• Journal of the Korean Magnetics Society
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• v.26 no.5
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• pp.173-178
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• 2016

This study is to evaluate the effect of a Contrast Media (CM) on dose calculations and clinical significance in Radiation (Electromagnetic wave) Therapy (RT) plans for head & neck (H&N) and prostate cancer. Pinnacle 8.0 system was used to measure the change of Electron Density (ED) of the tissue for CM. To determine the effect of dose calculation due to CM, we did the RT planning for 30 patients. To compare the ED and dose calculations of RT plans, 3D CRT and IMRT plans were do with pinnacle and Tomotherapy planning system. Mean difference of ED between enhanced and unenhanced CT was less than 4%: H&N Target Volume (TV) 2.1%, parotid 1.9%, SMG 3.6%, tongue 0.9%, spinal cord 0.3%, esophagus 2.6%, mandible 0.1% and prostate TV 0.7%, lymph node 1.1%, bladder 1.2%, rectum 1.5%, small bowel 1.2%, colon 0.6%, penile bulb 0.8%, femoral head -0.2%. The dose difference between RT plan using CM and without CM showed an increase of dose in TV. The rate of increase was less than 2.5% (3D CRT: H&N 0.69~2.51%, prostate 0.04~1.14%, IMRT: H&N 0.58~1.31%, prostate 0.36~1.04%). RT plans using a CM has the insignificant effect on the organs and TV, so this error is allowable clinically. However, the much more accurate plan is possible as to image fusion (CM and without CM images) to ROI contour and when dose calculation, use the without CM image. Using the fusion of 'ROI import' perform calculations on without CM, it will be able to reduce the error (1~3%) caused by the CM.

• Radiation Oncology Journal
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• v.28 no.3
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• pp.166-176
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• 2010

Purpose: To determine the appropriate prostate planning target volume (PTV) margins for 3-dimensitional (3D) conformal radiotherapy (CRT) and intensity-modulated radiation therapy (IMRT) patients treated with an endorectal balloon (ERB) under our institutional treatment condition. Materials and Methods: Patients were treated in the supine position. An ERB was inserted into the rectum with 70 cc air prior to planning a CT scan and then each treatment fraction. Electronic portal images (EPIs) and digital reconstructed radiographs (DRR) of planning CT images were used to evaluate inter-fractional patient's setup and ERB errors. To register both image sets, we developed an in-house program written in visual $C^{++}$. A new method to determine prostate PTV margins with an ERB was developed by using the common method. Results: The mean value of patient setup errors was within 1 mm in all directions. The ERB inter-fractional errors in the superior-inferior (SI) and anterior-posterior (AP) directions were larger than in the left-right (LR) direction. The calculated 1D symmetric PTV margins were 3.0 mm, 8.2 mm, and 8.5 mm for 3D CRT and 4.1 mm, 7.9 mm, and 10.3 mm for IMRT in LR, SI, and AP, respectively according to the new method including ERB random errors. Conclusion: The ERB random error contributes to the deformation of the prostate, which affects the original treatment planning. Thus, a new PTV margin method includes dose blurring effects of ERB. The correction of ERB systematic error is a prerequisite since the new method only accounts for ERB random error.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.41-52
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• 2020

Purpose: To find out the dosimetric usefulness, setup reproducibility and efficiency of applying 3D Bolus by comparing two treatment plans in which Commercial Bolus and 3D Bolus produced by 3D Printing Technology were applied to the neck during VMAT treatment of Hypopahrynx Cancer to evaluate the clinical applicability. Materials and Methods: Based on the CT image of the RANDO phantom to which CB was applied, 3D Bolus were fabricated in the same form. 3D Bolus was printed with a polyurethane acrylate resin with a density of 1.2g/㎤ through the SLA technique using OMG SLA 660 Printer and MaterializeMagics software. Based on two CT images using CB and 3D Bolus, a treatment plan was established assuming VMAT treatment of Hypopharynx Cancer. CBCT images were obtained for each of the two established treatment plans 18 times, and the treatment efficiency was evaluated by measuring the setup time each time. Based on the obtained CBCT image, the adaptive plan was performed through Pinnacle, a computerized treatment planning system, to evaluate target, normal organ dose evaluation, and changes in bolus volume. Results: The setup time for each treatment plan was reduced by an average of 28 sec in the 3D Bolus treatment plan compared to the CB treatment plan. The Bolus Volume change during the pretreatment period was 86.1±2.70㎤ in 83.9㎤ of CB Initial Plan and 99.8±0.46㎤ in 92.2㎤ of 3D Bolus Initial Plan. The change in CTV Min Value was 167.4±19.38cGy in CB Initial Plan 191.6cGy and 149.5±18.27cGy in 3D Bolus Initial Plan 167.3cGy. The change in CTV Mean Value was 228.3±0.38cGy in CB Initial Plan 227.1cGy and 227.7±0.30cGy in 3D Bolus Initial Plan 225.9cGy. The change in PTV Min Value was 74.9±19.47cGy in CB Initial Plan 128.5cGy and 83.2±12.92cGy in 3D Bolus Initial Plan 139.9cGy. The change in PTV Mean Value was 226.2±0.83cGy in CB Initial Plan 225.4cGy and 225.8±0.33cGy in 3D Bolus Initial Plan 224.1cGy. The maximum value for the normal organ spinal cord was the same as 135.6cGy on average each time. Conclusion: From the experimental results of this paper, it was found that the application of 3D Bolus to the irregular body surface is more dosimetrically useful than the application of Commercial Bolus, and the setup reproducibility and efficiency are excellent. If further case studies along with research on the diversity of 3D printing materials are conducted in the future, the application of 3D Bolus in the field of radiation therapy is expected to proceed more actively.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.1-16
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• 2002

Purpose : Three dimensional conformal radiotherapy planning is being used widely for the treatment of patients with brain tumor. However, it takes much time to develop an optimal treatment plan, therefore, it is difficult to apply this technique to all patients. To increase the efficiency of this technique, we need to develop standard radiotherapy plant for each site of the brain. Therefore we developed several 3 dimensional conformal radiotherapy plans (3D plans) for tumors at each site of brain, compared them with each other, and with 2 dimensional radiotherapy plans. Finally model plans for each site of the brain were decide. Materials and Methods : Imaginary tumors, with sizes commonly observed in the clinic, were designed for each site of the brain and drawn on CT images. The planning target volumes (PTVs) were as follows; temporal $tumor-5.7\times8.2\times7.6\;cm$, suprasellar $tumor-3\times4\times4.1\;cm$, thalamic $tumor-3.1\times5.9\times3.7\;cm$, frontoparietal $tumor-5.5\times7\times5.5\;cm$, and occipitoparietal $tumor-5\times5.5\times5\;cm$. Plans using paralled opposed 2 portals and/or 3 portals including fronto-vertex and 2 lateral fields were developed manually as the conventional 2D plans, and 3D noncoplanar conformal plans were developed using beam's eye view and the automatic block drawing tool. Total tumor dose was 54 Gy for a suprasellar tumor, 59.4 Gy and 72 Gy for the other tumors. All dose plans (including 2D plans) were calculated using 3D plan software. Developed plans were compared with each other using dose-volume histograms (DVH), normal tissue complication probabilities (NTCP) and variable dose statistic values (minimum, maximum and mean dose, D5, V83, V85 and V95). Finally a best radiotherapy plan for each site of brain was selected. Results : 1) Temporal tumor; NTCPs and DVHs of the normal tissue of all 3D plans were superior to 2D plans and this trend was more definite when total dose was escalated to 72 Gy (NTCPs of normal brain 2D $plans:27\%,\;8\%\rightarrow\;3D\;plans:1\%,\;1\%$). Various dose statistic values did not show any consistent trend. A 3D plan using 3 noncoplanar portals was selected as a model radiotherapy plan. 2) Suprasellar tumor; NTCPs of all 3D plans and 2D plans did not show significant difference because the total dose of this tumor was only 54 Gy. DVHs of normal brain and brainstem were significantly different for different plans. D5, V85, V95 and mean values showed some consistent trend that was compatible with DVH. All 3D plans were superior to 2D plans even when 3 portals (fronto-vertex and 2 lateral fields) were used for 2D plans. A 3D plan using 7 portals was worse than plans using fewer portals. A 3D plan using 5 noncoplanar portals was selected as a model plan. 3) Thalamic tumor; NTCPs of all 3D plans were lower than the 2D plans when the total dose was elevated to 72 Gy. DVHs of normal tissues showed similar results. V83, V85, V95 showed some consistent differences between plans but not between 3D plans. 3D plans using 5 noncoplanar portals were selected as a model plan. 4) Parietal (fronto- and occipito-) tumors; all NTCPs of the normal brain in 3D plans were lower than in 2D plans. DVH also showed the same results. V83, V85, V95 showed consistent trends with NTCP and DVH. 3D plans using 5 portals for frontoparietal tumor and 6 portals for occipitoparietal tumor were selected as model plans. Conclusion : NTCP and DVH showed reasonable differences between plans and were through to be useful for comparing plans. All 3D plans were superior to 2D plans. Best 3D plans were selected for tumors in each site of brain using NTCP, DVH and finally by the planner's decision.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5259-5264
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• 2014

Background: CT based brachytherapy allows 3-dimensional (3D) assessment of organs at risk (OAR) doses with dose volume histograms (DVHs). The purpose of this study was to compare computed tomography (CT) based volumetric calculations and International Commission on Radiation Units and Measurements (ICRU) reference-point estimates of radiation doses to the bladder and rectum in patients with carcinoma of the cervix treated with high-dose-rate (HDR) intracavitary brachytherapy (ICBT). Materials and Methods: Between March 2011 and May 2012, 20 patients were treated with 55 fractions of brachytherapy using tandem and ovoids and underwent post-implant CT scans. The external beam radiotherapy (EBRT) dose was 48.6Gy in 27 fractions. HDR brachytherapy was delivered to a dose of 21 Gy in three fractions. The ICRU bladder and rectum point doses along with 4 additional rectal points were recorded. The maximum dose ($D_{Max}$) to rectum was the highest recorded dose at one of these five points. Using the HDRplus 2.6 brachyhtherapy treatment planning system, the bladder and rectum were retrospectively contoured on the 55 CT datasets. The DVHs for rectum and bladder were calculated and the minimum doses to the highest irradiated 2cc area of rectum and bladder were recorded ($D_{2cc}$) for all individual fractions. The mean $D_{2cc}$ of rectum was compared to the means of ICRU rectal point and rectal $D_{Max}$ using the Student's t-test. The mean $D_{2cc}$ of bladder was compared with the mean ICRU bladder point using the same statistical test. The total dose, combining EBRT and HDR brachytherapy, were biologically normalized to the conventional 2 Gy/fraction using the linear-quadratic model. (${\alpha}/{\beta}$ value of 10 Gy for target, 3 Gy for organs at risk). Results: The total prescribed dose was $77.5Gy{\alpha}/{\beta}10$. The mean dose to the rectum was $4.58{\pm}1.22Gy$ for $D_{2cc}$, $3.76{\pm}0.65Gy$ at $D_{ICRU}$ and $4.75{\pm}1.01Gy$ at $D_{Max}$. The mean rectal $D_{2cc}$ dose differed significantly from the mean dose calculated at the ICRU reference point (p<0.005); the mean difference was 0.82 Gy (0.48-1.19Gy). The mean EQD2 was $68.52{\pm}7.24Gy_{{\alpha}/{\beta}3}$ for $D_{2cc}$, $61.71{\pm}2.77Gy_{{\alpha}/{\beta}3}$ at $D_{ICRU}$ and $69.24{\pm}6.02Gy_{{\alpha}/{\beta}3}$ at $D_{Max}$. The mean ratio of $D_{2cc}$ rectum to $D_{ICRU}$ rectum was 1.25 and the mean ratio of $D_{2cc}$ rectum to $D_{Max}$ rectum was 0.98 for all individual fractions. The mean dose to the bladder was $6.00{\pm}1.90Gy$ for $D_{2cc}$ and $5.10{\pm}2.03Gy$ at $D_{ICRU}$. However, the mean $D_{2cc}$ dose did not differ significantly from the mean dose calculated at the ICRU reference point (p=0.307); the mean difference was 0.90 Gy (0.49-1.25Gy). The mean EQD2 was $81.85{\pm}13.03Gy_{{\alpha}/{\beta}3}$ for $D_{2cc}$ and $74.11{\pm}19.39Gy_{{\alpha}/{\beta}3}$ at $D_{ICRU}$. The mean ratio of $D_{2cc}$ bladder to $D_{ICRU}$ bladder was 1.24. In the majority of applications, the maximum dose point was not the ICRU point. On average, the rectum received 77% and bladder received 92% of the prescribed dose. Conclusions: OARs doses assessed by DVH criteria were higher than ICRU point doses. Our data suggest that the estimated dose to the ICRU bladder point may be a reasonable surrogate for the $D_{2cc}$ and rectal $D_{Max}$ for $D_{2cc}$. However, the dose to the ICRU rectal point does not appear to be a reasonable surrogate for the $D_{2cc}$.

• Radiation Oncology Journal
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• v.27 no.4
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• pp.228-239
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• 2009

Purpose: 4DCT scans performed for radiotherapy were retrospectively analyzed to assess the possible benefits of respiratory gating in non-small cell lung cancer (NSCLC) and established the predictive factors for identifying patients who could benefit from this approach. Materials and Methods: Three treatment planning was performed for 15 patients with stage I~III NSCLC using different planning target volumes (PTVs) as follows: 1) PTVroutine, derived from the addition of conventional uniform margins to gross tumor volume (GTV) of a single bin, 2) PTVall phases (patient-specific PTV), derived from the composite GTV of all 6 bins of the 4DCT, and 3) PTVgating, derived from the composite GTV of 3 consecutive bins at end-exhalation. Results: The reductions in PTV were 43.2% and 9.5%, respectively, for the PTVall phases vs. PTVroutine and PTVgating vs. PTVall phases. Compared to PTVroutine, the use of PTVall phases and PTVgating reduced the mean lung dose (MLD) by 18.1% and 21.6%, and $V_{20}$ by 18.2% and 22.0%, respectively. Significant correlations were seen between certain predictive factors selected from the tumor mobility and volume analysis, such as the 3D mobility vector, the reduction in 3D mobility and PTV with gating, and the ratio of GTV overlap between 2 extreme bins and additional reductions in both MLD and $V_{20}$ with gating. Conclusion: The additional benefits with gating compared to the use of patient-specific PTV were modest; however, there were distinct correlations and differences according to the predictive factors. Therefore, these predictive factors might be useful for identifying patients who could benefit from respiratory-gated radiotherapy.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.51-57
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• 2014

Purpose : In the case of treating pancreatic cancer, the importance is put on the spread of dose. Changes take place in duodenum in accordance with respiration. Thus, in this paper, I am going to trace the positioning of duodenum and the changes in bulks of body per dose by scanning the patients' Kilovoltage Cone-Beam CT using the hospital equipped CT-on rail System. Materials and Methods : Seeing three patients, I have acquired KVCBCT by using CT-on rail System and spotted the change in positioning at duodenum after comparing with the preliminary image of treatment plan by using SYNGO Software. Then, I followed the change in the bulk of duodenum and analyzed the changes in bulks of body on the same dose by transmitting the acquired KVCBCT into Pinnacle, a treatment plan system. Results : The changes in the positioning shall be as set forth like this: 1.2cm, 1.0cm in Left-Right Direction, 0cm, 0.8cm in Craniocaudal Direction, 0.1cm, and 1.0cm in Anterior-Posterior Direction. Patient number one showed that his bulks in body had increased by maximum 460%, minimum 120%, the bulks in patient number two had increased bymaximum 490%, minimum 160%, and the bulks of patient number three had increased by maximum 150%. But Minimum volume decreased 30%. Patient number one showed only a little bit of change at first when compared with the preliminary treatment plan. However, the dose increased the bulks in the patient's body: $V_{10}$ 118%, $V_{20}$ 117%, $V_{30}$ 400%, and $V_{40}$ 480% Conclusion : In treating patients with radiation therapy using 3D-CRT, the dose amount penetrated into duodenum needs to be minimized by planning appropriate treatment beforehand. In order to establish an appropriate treatment plan it is required to comprehend the changes at positioning of the duodenum by respiration and predict the changes in the bulks of duodenum by setting precise Planning Target Volume.

• Progress in Medical Physics
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• v.25 no.4
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• pp.199-204
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• 2014

The purpose of this study is to evaluate the dosimetric outcome of the field-in-field (FIF) plans compared with tangential wedged beams (TWB) plans for whole breast irradiation of breast cancer patients. Twenty patients with right-sided breast cancer and 10 patients with left-sided breast cancer were retrospectively enrolled in this study. We generated a FIF plan and a TWB plan for each patient to compare dosimetric outcomes. The dose the homogeneity index (HI), the conformity index (CI) and the uniformity index (UI) were defined and used for comparison of the dosimetric outcome of the planning target volume (PTV). To compare the dosimetric outcome of the organs at risk, the mean dose ($D_{mean}$) and the percentage of volumes receiving more than 10, 20 and 30 Gy of the ipsilateral lung and heart were used. The FIF plans had significantly lower HI (p=0.002), higher UI (p=0.000) and CI (p=0.000) than those of the TWB plans, which means that the FIF plans were better than the TWB plans in the dosimetric comparisons of the PTV. The $V10_{lung}$ ($17.1{\pm}7.1$ vs. $18.6{\pm}6.6%$, p=0.020) and $V30_{lung}$ ($10.3{\pm}5.1%$ vs. $10.7{\pm}5.2%$, p=0.000) were lower with the FIF plans compared with those of the TWB plans, with statistical significance. For the left-sided breast cancer patients, $D_{mean}$ of the heart ($2.6{\pm}1.3$ vs. $3.2{\pm}1.4$ Gy, p=0.000), $V20_{heart}$ ($3.4{\pm}2.6$ vs. $3.6{\pm}2.8%$, p=0.005) and $V30_{heart}$ ($2.6{\pm}2.3%$ vs. $2.9{\pm}2.4%$, p=0.004) were significantly lower for the FIF plans in comparison with those of the TWB plans. The FIF plans increased the dose homogeneity, conformity and uniformity of the target volume for the whole-breast irradiation compared with the TWB plans. Moreover, FIF plans reduced the doses to the ipsilateral lung and heart.

• Journal of Radiation Protection and Research
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• v.32 no.3
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• pp.105-110
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• 2007

Purpose : In spite of recent remarkable improvement of diagnostic imaging modalities such as CT, MRI, and PET and radiation therapy planing systems, ICR plan of uterine cervix cancer, based on recommendation of ICRU38(2D film-based) such as Point A, is still used widely. A 3-dimensional ICR plan based on CT image provides dose-volume histogram(DVH) information of the tumor and normal tissue. In this study, we compared tumor-dose, rectal-dose and bladder-dose through an analysis of DVH between CTV plan and ICRU38 plan based on CT image. Method and Material : We analyzed 11 patients with a cervix cancer who received the ICR of Ir-192 HDR. After 40Gy of external beam radiation therapy, ICR plan was established using PLATO(Nucletron) v.14.2 planing system. CT scan was done to all the patients using CT-simulator(Ultra Z, Philips). We contoured CTV, rectum and bladder on the CT image and established CTV plan which delivers the 100% dose to CTV and ICRU plan which delivers the 100% dose to the point A. Result : The volume$(average{\pm}SD)$ of CTV, rectum and bladder in all of 11 patients is $21.8{\pm}6.6cm^3,\;60.9{\pm}25.0cm^3,\;111.6{\pm}40.1cm^3$ respectively. The volume covered by 100% isodose curve is $126.7{\pm}18.9cm^3$ in ICRU plan and $98.2{\pm}74.5cm^3$ in CTV plan(p=0.0001), respectively. In (On) ICRU planning, $22.0cm^3$ of CTV volume was not covered by 100% isodose curve in one patient whose residual tumor size is greater than 4cm, while more than 100% dose was irradiated unnecessarily to the normal organ of $62.2{\pm}4.8cm^3$ other than the tumor in the remaining 10 patients with a residual tumor less than 4cm in size. Bladder dose recommended by ICRU 38 was $90.1{\pm}21.3%$ and $68.7{\pm}26.6%$ in ICRU plan and in CTV plan respectively(p=0.001) while rectal dose recommended by ICRU 38 was $86.4{\pm}18.3%$ and $76.9{\pm}15.6%$ in ICRU plan and in CTV plan, respectively(p=0.08). Bladder and rectum maximum dose was $137.2{\pm}50.1%,\;101.1{\pm}41.8%$ in ICRU plan and $107.6{\pm}47.9%,\;86.9{\pm}30.8%$ in CTV plan, respectively. Therefore, the radiation dose to normal organ was lower in CTV plan than in ICRU plan. But the normal tissue dose was remarkably higher than a recommended dose in CTV plan in one patient whose residual tumor size was greater than 4cm. The volume of rectum receiving more than 80% isodose (V80rec) was $1.8{\pm}2.4cm^3$ in ICRU plan and $0.7{\pm}1.0cm^3$ in CTV plan(p=0.02). The volume of bladder receiving more than 80% isodose(V80bla) was $12.2{\pm}8.9cm^3$ in ICRU plan and $3.5{\pm}4.1cm^3$ in CTV plan(p=0.005). According to these parameters, CTV plan could also save more normal tissue compared to ICRU38 plan. Conclusion : An unnecessary excessive radiation dose is irradiated to normal tissues within 100% isodose area in the traditional ICRU plan in case of a small size of cervix cancer, but if we use CTV plan based on CT image, the normal tissue dose could be reduced remarkably without a compromise of tumor dose. However, in a large tumor case, we need more research on an effective 3D-planing to reduce the normal tissue dose.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.