϑ[σ(ν1+ν2(1η2x+1+η2y))σ(ν1+ν2(1+η2x+1η2y))]dη=10ηϑσ(ν1+ν2(1η2x+1+η2y))dη10ηϑσ(ν1+ν2(1+η2x+1η2y))dη. (2.8)

    By integrating by parts with w=ν1+ν2(1η2x+1+η2y), we can deduce:

    ϖ1=2(yx)σ(ν1+ν2y)+2ϑ(yx)10ηϑ1σ(ν1+ν2(1η2x+1+η2y))dη=2(yx)σ(ν1+ν2y)+2ϑ+1ϑ(yx)ϑ+1ν1+ν2x+y2ν1+ν2yσ((ν1+ν2x+y2)w)ϑ1σ(w)dw=2(yx)σ(ν1+ν2y)+2ϑ+1Γ(ϑ+1)(yx)ϑ+1Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2).

    Similarly, we can deduce:

    ϖ2=2yxσ(ν1+ν2x)2ϑ+1Γ(ϑ+1)(yx)ϑ+1Jϑ(ν1+ν2x)σ(ν1+ν2x+y2).

    By substituting ϖ1 and ϖ2 in (2.8) and then multiplying by (yx)4, we obtain required identity (2.7).

    Corollary 2.2. Lemma 2.1 with

    ϑ=1 becomes:

    1yxν1+ν2xν1+ν2yσ(w)dwσ(ν1+ν2x+y2)=(yx)410η[σ(ν1+ν2(1η2x+1+η2y))σ(ν1+ν2(1+η2x+1η2y))]dη.

    ϑ=1, x=ν1 and y=ν2 becomes:

    1ν2ν1ν2ν1σ(w)dwσ(ν1+ν22)=(ν2ν1)410η[σ(ν1+ν2(1η2ν1+1+η2ν2))σ(ν1+ν2(1+η2ν1+1η2ν2))]dη.

    x=ν1 and y=ν2 becomes:

    2ϑ1Γ(ϑ+1)(ν2ν1)ϑ[Jϑν1+σ(ν1+ν22)+Jϑν2σ(ν1+ν22)]σ(ν1+ν22)=(ν2ν1)410ηϑ[σ(ν1+ν2(1η2ν1+1+η2ν2))σ(ν1+ν2(1+η2ν1+1η2ν2))]dη.

    Theorem 2.2. Let σ:[ν1,ν2]RR be a differentiable function on (ν1,ν2) and |σ| is convex on [ν1,ν2] with ν1ν2 and x,y[ν1,ν2]. Then, we have:

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)2(1+ϑ)[|σ(ν1)|+|σ(ν2)||σ(x)|+|σ(y)|2]. (2.9)

    Proof. By taking modulus of identity (2.7), we get

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4[10ηϑ|σ(ν1+ν2(1η2x+1+η2y))|dη+10ηϑ|σ(ν1+ν2(1+η2x+1η2y))|dη].

    Then, by applying the convexity of |σ| and the Jensen-Mercer inequality on above inequality, we get

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4[10ηϑ[|σ(ν1)|+|σ(ν2)|(1+η2|σ(x)|+1η2)|σ(y)|]dη+10ηϑ[|σ(ν1)|+|σ(ν2)|(1η2|σ(x)|+1+η2)|σ(y)|]dη]=(yx)2(1+ϑ)[|σ(ν1)|+|σ(ν2)||σ(x)|+|σ(y)|2],

    which completes the proof of Theorem 2.2.

    Corollary 2.3. Theorem 2.2 with

    ϑ=1 becomes:

    |1yxν1+ν2xν1+ν2yσ(w)dwσ(ν1+ν2x+y2)|(yx)4[|σ(ν1)|+|σ(ν2)||σ(x)|+|σ(y)|2].

    ϑ=1, x=ν1 and y=ν2 becomes [27, Theorem 2.2].

    x=ν1 and y=ν2 becomes:

    |1ν2ν1ν2ν1σ(w)dwσ(ν1+ν22)|(ν2ν1)4[|σ(ν1)|+|σ(ν2)|2].

    Theorem 2.3. Let σ:[ν1,ν2]RR be a differentiable function on (ν1,ν2) and |σ|q,q>1 is convex on [ν1,ν2] with ν1ν2 and x,y[ν1,ν2]. Then, we have:

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4pϑp+1[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+3|σ(y)|q4))1q+(|σ(ν1)|q+|σ(ν2)|q(3|σ(x)|q+|σ(y)|q4))1q], (2.10)

    where 1p+1q=1.

    Proof. By taking modulus of identity (2.7) and using Hölder's inequality, we get

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4(10ηϑp)1p{(10|σ(ν1+ν2(1η2x+1+η2y))|qdη)1q+(10|σ(ν1+ν2(1+η2x+1η2y))|qdη)1q}.

    Then, by applying the Jensen-Mercer inequality with the convexity of |σ|q, we can deduce

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4(10ηϑp)1p{(10|σ(ν1)|q+|σ(ν2)|q(1η2|σ(x)|q+1+η2|σ(y)|q))1q+(10|σ(ν1)|q+|σ(ν2)|q(1+η2|σ(x)|q+1η2|σ(y)|q))1q}=(yx)4pϑp+1[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+3|σ(y)|q4))1q+(|σ(ν1)|q+|σ(ν2)|q(3|σ(x)|q+|σ(y)|q4))1q],

    which completes the proof of Theorem 2.3.

    Corollary 2.4. Theorem 2.3 with

    ϑ=1 becomes:

    |1yxν1+ν2xν1+ν2yσ(w)dwσ(ν1+ν2x+y2)|(yx)4pp+1[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+3|σ(y)|q4))1q+(|σ(ν1)|q+|σ(ν2)|q(3|σ(x)|q+|σ(y)|q4))1q].

    ϑ=1, x=ν1 and y=ν2 becomes:

    |1ν2ν1ν2ν1σ(w)dwσ(ν1+ν22)|(ν2ν1)22p(1p+1)1p[|σ(ν1)|+|σ(ν2)|].

    x=ν1 and y=ν2 becomes:

    |2ϑ1Γ(ϑ+1)(ν2ν1)ϑ[Jϑν1+σ(ν1+ν22)+Jϑν2σ(ν1+ν22)]σ(ν1+ν22)|2ϑ12qν2ν1(1p+1)1p[|σ(ν1)|+|σ(ν2)|].

    Theorem 2.4. Let σ:[ν1,ν2]RR be a differentiable function on (ν1,ν2) and |σ|q,q1 is convex on [ν1,ν2] with ν1ν2 and x,y[ν1,ν2]. Then, we have:

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4(ϑ+1)[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+(2ϑ+3)|σ(y)|q2(ϑ+2)))1q+(|σ(ν1)|q+|σ(ν2)|q((2ϑ+3)|σ(x)|q+|σ(y)|q2(ϑ+2)))1q]. (2.11)

    Proof. By taking modulus of identity (2.7) with the well-known power mean inequality, we can deduce

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4(10ηϑ)11q{(10ηϑ|σ(ν1+ν2(1η2x+1+η2y))|qdη)1q+(10ηϑ|σ(ν1+ν2(1+η2x+1η2y))|qdη)1q}.

    By applying the Jensen-Mercer inequality with the convexity of |σ|q, we can deduce

    |2ϑ1Γ(ϑ+1)(yx)ϑ[Jϑ(ν1+ν2y)+σ(ν1+ν2x+y2)+Jϑ(ν1+ν2x)σ(ν1+ν2x+y2)]σ(ν1+ν2x+y2)|(yx)4(10ηϑ)11q{(10ηϑ[|σ(ν1)|q+|σ(ν2)|q(1η2|σ(x)|q+1+η2|σ(y)|q)])1q+(10ηϑ[|σ(ν1)|q+|σ(ν2)|q(1+η2|σ(x)|q+1η2|σ(y)|q)])1q}=(yx)4(ϑ+1)[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+(2ϑ+3)|σ(y)|q2(ϑ+2)))1q+(|σ(ν1)|q+|σ(ν2)|q((2ϑ+3)|σ(x)|q+|σ(y)|q2(ϑ+2)))1q],

    which completes the proof of Theorem 2.4.

    Corollary 5. Theorem 2.4 with

    q=1 becomes Theorem 2.2.

    ϑ=1 becomes:

    |1yxν1+ν2xν1+ν2yσ(w)dwσ(ν1+ν2x+y2)|(yx)8[(|σ(ν1)|q+|σ(ν2)|q(|σ(x)|q+5|σ(y)|q6))1q+(|σ(ν1)|q+|σ(ν2)|q(5|σ(x)|q+|σ(y)|q6))1q].

    ϑ=1, x=ν1 and y=ν2 becomes:

    |1ν2ν1ν2ν1σ(w)dwσ(ν1+ν22)|(yx)8[(5|σ(ν1)|q+|σ(ν2)|q6)1q+(|σ(ν1)|q+5|σ(ν2)|q6)1q].

    x=ν1 and y=ν2 becomes:

    |2ϑ1Γ(ϑ+1)(ν2ν1)ϑ[Jϑν1+σ(ν1+ν22)+Jϑν2σ(ν1+ν22)]σ(ν1+ν22)|(ν2ν1)4(ϑ+1)[((2ϑ+3)|σ(ν1)|q+|σ(ν2)|q2(ϑ+2))1q+(|σ(ν1)|q+(2ϑ+3)|σ(ν2)|q2(ϑ+2))1q].

    Here, we consider the following special means:

    ● The arithmetic mean:

    A(ν1,ν2)=ν1+ν22,ν1,ν20.

    ● The harmonic mean:

    H(ν1,ν2)=2ν1ν2ν1+ν2,ν1,ν2>0.

    ● The logarithmic mean:

    L(ν1,ν2)={ν2ν1lnν2lnν1,ifν1ν2,ν1,ifν1=ν2,ν1,ν2>0.

    ● The generalized logarithmic mean:

    Ln(ν1,ν2)={[νn+12νn+11(n+1)(ν2ν1)]1n,ifν1ν2ν1,ifν1=ν2,ν1,ν2>0;nZ{1,0}.

    Proposition 3.1. Let 0<ν1<ν2 and nN, n2. Then, for all x,y[ν1,ν2], we have:

    |Lnn(ν1+ν2y,ν1+ν2x)(2A(ν1,ν2)A(x,y))n|n(yx)4[2A(νn11,νn12)A(xn1,yn1)]. (3.1)

    Proof. By applying Corollary 2.3 (first item) for the convex function σ(x)=xn,x>0, one can obtain the result directly.

    Proposition 3.2. Let 0<ν1<ν2. Then, for all x,y[ν1,ν2], we have:

    |L1(ν1+ν2y,ν1+ν2x)(2A(ν1,ν2)A(x,y))1|(yx)4[2H1(ν21,ν22)H1(x2,y2)]. (3.2)

    Proof. By applying Corollary 2.3 (first item) for the convex function σ(x)=1x,x>0, one can obtain the result directly.

    Proposition 3.3. Let 0<ν1<ν2 and nN, n2. Then, we have:

    |Lnn(ν1,ν2)An(ν1,ν2)|n(ν2ν1)4[A(νn11,νn12)], (3.3)

    and

    |L1(ν1,ν2)A1(ν1,ν2)|(ν2ν1)4H1(ν21,ν22). (3.4)

    Proof. By setting x=ν1 and y=ν2 in results of Proposition 3.1 and Proposition 3.2, one can obtain the Proposition 3.3.

    Proposition 3.4. Let 0<ν1<ν2 and nN, n2. Then, for q>1,1p+1q=1 and for all x,y[ν1,ν2], we have:

    |Lnn(ν1+ν2y,ν1+ν2x)(2A(ν1,ν2)A(x,y))n|n(yx)4pp+1{[2A(νq(n1)1,νq(n1)2)12A(xq(n1),3yq(n1))]1q+[2A(νq(n1)1,νq(n1)2)12A(3xq(n1),yq(n1))]1q}. (3.5)

    Proof. By applying Corollary 2.4 (first item) for convex function σ(x)=xn,x>0, one can obtain the result directly.

    Proposition 3.5. Let 0<ν1<ν2. Then, for q>1,1p+1q=1 and for all x,y[ν1,ν2], we have:

    |L1(ν1+ν2y,ν1+ν2x)(2A(ν1,ν2)A(x,y))1|q2(yx)4pp+1{[H1(ν2q1,ν2q2)34H1(x2q,3y2q)]1q+[H1(ν2q1,ν2q2)34H1(3x2q,y2q)]1q}. (3.6)

    Proof. By applying Corollary 2.4 (first item) for the convex function σ(x)=1x,x>0, one can obtain the result directly.

    Proposition 3.6. Let 0<ν1<ν2 and nN, n2. Then, for q>1 and 1p+1q=1, we have:

    |Lnn(ν1,ν2)An(ν1,ν2)|n(ν2ν1)4pp+1{[2A(νq(n1)1,νq(n1)2)12A(νq(n1)1,3νq(n1)2)]1q+[2A(νq(n1)1,νq(n1)2)12A(3νq(n1)1,νq(n1)2)]1q}, (3.7)

    and

    |L1(ν1,ν2)A1(ν1,ν2)|q2(ν2ν1)4pp+1{[H1(ν2q1,ν2q2)34H1(ν2q1,3ν2q2)]1q+[H1(ν2q1,ν2q2)34H1(3ν2q1,ν2q2)]1q}. (3.8)

    Proof. By setting x=ν1 and y=ν2 in results of Proposition 3.4 and Proposition 3.5, one can obtain the Proposition 3.6.

    As we emphasized in the introduction, integral inequality is the most important field of mathematical analysis and fractional calculus. By using the well-known Jensen-Mercer and power mean inequalities, we have proved new inequalities of Hermite-Hadamard-Mercer type involving Riemann-Liouville fractional operators. In the last section, we have considered some propositions in the context of special functions; these confirm the efficiency of our results.

    We would like to express our special thanks to the editor and referees. Also, the first author would like to thank Prince Sultan University for funding this work through research group Nonlinear Analysis Methods in Applied Mathematics (NAMAM) group number RG-DES-2017-01-17.

    The authors declare no conflict of interest.


    Acknowledgments



    The authors would like to thank Amir Owrangi of UT Southwestern Medical Centre for assistance in the phase-space files and photon energy spectra of the FF and FFF photon beams used in the Monte Carlo simulations.

    Conflict of interest



    The authors have no potential conflict of interest on financial or commercial matters associated with this study.

    [1] Delaney G, Jacob S, Featherstone C, et al. (2005) The role of radiotherapy in cancer treatment: estimating optimal utilization from a review of evidence-based clinical guidelines. Cancer 104: 1129-1137. doi: 10.1002/cncr.21324
    [2] Naylor W, Mallett J (2001) Management of acute radiotherapy induced skin reactions: a literature review. Eur J Oncol Nurs 5: 221-233. doi: 10.1054/ejon.2001.0145
    [3] Baumann BC, Verginadis II, Zeng C, et al. (2018) Assessing the validity of clinician advice that patients avoid use of topical agents before daily radiotherapy treatments. JAMA Oncol 4: 1742-1748. doi: 10.1001/jamaoncol.2018.4292
    [4] Harris R, Probst H, Beardmore C, et al. (2012) Radiotherapy skin care: A survey of practice in the UK. Radiography 18: 21-27. doi: 10.1016/j.radi.2011.10.040
    [5] Morley L, Cashell A, Sperduti A, et al. (2014) Evaluating the relevance of dosimetric considerations to patient teaching regarding skin care during radiation therapy. J Radiother Pract 13: 294-301. doi: 10.1017/S1460396913000241
    [6] Tse K, Morley L, Cashell A, et al. (2016) Dosimetric impacts on skin toxicity for patients using topical agents and dressings radiotherapy. J Radiother in Pract 15: 314-321. doi: 10.1017/S1460396916000285
    [7] Hadley SW, Kelly R, Lam K (2005) Effects of immobilization mask material on surface dose. J Appl Clin Med Phys 6: 1-7. doi: 10.1120/jacmp.v6i1.1957
    [8] Khan Y, Villarreal-Barajas JE, Udowicz M, et al. (2013) Clinical and dosimetric implications of air gaps between bolus and skin surface during radiation therapy. J Cancer Ther 4: 1251-1255. doi: 10.4236/jct.2013.47147
    [9] Løkkevik E, Skovlund E, Reitan JB, et al. (1996) Skin treatment with bepanthen cream versus no cream during radiotherapy: a randomized controlled trial. Acta Oncol 35: 1021-1026. doi: 10.3109/02841869609100721
    [10] Chow JCL, Grigorov GN (2008) Surface dosimetry for oblique tangential photon beams: A Monte Carlo simulation study. Med Phys 35: 70-76. doi: 10.1118/1.2818956
    [11] Chow JCL, Grigorov GN, Barnett RB (2006) Study on surface dose generated in prostate intensity-modulated radiation therapy treatment. Med Dosim 31: 249-258. doi: 10.1016/j.meddos.2005.07.002
    [12] Chow JCL, Owrangi AM (2016) A surface energy spectral study on the bone heterogeneity and beam obliquity using the flattened and unflattened photon beams. Rep Pract Oncol Radiother 21: 63-70. doi: 10.1016/j.rpor.2015.11.001
    [13] Chow JCL, Owrangi AM (2014) Dosimetric dependences of bone heterogeneity and beam angle on the unflattened and flattened photon beams: A Monte Carlo comparison. Radiat Phys Chem 101: 46-52. doi: 10.1016/j.radphyschem.2014.03.041
    [14] Bortfeld T (2006) IMRT: a review and preview. Phys Med Biol 51: R363. doi: 10.1088/0031-9155/51/13/R21
    [15] Jia J, Hui L, Chow JCL (2015) A leaf sequencing algorithm for multileaf collimator in intensity modulated radiotherapy. Rep Radiother Oncol 2: e4922.
    [16] Chow JCL, Grigorov GN, Yazdani N (2006) SWIMRT: A graphical user interface using sliding window algorithm to construct a fluence map machine file. J Appl Clin Med Phys 7: 69-85. doi: 10.1120/jacmp.v7i2.2231
    [17] Sharma SD (2011) Unflattened photon beams from the standard flattening filter free accelerators for radiotherapy: advantages, limitations and challenges. J Med Phys 36: 123-125. doi: 10.4103/0971-6203.83464
    [18] Chow JCL, Owrangi AM (2019) Mucosal dosimetry on unflattened photon beams: A Monte Carlo phantom study. Biomed Phys Eng Express 5: 015007. doi: 10.1088/2057-1976/aaeaaa
    [19] Chow JCL, Jiang R, Leung MKK (2011) Dosimetry of oblique tangential photon beams calculated by superposition/convolution algorithms: a Monte Carlo evaluation. J Appl Clin Med Phys 12: 108-121. doi: 10.1120/jacmp.v12i1.3424
    [20] Chow JCL (2018) Recent progress in Monte Carlo simulation of gold nanoparticle radiosensitization. AIMS Biophys 5: 231-244. doi: 10.3934/biophy.2018.4.231
    [21] Rogers DWO (2006) Fifty years of Monte Carlo simulations for medical physics. Phys Med Biol 51: R287. doi: 10.1088/0031-9155/51/13/R17
    [22] Kawrakow I, Mainegra-Hing E, Rogers DWO, et al. (2000) The EGSnrc code system: Monte Carlo simulation of electron and photon transport. NRCC Report PIRS-701 Ottawa: NRC, Available from: https://nrc-cnrc.github.io/EGSnrc/doc/pirs701-egsnrc.pdf.
    [23] Walters B, Kawrakow I, Rogers DWO (2005) DOSXYZnrc users manual. NRCC Report PIRS-794revB Ottawa: NRC, Available from: https://nrc-cnrc.github.io/EGSnrc/doc/pirs794-dosxyznrc.pdf.
    [24] Constantin M, Perl J, LoSasso T, et al. (2011) Modeling the TrueBeam linac using a CAD to Geant4 geometry implementation: dose and IAEA-compliant phase space calculations. Med Phys 38: 4018-4024. doi: 10.1118/1.3598439
    [25] Sardari D, Maleki R, Samavat H, et al. (2010) Measurement of depth-dose of linear accelerator and simulation by use of GEANT4 computer code. Rep Pract Oncol Radiother 15: 64-68. doi: 10.1016/j.rpor.2010.03.001
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