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Organs at Risk

Organs at Risk (OAR) refer to the healthy tissues and organs that are located near a tumor or treatment area and may be inadvertently exposed to radiation or other therapies during cancer treatment.
Identifying and minimizing radiation exposure to these critical structures is essential for reducing treatment-related toxicities and improving patient outcomes.
PubCompare.ai's AI-driven platform empowers researchers to optimize protocols for OARs, enabling them to locate, compare, and identify the best protocols and products from literature, pre-prints, and patents.
This enhanced reproducibility and accuracy can lead to more effective and safer cancer treatment strategies.

Most cited protocols related to «Organs at Risk»

1
Comparison of Dose Calculation Methods
Cited 10 times
The five calculations described in the Material and Methods Section C above were exported in DICOM format. The dose and volume data for PTV and organs at risk (OAR) listed in Table 2 were extracted from the DICOM files for the five plans, respectively, using the in‐house MATLAB (The MathWorks, Natick, MA) code and the computational environment for radiotherapy research (CERR)(20) software.
Based on parameters listed in Table 2, the following metrics were derived to evaluate the differences and relations among the five calculations:

R(Dx)2,1: Ratio of Dx of PTV between two calculations defined as Dxplan2Dxplan1, where Dx represents the dose to x percent of the PTV and x was 1%, 95%, or 99%. We compared the quantity [R(Dx)2,1−1] which represented the percentage difference between two calculations;

Percentage of cases in which the difference in D95 of PTV between two calculations was more than 7%. The 7% dose difference was chosen since it might be detectable from clinical outcomes;(21) and

Correlation of mean lung dose (MLD) and V20 of lungs between two calculations.

Comparisons between MCHete* and PBHomo were of great interest since the calculations with MC and heterogeneity correction in MCHete* gave the actual planned doses, which may have been different from the dose given by PB calculations without heterogeneity correction.
To study the tumor location dependence of the dose differences between MC and PB calculations, all lesions were separately grouped based on the distance between the GTV contours to the chest wall. A lesion was considered as an edge case if the distance was smaller than 1 cm; otherwise, it was considered as an island lesion, as shown in Fig. 2. The comparisons were conducted separately for the two types of lesions.†
Zhuang T., Djemil T., Qi P., Magnelli A., Stephans K., Videtic G, & Xia P. (2013). Dose calculation differences between Monte Carlo and pencil beam depend on the tumor locations and volumes for lung stereotactic body radiation therapy. Journal of Applied Clinical Medical Physics, 14(2), 38-51.
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Publication 2013
Genetic Heterogeneity Lung Neoplasms by Site Organs at Risk Radiotherapy Wall, Chest
2
Knowledge-Based Optimization Engine for Eclipse TPS
Cited 7 times
A new optimization engine was introduced in the Eclipse TPS (Varian Medical Systems, Palo Alto, USA) in the release 13.5. This is made of three main components: a model building and training engine; a model-based dose-volume histogram (DVH) and automated constraints prediction tool; a new VMAT and IMRT optimization algorithm to manage the above.
The sequence of main steps necessary to generate a model is as follows:

Selection of a set of training plans. No specific requirements are mandatory to be candidate for training. The strategy adopted was to create a “universal” model for HCC and the only requirement was to select plans accepted for clinical treatment.

Association of these plans to a model layout where target and organs at risk ontology, dose prescriptions and some descriptive elements can be defined.

Definition of the type of constraints to be generated per each structure (points vs. lines, priorities, user defined vs. fully automated).

Dosimetric and geometrical data extraction from the patient database to the model engine.

Model training. Based on principal component (PC) analysis methods [2 (link),3 (link),15 ,16 (link)].

Model publication and validation.

Figure 1 shows a schematic representation of the model determination steps and of the PC method applied to DVH. The assumption is that any DVH can be represented as a combination of the average DVH over a population plus a sum of some weighted PC and a residual. The first PC is determined by maximizing the variance of the training set it can explain; any consecutive PC is chosen so that the residual variance is further accounted for. The features used to build the model primarily include geometric characteristic of the various structures, as well as their mutual position and their relationships with the treatment fields. These are modeled by constructing a Geometry-Based Expected Dose (GED) which evaluates the distance between each structure and the target surface by means of the amount of dose that each target contributes to an organ for the current field geometry. The final prediction model is built as a combination of the PC and regression techniques for the in-field region of any OAR and a mean and standard deviation model on the DVH fo the other OAR regions. The PC is applied to the GED and DVH to find the main component scores.

A schematic representation of the model determination steps and of the PC method applied to DVH.

A trained model, once made “public”, can be used to perform predictive estimation of the DVHs for any given new test case and, from these, to determine the planning constraints. The DVH prediction workflow is described as:

Selection of a knowledge-based model

Matching of structure names if the ontology mapping is not complete

Prediction of a range of possible DVH for each of the structures present in both the plan and the model.

Automatic generation of the dose-volume constraints based on the rules from the model configuration. With a fully automatic procedure, these are located below the lower limit of a prediction range generated from the most probable DVH curve by adding and subtracting a variation curve. This corresponds to 1 standard deviation for the out-of-field region. For the in-field region this is constructed by adding in quadrature the DVH PC multiplied by the standard error related to the model regression. Also the priorities are defined by the prediction engine and account for a basic balance between all possible trade-offs. All point constraints and priorities can be modified during optimization.

Figure 2 exemplifies the resulting model-based predictive objectives with the estimate range and automatic objectives (line objectives in this example).

Examples of the model-based predictive objectives with the estimate range and automatic objectives (line objectives in this example).

Fogliata A., Wang P.M., Belosi F., Clivio A., Nicolini G., Vanetti E, & Cozzi L. (2014). Assessment of a model based optimization engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer. Radiation Oncology (London, England), 9, 236.
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Publication 2014
Organs at Risk Patients Prescriptions Prognosis Radiometry Radiotherapy, Intensity-Modulated Volumetric-Modulated Arc Therapy
3
Measurement of Out-of-Field Radiation Doses
Cited 6 times
TLD measurements of absorbed dose were made in the anthropomorphic
phantom to determine the out-of-field stray radiation dose relative to the
in-field therapeutic radiation dose. The linear accelerators used in this study
were calibrated according to the American Association of Physicists in Medicine
Task Group 51 calibration protocol (Almond
et al 1999) by a medical physicist certified by
the American Board of Radiology. Additionally, the outputs of the linear
accelerators were verified to within 2% on the days of phantom irradiation. In
the measurement at MD Anderson, there were 72 TLD locations in organs and
tissues throughout the phantom outside of the field or near the field edge. In
the measurement at AUBMC, there were 209 TLD locations: 184 were in organs and
tissues throughout the phantom outside of the field or near the field edge, 20
were attached to the surface of the phantom to measure skin dose, 3 were at
in-field calculation points to verify delivery of the prescribed dose, and 2
were kept outside of the treatment room to quantify background radiation at the
facility. A list that maps the TLD locations to organs at risk for
radiation-induced cancer was provided by the phantom manufacturer, which
included brain, eyes, thyroid, bone marrow, esophagus, thymus, breasts, lungs,
liver, pancreas, gall bladder, spleen, stomach, kidneys, adrenals, intestine,
prostate, bladder, and testicles.
The dosimeters were composed of lithium fluoride TLD-100 powder capsules
(Quantaflux Radiological Services, San Jose, California). This TLD is suitable
for measuring out-of-field photon dose in 6-MV radiotherapy (Kry et al 2007 (link), Scarboro et al 2010 (link)). The
TLDs were calibrated and read by certified technicians at the Radiological
Physics Center (MD Anderson, Houston, Texas), which includes an accredited
dosimetry calibration laboratory.
The absorbed doses at all TLD locations were collected from the TLD
measurements and from the TPS calculations at points corresponding to the TLD
locations and compared. The values of D were reported relative
to the prescribed therapeutic dose of 30.6 Gy, or
D/DRx (in cGy/Gy), for the
treatment plan.
The overall uncertainty of the absorbed dose measured by each in-field
TLD was 2.5% (Kirby et al1992). We assumed the uncertainty in the in-field dose calculation
would be approximately 2% on the basis of validation measurements obtained at
the time of commissioning of each linear accelerator. We did not account for the
possibility of systematic uncertainty in the absorbed dose measured by each
outof-field TLD because of the non-uniformity of photon spectral fluence in that
region (see section 4), however, we would estimate this uncertainty to be less
than 12% (Kry et al2006, Olko et al2006, Scarboro et al2011). No information about the uncertainty in the out-of-field dose
calculations by the TPSs was available from the manufacturers.
Taddei P.J., Jalbout W., Howell R.M., Khater N., Geara F., Homann K, & Newhauser W.D. (2013). Analytical model for out-of-field dose in photon craniospinal irradiation. Physics in medicine and biology, 58(21), 7463-7479.
Publication 2013
Acute Tubulointerstitial Nephritis Adrenal Glands Background Radiation Bone Marrow Brain Breast Caffeine Capsule Esophagus Eye Gallbladder Intestines Kidney Linear Accelerators lithium fluoride Liver Lung Malignant Neoplasms Microtubule-Associated Proteins Obstetric Delivery Organs at Risk Pancreas Powder Prostate Radiation Radiotherapy Skin Spleen Stomach Testis Therapeutics Thymus Plant Thyroid Gland Urinary Bladder X-Rays, Diagnostic
4
Multimodal Imaging-Guided IMRT for Prostate Cancer
Cited 6 times
EBRT treatment utilized CT simulation in the same supine treatment position as the MRI, with the two scans aligned using mutual information registration, as previously described [16 (link)]. The target and prostatic substructure volumes, including the proximal and distal prostatic urethra, combined transitional and central zones (TZ-CZ), peripheral zone, any apparent prostate lesions, and the GU diaphragm, were defined primarily based on the MRI. The proximal prostatic urethra was defined as the portion of prostatic urethra extending superiorly from the bladder to the inferior-most aspect of the TZ-CZ/peripheral zone border, while the distal prostatic urethra was defined from the TZ-CZ/peripheral zone border superiorly to the prostate/pelvic floor border inferiorly (Figure 1). Defined organs at risk (OARs) were defined primarily with CT information, and included the bladder, rectum, GU diaphragm, femoral heads, and penile bulb. The rectum was defined from the bottom of the ischial tuberosities inferiorly to the sacral prominence superiorly. For S-IMRT, the planning target volume (PTV) the MRI-defined prostate volume expanded by 3 mm. The PTV was prescribed 75.85 Gy in 41 fractions. PTV optimization constraints included mean dose of 100% ± 3% of the prescription dose, minimum dose ≥ 93% of the prescription dose to ≥ 0.5 cc, and maximum dose (Dmax) ≤ 115% of the prescription dose (to ≥ 0.5 cc). IMRT optimization constraints for OARs were based on those used in RTOG P-0126 (http://www.rtog.org/ClinicalTrials/ProtocolTable/StudyDetails.aspx?study=0126), and included the following: for bladder, V80Gy ≤ 15%, V75Gy ≤ 25%, V70Gy ≤ 35%, and V65Gy ≤ 50%; for rectum, V75Gy ≤ 15%, V70Gy ≤ 25%, V65Gy ≤ 35%, and V60Gy ≤ 50%; for GU diaphragm, mean dose ≤ 65 Gy and maximum dose ≤115% of mean dose (to 0.5 cc); for femoral heads, mean dose ≤ 50 Gy and V52 Gy ≤ 10%; for penile bulb, mean dose ≤ 52.5 Gy and V70Gy ≤ 15%.
For US-IMRT, the PTV was the MRI-defined prostatic peripheral zone expanded uniformly by 3–5 mm, depending on clinical assessment of each case. The MRI-defined prostatic substructures were expanded uniformly by 3 mm to account for organ motion and setup uncertainties. The prescription dose and optimization goals for US-IMRT planning were the same as for S-IMRT; additional prostatic substructure OAR constraints for the proximal prostatic urethra were mean dose ≤65 Gy and Dmax to at least 0.5 cc ≤115% of mean dose, and for the distal prostatic urethra were mean dose ≤74 Gy and Dmax to at least 0.5 cc ≤115% of mean dose. During treatment, daily pre-treatment orthogonal imaging was used with re-positioning for variations of ≥ 3 mm. Patients were seen at least weekly during radiation therapy with documentation of treatment tolerance and prescription medications recorded.
Vainshtein J., Abu-Isa E., Olson K.B., Ray M.E., Sandler H.M., Normolle D., Litzenberg D.W., Masi K., Pan C, & Hamstra D.A. (2012). Randomized phase II trial of urethral sparing intensity modulated radiation therapy in low-risk prostate cancer: implications for focal therapy. Radiation Oncology (London, England), 7, 82.
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Publication 2012
CC-115 Femur Heads Immune Tolerance Ischium Medulla Oblongata Organs at Risk Patients Pelvic Diaphragm Penis Prescription Drugs Prostate Radionuclide Imaging Radiotherapy Radiotherapy, Intensity-Modulated Rectum Sacrum Urethra Urinary Bladder Vaginal Diaphragm Vision
5
Dosimetric Comparison of 3DCRT, IMRT, and RapidArc for Liver Cancer
Cited 5 times
In our study, we prescribed 95% of total dose to cover ≥ 95% of the PTV coverage in daily 1.8-Gy fractions while keeping the minimum dose ≥ 93% of total dose and maximum dose ≤ 107% of total dose and normalized all plans to the mean dose of PTV. The guidelines for dose prescription were as follows. When the normal liver volume irradiated with > 50% of the isocenter dose was < 25%, 25-50%, or 50-75%, the total dose prescribed was > 59.4 Gy, 45-54 Gy, and 41.4 Gy, respectively [19 (link)]. No patient received whole liver irradiation. The constraints for the organs at risk (OARs), can be seen in Table 1. These were imposed in terms of the TD5/5 to ensure that the maximal tolerated doses to the normal liver, stomach, kidneys, and spinal cord were not exceeded [11 (link)]. Six-or 10-MV photon beams were used, depending on the tumor location, and the same energy was used for each patient and for all three methods.
For each patient, three different plans (3DCRT, IMRT, and RapidArc) were calculated using the Eclipse planning system with the 120-leaf multi-leaf collimator (MLC) (Varian Medical Systems). For the 3DCRT and IMRT plans, all the gantry angles and numbers of radiation fields (range, 4-5) were manually selected on the basis of the morphological relationship between the PTV and OARs to cover at least 95% of the PTV and spare the OARs. A dose rate of 400 MU/min was used. For RapidArc, the plans were optimized using the two-arc technique with gantry angle running counterclockwise from 179° to 181° and clockwise from 181° to 179° and with the dose rate varied between 0 MU/min and 600 MU/min (upper limit). The optimization constraints for OARs using RapidArc were the same as the constraints in Table 1.
Kuo Y.C., Chiu Y.M., Shih W.P., Yu H.W., Chen C.W., Wong P.F., Lin W.C, & Hwang J.J. (2011). Volumetric intensity-modulated Arc (RapidArc) therapy for primary hepatocellular carcinoma: comparison with intensity-modulated radiotherapy and 3-D conformal radiotherapy. Radiation Oncology (London, England), 6, 76.
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Publication 2011
Infantile Neuroaxonal Dystrophy Kidney Liver Neoplasms by Site Organs at Risk Patients Plant Leaves Radiotherapy Radiotherapy, Conformal Radiotherapy, Intensity-Modulated Spinal Cord Stomach Vision

Most recents protocols related to «Organs at Risk»

1
Cardiac Substructure Contouring and Radiation Planning
In Step 2 (Figure 1, Right panel), an electrophysiologist and radiation oncologist collaborated to select target areas based on the combined 17-segment model that was created in Step 1. Regions suspected to be the substrates or foci were designated as ON (red), unselected regions were designated as OFF (green), and organs at risk of failure were designated as OAR (yellow). OARs must be considered, including cardiac substructures (e.g., coronary arteries, valves, papillary muscles, and stimulatory conduction systems) and surrounding organs (e.g., the stomach wall, ribs, esophagus, trachea, and spinal cord). For the tentative target, the medical physicists used radiotherapy planning software (Eclipse ver. 13.7; Varian Medical Systems Inc., Palo Alto, CA, USA) to contour the cardiac substructures and target volume.16 (link)
In step 3, the irradiation volume and the dose distribution was estimated using an algorithm of Acuros XB (Varian Medical Systems Inc.). Adjustments were required if the dose calculation for critical organs exceeded the constraint. Targeting and contouring are mutually repeated many times to improve the accuracy of the treatment plan and to determine the final irradiated area. Considering heart rate and respiratory variability, as well as rotational errors,17 (link) a margin of 2–5 mm was expanded to the clinical target volume (CTV), defined as the internal target volume and planning target volume (PTV). The amount for the PTV should be <100 mL, based on a previous report (mean 98.9 mL, range 60.9–298.8 mL).3 (link)
Amino M., Kabuki S., Kunieda E., Hashimoto J., Sugawara A., Sakai T., Sakama S., Ayabe K., Ohno Y., Yagishita A., Kobayashi Y., Ikari Y, & Yoshioka K. (2023). Interim Report of a Japanese Phase II Trial for Cardiac Stereotactic Body Radiotherapy in Refractory Ventricular Tachycardia　― Focus on Target Determination ―. Circulation Reports, 5(3), 69-79.
Publication 2023
Artery, Coronary Esophagus Heart Organs at Risk Papillary Muscles Radiation Oncologists Rate, Heart Respiratory Rate Ribs Spinal Cord Stomach Systems, Heart Conduction Trachea
2
SBRT for Lung Tumor Treatment
Patients were simulated using CT imaging with both 3D and 4D scans to account for respiratory motion. Photon (x-ray) beams with photon energies of 6 MV were used. All patients received a simulation CT scan used to contour the gross tumor volume (GTV). No margin was added for clinical target volume (CTV). GTV were defined either on MIP (Maximum Intensity Projection) images or using GTVs at 3 phases (inspiration, expiration and midphase) of the respiratory cycle to create an ITV. An additional 0.5 cm in the axial plane and 0.5 to 1.0 cm in the longitudinal plane (craniocaudal) was added to the each GTV to create the planning target volume (PTV).
SBRT dose/fractionation treatment regimens ranged from 34 to 54 Gy in 1 to 10 fractions using photons. The treatment goals were 54 Gy in 3 fractions for peripheral lesions and 50 Gy in 5 fractions central lesions. Treatment dose and fractionation was per physician discretion and was adjusted based on tumor size, location, organs at risk, patient comorbidities, and prior treatment. Per protocol, treatments delivered with > 10 Gy per fraction had a minimum of 48-h interfraction interval. Treatments with ≤ 10 Gy per fraction had a minimum 24-h interfraction interval. Treatments were completed over 14 days for 3 fraction treatments and over 21 days for > 5 fraction treatment schedules.
Local recurrence (LR) was assessed radiographically and was defined as tumor recurrence or increased size of the treated tumor, based on Response Evaluation Criteria in Solid Tumors (RECIST) criteria on CT imaging, within the radiation PTV [10 (link)]. Time to LR was measured from the end of SBRT to the time of tumor recurrence or last follow up. Local progression-free survival was defined as the time from end of SBRT to the time of LR. Overall survival (OS) was measured from the end of radiation to the time of death.
Adverse radiation events due to SBRT were graded based on the Common Terminology Criteria for Adverse Events, version 4.0.
Gutkin P.M., Gore E., Charlson J., Neilson J.C., Johnstone C., King D.M., Hackbarth D.A., Wooldridge A., Mannem R, & Bedi M. (2023). Stereotactic body radiotherapy for metastatic sarcoma to the lung: adding to the arsenal of local therapy. Radiation Oncology (London, England), 18, 42.
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Publication 2023
Inhalation Neoplasms Organs at Risk Patients Physicians Radiography Radionuclide Imaging Radiotherapy Radiotherapy Dose Fractionations Recurrence Respiratory Rate Treatment Protocols X-Ray Computed Tomography
3
SBRT for Prostate Cancer with Fiducial Tracking
For treatment planning purposes, four gold fiducial markers were inserted into the prostate gland. One week later, a computed tomography (CT) scan was performed (slice thickness, 2 mm) followed by T2-weighted magnetic resonance imaging (MRI). The CT and MRI images were then fused for treatment planning. The clinical target volume (CTV) was defined by the prostate capsule and the proximal seminal vesicles. The planning target volume (PTV) was created by expanding the CTV margins by 3 mm posteriorly and 5 mm in all other directions. The following structures were contoured as organs at risk (OAR): rectum, bladder, penile bulb, and both femurs. The prostatic urethra was not included as an OAR because the prescription isodose line was limited to ≥75% to restrict the maximum dose to 125% of the prescription dose. SBRT was delivered to patients using the CyberKnife robotic radiosurgery system (Accuray Inc., Sunnyvale, CA, USA). Fiducial-based tracking was used to account for inter- and intra-fraction prostate motion.
A total dose of 35 or 36.25 Gy to the PTV was delivered in five fractions of 7.0 or 7.25 Gy. Before simulation (planning CT and MRI) and prior to each SBRT fraction, patients were instructed to drink approximately 500 mL of water 20–30 min before the session to fill their bladder to a comfortable level. They were also instructed to present with an empty rectum.
Milecki P., Adamska A., Rucinska A., Pałucki G., Szumiło A., Skrobała A., Jodda A, & Michalak M. (2023). Large Prostate Volume Does Not Negatively Impact Health-Related Quality of Life in Patients with Prostate Cancer Treated with Ultrahypofractionated Stereotactic Body Radiotherapy. Journal of Personalized Medicine, 13(2), 233.
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Publication 2023
Capsule CyberKnife Radiosurgery Femur Fiducial Markers Gold Medulla Oblongata Organs at Risk Patients Penis Prostate Radionuclide Imaging Rectum Seminal Vesicles Urethra Urinary Bladder X-Ray Computed Tomography
4
SBRT for Unidentified Lesions via VMAT/IMRT
Patients underwent CT simulation in a supine position with a slide of 2.5 mm. All patients were immobilized using a vacuum-assisted body mold to recreate exact positioning during daily sessions. Target lesion was not readily identified on the CT simulation, and the planning data set was registered to a diagnostic contrast CT or PET-CT, using a mutual information algorithm from our in-house treatment system, to facilitate gross tumor volume (GTV) delineation. A 3–8 mm isotropic expansion was generated from GTV to obtain planning target volume (PTV). Organs at risk (OARs) were delineated depending on the target lesion location without margins. The treatment planning system was Eclipse 4.5.5 (Varian), and VMAT/IMRT technique on a 6-MV linear accelerator Varian were used for treatment. The dose of SBRT was converted to the biologically effective dose (BED) to compare different dose-fractionation schedules. The BED was calculated using the linear-quadratic model with α/β = 10 Gy for the tumor and α/β = 3 to the organs at risk. Dose schedules were chosen with the aim of delivering ablative treatments respecting dose constraints for OARs.
Facondo G., Vullo G., De Sanctis V., Rotondi M., Sigillo R.C., Valeriani M, & Osti M.F. (2023). Clinical Outcomes of Stereotactic Body Radiotherapy (SBRT) for Oligometastatic Patients with Lymph Node Metastases from Gynecological Cancers. Journal of Personalized Medicine, 13(2), 229.
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Publication 2023
Diagnosis Fungus, Filamentous Human Body Linear Accelerators Neoplasms Organs at Risk Patients Radiotherapy, Intensity-Modulated Radiotherapy Dose Fractionations Scan, CT PET Vacuum Volumetric-Modulated Arc Therapy
5
Stereotactic Body Radiotherapy for Liver Tumors

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Publication 2023
Arm, Upper CAT SCANNERS X RAY Cone-Beam Computed Tomography Fiducial Markers Fluoroscopy Gold Head Liver Neoplasms Neoplasms by Site Obstetric Delivery Organs at Risk Patients Radiography Radiometry Radiotherapy Respiratory Rate Spinal Cord STEEP1 protein, human Vacuum X-Ray Computed Tomography X-Rays, Diagnostic

Top products related to «Organs at Risk»

1
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2
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The Eclipse TPS is a compact and versatile lab equipment designed for a range of analytical applications. It features a temperature-controlled sample compartment and can accommodate various sample holders and accessories. The Eclipse TPS provides precise temperature control and monitoring capabilities to ensure accurate and consistent results during sample analysis.
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More about "Organs at Risk"

Organs at Risk (OAR) are the healthy tissues and structures located near a tumor or treatment area that may be inadvertently exposed to radiation or other therapies during cancer treatment.
Minimizing radiation exposure to these critical structures is essential for reducing treatment-related toxicities and improving patient outcomes.
OARs can include organs such as the heart, lungs, kidneys, liver, spinal cord, and more, depending on the tumor location and treatment modality.
The Eclipse treatment planning system, Brilliance CT Big Bore, and LightSpeed RT16 are examples of imaging and treatment planning technologies that can be used to identify and contour OARs.
The Eclipse TPS and Brilliance CT Big Bore Oncology Configuration, as well as the RayStation planning system and Pinnacle3 (Pinnacle treatment planning system), offer advanced tools for OAR delineation, dose optimization, and plan evaluation.
By utilizing AI-driven platforms like PubCompare.ai, researchers can optimize protocols for OARs by locating, comparing, and identifying the best protocols and products from literature, pre-prints, and patents.
This enhanced reproducibility and accuracy can lead to more effective and safer cancer treatment strategies, ultimately improving patient outcomes.
In addition to the aforementioned technologies, Eclipse version 8.6 also provides features for OAR management and dose optimization.
Overall, the careful consideration and protection of Organs at Risk is a critical component of modern cancer treatment planning and delivery.