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1.
Radiat Prot Dosimetry ; 194(4): 214-222, 2021 Aug 02.
Article in English | MEDLINE | ID: mdl-34244802

ABSTRACT

This study was conducted to determine first local diagnostic reference levels (DRLs) and achievable doses (ADs) for pediatric patients during the most common computed tomography (CT) procedures in Yazd province. The DRL was obtained based on volume CT dose index (CTDIvol) and dose length product (DLP) for four various age groups of children. Data were collected from the most commonly performed pediatric CT scans, including abdomen-pelvis, chest, brain and sinus examinations, at six high-loaded institutes. The patients' data (766 no.) in terms of CTDIvol and DLP were obtained from four age groups: ≤1-, 1-5-, 5-10- and 10-15-y-old. The 75th percentiles of CTDIvol and DLP were considered as DRL values and the 50th percentiles were described as ADs for those parameters. Consequently, the acquired DRLs were compared with other national and international published values. The DRLs in terms of CTDIvol for abdomen-pelvis, chest, brain and sinus examinations were 3, 8, 9 and 10 mGy; 4, 5, 5 and 5 mGy; 25, 28, 29 and 38 mGy; and 23, 24, 26 and 27 mGy for four different age groups of ≤1-, 1-5-, 5-10- and 10-15-y-old, respectively. The DRL values in terms of DLP were 75, 302, 321 and 342 mGy.cm; 109, 112, 135 and 170 mGy.cm, 352, 355, 360 and 481 mGy.cm; and 206, 211, 228 and 245 mGy.cm, respectively, for the mentioned age groups. In this study, the DRL and AD values in the brain examination were greater among the other studied regions. The DRL plays a critical role in the optimization of radiation doses delivered to patients and in improving their protection. This study provides the local DRLs and ADs for the most common pediatric CT scanning in Yazd province to create optimum situation for the clinical practice.


Subject(s)
Diagnostic Reference Levels , Tomography, X-Ray Computed , Child , Humans , Radiation Dosage , Reference Values , Thorax
2.
J Cancer Res Ther ; 16(6): 1323-1330, 2020.
Article in English | MEDLINE | ID: mdl-33342791

ABSTRACT

PURPOSE: Different dose calculation algorithms (DCAs) predict different dose distributions for the same treatment. Awareness of optimal model parameters is vital for estimating normal tissue complication probability (NTCP) for different algorithms. The aim is to determine the NTCP parameter values for different DCAs in left-sided breast radiotherapy, using the Lyman-Kutcher-Burman (LKB) model. MATERIALS AND METHODS: First, the methodology recommended by International Atomic Energy Agency TEC-DOC 1583 was used to establish the accuracy of dose calculations of different DCAs including: Monte Carlo (MC) and collapsed cone algorithms implemented in Monaco, pencil beam convolution (PBC) and analytical anisotropic algorithm (AAA) implemented in Eclipse, and superposition and Clarkson algorithms implemented in PCRT3D treatment planning systems (TPSs). Then, treatment planning of 15 patients with left-sided breast cancer was performed by the mentioned DCAs and NTCP of the left-lung normal tissue were calculated for each patient individually, using the LKB model. For the PB algorithm, the NTCP parameters were taken from previously published values and new model parameters obtained for each DCA, using the iterative least squares methods. RESULTS: For all cases and DCAs, NTCP computation with the same model parameters resulted in >15% deviation in NTCP values. The new NTCP model parameters were classified according to the algorithm type. Thus, the discrepancy of NTCP computations was reduced up to 5% after utilizing adjusted model parameters. CONCLUSIONS: This paper confirms that the NTCP values for a given treatment type are different for the different DCAs. Thus, it is essential to introduce appropriate NTCP parameter values according to DCA adopted in TPS, to obtain a more precise estimation of lung NTCP. Hence, new parameter values, classified according to the DCAs, must be determined before introducing NTCP estimation in clinical practice.


Subject(s)
Algorithms , Breast Neoplasms/radiotherapy , Lung/radiation effects , Radiotherapy Planning, Computer-Assisted/methods , Breast Neoplasms/pathology , Female , Humans , Monte Carlo Method , Probability , Radiotherapy Dosage
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