Patient-specific Set Research Articles

Systematic Study of Patient-Specific Organs at Risk Auto-Segmentation on Daily kVCT Images for Adaptive Head and Neck Radiotherapy

<h3>Purpose/Objective(s)</h3> A newly developed biology-guided radiotherapy (BgRT) system has been set up in our institution, which enables high-quality kVCT imaging for each treatment fraction. This study explored deep learning-based patient-specific auto-segmentation to facilitate adaptive radiotherapy, based on data of the first head and neck patient case treated with this new system. <h3>Materials/Methods</h3> The esophagus, larynx, and pharynx were selected as the organs at risk (OAR) for auto-segmentation analysis. A population network was first learned on a population dataset, which contains 67 different patient cases from conventional intensity-modulated radiotherapy (IMRT). Then the pre-trained population network was adapted to this specific patient using a transfer learning method based on the longitudinal data from the initial treatment planning and 17 sets of daily image guidance kVCT images. The selected OARs were contoured by a radiation oncologist on 18 sets of images as the ground truth. The performance of the patient-specific network was compared with the population network as well as the clinical rigid registration method. The corresponding dosimetric impacts resulting from different segmentation and registration methods were also investigated. <h3>Results</h3> The initial Dice similarity coefficient (DSC) results of the population network on the patient-specific evaluation set were 0.821, 0.537, 0.739 for esophagus, larynx, and pharynx respectively, and they were markedly improved to 0.887, 0.889, 0.850 with the proposed patient-specific network. These results also outperformed the results of 0.670, 0.792, 0.709 with the registration-based method in current clinical practice. The contouring accuracy of the patient-specific network gradually increased with the increase of longitudinal training cases and approached saturation with more than six training cases. The qualification result also shows the population network was adapted to the specific manual contouring style after the patient-specific learning. Discrepancies of the mean doses by using the manual contour and the patient-specific auto-segmentation result were -1.29%, -1.05%, -0.13% for the three OARs respectively, better than the differences of 4.80%, -6.56%, -1.84% using the registration contour. The OAR dose underestimation in some treatment fractions based on the registration contour was markedly improved when using the patient-specific auto-segmentation result. <h3>Conclusion</h3> Auto-segmentation of daily kVCT images was studied based on patient-specific learning to facilitate future adaptive radiotherapy. Compared with the common population network and the clinical registration method, the patient-specific network could achieve a much better contouring and dosimetric accuracy and thus is promising to become a powerful tool in adaptive radiotherapy applications.

FDA-Approved Pharmacotherapy for Weight Loss Over the Last Decade.

Obesity is a recently defined illness whose diagnosis and treatment continue to be stigmatized. Currently, due to lifestyle changes brought on by technological advancements and the wide availability and affordability of high-calorie foods, millions of people around the world suffer from obesity and/or its sequelae. Finding adequate prevention and treatment options would therefore lead to massive improvements in the duration and quality of life of affected individuals. In this review, we searched the PubMed database for studies exploring the safety and efficacy of the five medications currently approved by the FDA for the treatment of obesity. We included only studies pertaining to adult patients that have been published between 2012 and 2022. We found evidence that all the drugs analyzed such as orlistat, phentermine/topiramate, naltrexone/bupropion, liraglutide, and semaglutide appear to be effective in inducing weight loss, with the suggestion that semaglutide may have superior efficacy. However, a massive obstacle in developing treatment guidelines remains the lack of prolonged studies monitoring the long-term safety and efficacy of obesity medications. Nevertheless, in patients at risk of complications from obesity, the benefits of losing fat mass may outweigh the potential side effects associated with these medications and clinicians should prescribe whichever of the FDA-approved pharmacotherapy they deem most appropriate for the patient’s specific set of circumstances.

Central arterial pressure and patient-specific model parameter estimation based on radial pressure measurements

One-dimensional arterial flow simulations are suitable to estimate the aortic pressure from peripheral measurements in a patient-specific arterial network. This study introduces a reduction of the system parameters, and a novel calculation method to estimate the patient-specific set and the aortic curve based on radial applanation tonometry. Peripheral and aortic pressure curves were measured in patients, optimization were carried out. The aortic pressure curves were reproduced well, with an overestimation of the measured Systolic and Mean Blood Pressures on average by 0.6 and 0.5 mmHg respectively, and the Root Mean Square Difference of the curves was 3 mmHg on average.

Energy and sparse coding coefficients as sufficient measures for VEBs classification

This paper proposes an efficient model strategy based on the use of two features, Energy (En) and sparse coding coefficients (non-zero elements, Nze), from sparse representation (SR) modeling to detect the arrhythmia. First, we use a set of labeled QRS complexes for dictionary learning. Each category of heartbeats generates a dictionary. Then, SR modeling is applied to unlabelled QRS complexes and thus based on the previously learned dictionaries. The making decision to select the correct class of heartbeats depends on the low value of the SR modeling attributes (En and Nze). These features go beyond the six intuitive properties (Robin Hood, Scaling, Rising Tide, Cloning, Bill Gates, and Babies) that a good sparsity measure ought to fulfill, such as Pietra/Gini indexes (PI, GI), Hoyer, etc. We validate the performance of our strategy on records, including VEBs, from the MIT-BIH Arrhythmia and the Petersburg Institute of Cardiological Technics (INCART) databases. The experimental results show an overall accuracy of 95.51%, 92.04%, and 79.19% with MIT-BIH and 97.67%, 86.73%, and 96.88% with INCART. These results correspond to three scenarios: patient-specific, cross-validation, and independent set, unseen data, respectively. Results are better or comparable to those obtained by the complex machine learning-based methods. The most relevant issues in the area of SR for classification (SRC) are mainly related to the measure of sparsity using recognized standards. In this study, we use a strategy based on model selection rather than machine learning (ML). Then, features were sufficient measures of sparsity and robust for VEBs detection.

Development and validation of a synthetic 3D-printed simulator for training in neuroendoscopic ventricular lesion removal.

Neuroendoscopic surgery using an ultrasonic aspirator represents a valid tool with which to perform the safe resection of deep-seated ventricular lesions, but the handling of neuroendoscopic instruments is technically challenging, requiring extensive training to achieve a steep learning curve. Simulation-based methods are increasingly used to improve surgical skills, allowing neurosurgical trainees to practice in a risk-free, reproducible environment. The authors introduce a synthetic, patient-specific simulator that enables trainees to develop skills for endoscopic ventricular tumor removal, and they evaluate the model's validity as a training instrument with regard to realism, mechanical proprieties, procedural content, and handling. The authors developed a synthetic simulator based on a patient-specific CT data set. The anatomical features were segmented, and several realistic 1:1 skull models with all relevant ventricular structures were fabricated by a 3D printer. Vascular structures and the choroid plexus were included. A tumor model, composed of polyvinyl alcohol, mimicking a soft-consistency lesion, was secured in different spots of the frontal horn and within the third ventricle. Neurosurgical trainees participating in a neuroendoscopic workshop qualitatively assessed, by means of a feedback survey, the properties of the simulator as a training model that teaches neuroendoscopic ultrasonic ventricular tumor surgery; the trainees rated 10 items according to a 5-point Likert scale. Participants appreciated the model as a valid hands-on training tool for neuroendoscopic ultrasonic aspirator tumor removal, highly rating the procedural content. Furthermore, they mostly agreed on its comparably realistic anatomical and mechanical properties. By the model's first application, the authors were able to recognize possible improvement measures, such as the development of different tumor model textures and the possibility, for the user, of creating a realistic surgical skull approach and neuroendoscopic trajectory. A low-cost, patient-specific, reusable 3D-printed simulator for the training of neuroendoscopic ultrasonic aspirator tumor removal was successfully developed. The simulator is a useful tool for teaching neuroendoscopic techniques and provides support in the development of the required surgical skills.

Process optimization in total knee arthoplasty procedures : Impact of size-specific instrument sets on costs and revenue.

Total knee arthroplasty (TKA) is a frequent operation in Germany and in 2017 a total of 191,272 interventions were carried out. These interventions are associated with high costs and involve complex clinical workflow organization and time-consuming instrument logistics. With this in mind, the aim of this study was to identify the economic potential of the instrument configuration in order to optimize the entire process in TKA. Changing the composition of the set of instruments used in the operating theater for TKA resulted in time and cost saving for the complete TKA procedure, including all personnel and off-shoot procedures. In addition, the operating time saved by the introduction of a patient-specific instrumentation set meant that the operating theater could be used for more or other surgical procedures, also generating additional revenue.

Abstract 736: Development of an allele-specific assay for detecting circulating tumor DNA in prostate cancer

Abstract Background and Hypothesis Cancer cells release circulating tumor DNA (ctDNA) into the bloodstream, which has the potential to be clinically relevant as a marker of tumor clonality and a marker of clinical response. This "liquid biopsy" may provide a non-invasive approach to cancer care diagnosis and monitoring. We have optimized a PCR assay for rapid and inexpensive selection and detection of a priori sequenced targets, serving as clonal and subclonal markers of cancer evolution. Our hypothesis is that this assay will allow us to detect circulating free DNA and ctDNA while modeling tumor clonality and measuring clinical response in patients undergoing treatment for metastatic prostate cancer. Methods From a given panel of somatic point mutations previously identified via unbiased sequencing of matched tumor and normal samples, multiplex PCR primer mixes were generated using the IonTorrent AmpliSeq Design tool, creating locus-specific primers flanking each point mutation by approximately 60bp on each side. To the 5’ end of each forward primer, a 7-base degenerate unique molecular identifier (UMI) was synthesized, to which an additional 32-base sequence complementary to the forward Illumina Nextera adaptor was further added. To the 3’ end of the reverse primer, a 34-base sequence complementary to the reverse Illumina Nextera adaptor was added. Forward primers for each patient-specific set were pooled and hybridized to aliquots of ctDNA extracted from patient plasma. The tagged product was amplified in exponential PCR with the reverse primer pool and a full-length Nextera i7 Indexing primer. Following purification and size selection, the tagged and partial-adaptor-ligated library was amplified in additional exponential cycles of PCR with full length Nextera i5 and i7 indexing primers. Libraries were then quantified and sequenced via MiSeq. Results and Conclusions We have previously shown that for a series of seven patients, primers designed against clonal and subclonal mutations successfully amplified their genomic targets in 269 out of 280 amplicons, averaging 10 amplicons per library and 100,000x target coverage per amplicon. Following duplicate reduction, approximately 1,000 unique molecules were sequenced. Spike-in experiments were utilized to establish the lower limit of reliable detection. This assay is currently being applied to patients with metastatic prostate cancer who had blood drawn across multiple timepoints. We are currently analyzing these samples to model tumor clonality and treatment response across multiple patients. Relevance and Importance We have developed a robust, patient-specific assay for detection of ctDNA and monitoring patients over time. This assay has the potential to provide a patient-specific and non-invasive approach for monitoring treatment and remission of metastatic prostate cancer. Citation Format: Nicholas T. Terrigino, S. Thomas Hennigan, Shana Trostel, Scott C. Wilkinson, Huihui Ye, Adam G. Sowalsky. Development of an allele-specific assay for detecting circulating tumor DNA in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 736.

Liver segmentation from low-radiation-dose pediatric computed tomography using patient-specific, statistical modeling.

The pediatric computed tomography (CT) volume is acquired at a low dose because radiation is harmful to young children. Consequently, the pediatric CT volume has lower signal-to-noise ratio, which makes organ segmentation difficult. In this paper, we propose a liver segmentation algorithm for pediatric CT scan using a patient-specific level set distribution model (LSDM). The patient-specific LSDM was constructed using a conditional LSDM (C-LSDM) conditioned on age. Furthermore, a patient-specific probabilistic atlas (PA) was generated using the model, which became a priori to the maximum a posteriori-based segmentation. The patient-specific PA generation by the C-LSDM using kernel density estimation was quicker than the conventional PA generation method using random numbers, and also, it was more accurate as it did not include any approximations. The liver segmentation algorithm was tested on 42 CT volumes of children aged between 2weeks and 7years. In the proposed method, the calculation time of the PA was about 9s for the single Gaussian method, while it was 337s for the conventional PA generation method using random numbers. Furthermore, using the kernel density estimation, median and 25%/75% tile of the generalized Dice similarity index between the PA and the correct liver region were found to be 0.3443 and 0.3191/0.3595. The Dice similarity index in the segmentation was 0.8821 and 0.8545/0.9085, which are higher than those obtained by the conventional method, and requires lower computational cost. We proposed a method to quickly and accurately generate a PA, combined with C-LSDM using kernel density estimation, which enabled efficient calculation and improved segmentation accuracy.

Enhancing Student Knowledge Through a Comprehensive Oncology Simulation

Objective. To evaluate the impact of a comprehensive oncology simulation on pharmacy students' knowledge and perceptions related to oncology pharmacy practice. Methods. Third-year pharmacy students at the University of South Florida completed an ovarian cancer case-based simulation. Stations involved patient-specific order set completion, counseling, order verification, and aseptic technique. Pre- and post-simulation assessments regarding therapeutic knowledge and aseptic technique as well as perceptions of pharmacists' roles in oncology practice were evaluated. Results. All students (n=109, 100%) completed the pre- and post-simulation assessments. There was an increase in knowledge after the simulation, which was statistically significant in three of the six questions. Furthermore, students' perceptions regarding pharmacist roles and self-confidence in ability to prepare patient-specific regimens increased on a 5-point Likert scale from 3.8 and 3.2 to 4.5 and 4.2 on the post-assessment, respectively. Conclusion. Participation in the simulation improved students' oncology-related knowledge and perceived understanding of the roles of oncology pharmacists.

A novel preventative solution for effective asthma management: a practical evaluation

In recent years, there has been an increased growth in the use of smart applications to better care and manage various medical conditions. Recent studies have concluded that the daily management via an application improves asthma control compared to manual or paper-based monitoring (Fonseca et al. in Allergy 61(3):389–390, 2006). To this effect, this research aims to study existing asthma applications and propose a holistic approach to asthma care and management by developing a novel Android application that provides a real-time, multi-way communication between patients and providers (healthcare, insurance, food, drug, etc.). The current state-of-the-art smart applications are able to aid users send information to their physicians typically via email; however, healthcare providers still need to contact patients through the traditional methods (phone, email, or face-to-face appointments). Our proposed multi-way communication can eliminate phone calls, emails, and appointment scheduling to save time and provide real-time feedback to the patients. Furthermore, providers can monitor the health status of patients remotely by checking their patient specific journal entry and set new and/or modified action plans and also uploads those to the patient’s smart devices. Providers can also send notifications to patients even if the device is in sleep mode. In case of emergency, patients are able to call 911 or find the nearest hospital and pharmacy via a pre-programmed one-click method. We have conducted extensive evaluation studies (both pre- and post) at a nationally recognized HIMSS Stage 6 regional trauma center (>500 beds) and its affiliated 23 associated clinical practices. The results confirm that the proposed solution has a strong potential to significantly improve the quality of care while reducing the overall cost of care delivery for the target population. In addition, the HIMSS 6 organization has availed meaningful use incentive programs due to these measures. We are also aiding the healthcare organization to conduct analysis of their patient data to provide various training seminars to facilitate effective management of this chronic condition. In the upcoming years, our goal is to continue to collaborate with the provider to help in designing proactive solutions for other chronic conditions, such as diabetes, heart disease, obesity, etc.

Abstract LB-275: Precise enumeration of cell-free DNA from patient-derived cell lines

Abstract Cancer cells secrete fragments of their genetic material in the form of cell-free DNA (cfDNA) producing a potential biomarker for following cell growth and drug response. While cfDNA has been popularized as a liquid biopsy analyte for monitoring disease status in patients with metastases, we have also applied cfDNA detection in vitro for following the establishment of patient-derived organoid cancer cell lines. Because the diversity of tumor subtypes in many cancers requires extensive optimization, the combinations of growth factors or other supplements can vary with each culture, even for the same cancer type. This challenging task is complicated further by contamination with normal cells. Historically, determining which condition is optimal for enriching for tumor cell growth required sacrificing at least some portion of the culture for a phenotypic analysis, adding cost and time to replenish the culture. As an alternative, we have developed a robust, sensitive, and patient-specific assay that can be rapidly applied as new culture conditions are optimized, with a priori knowledge of the clonal mutations present in the tumor sample. For a given panel of point mutations, multiplex PCR primers were generated using the IonTorrect AmpliSeq Design tool, creating locus-specific primers flanking each site by approximately 60bp on each side. To the 5’ end of each forward primer, a 7-base degenerate unique molecular identifier (UMI) was synthesized, to which an additional 32-base sequence complimentary to the forward Illumina Nextera adaptor was further added. To the 3’ end of the reverse primer, a 34-base sequence complimentary to the reverse Illumina Nextera adaptor was added. Once the patient-specific primer set is obtained, the total time from sample to result was less than two days. For each patient-specific primer set, the forward primers were pooled and used to tag DNA extracted from the cell culture supernatant of patient-derived cell lines with the adaptor and UMI sequence in a single hybridization and elongation cycle of PCR. Primers were blocked with terminal transferase and removed by spin-column, and the tagged product was amplified in 30 linear PCR cycles with the reverse primer pool. Following purification and size selection, the tagged and partial-adaptor-ligated library was amplified in 35 cycles of PCR with barcoded Illumina adaptors. Libraries were quantified, pooled, and sequenced on a MiSeq. Upon analysis of sequencing data, including the identification of unique template molecules, each template sample produced a number of starting molecules of DNA. With this critical data, we can determine which conditions successfully enriched for the growth of tumor cells and their subsequent release of cfDNA. Citation Format: Sean Hennigan, Shana Trostel, Adam G. Sowalsky. Precise enumeration of cell-free DNA from patient-derived cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-275. doi:10.1158/1538-7445.AM2017-LB-275

Individuality of the plasma sodium concentration

Older literature has suggested that the plasma sodium concentration is not individual, that it is neither intrinsic to an individual nor reproducible, longitudinally. We recently observed that the plasma sodium concentration is heritable. Because demonstrable heritability requires individuality of the relevant phenotype, we hypothesized that the plasma sodium concentration was substantially individual. In two large health plan-based cohorts, we demonstrated individuality of the plasma sodium concentration over a 10-yr interval; the intraclass correlation coefficient (ICC) averaged 0.4-0.5. The individuality of plasma sodium increased significantly with age. Plasma sodium individuality was equal to or only slightly less than that for plasma glucose but was less than the individuality for creatinine. The individuality of plasma sodium was further confirmed by comparing the Pearson correlation coefficient for within-individual versus between-individual pairs of sodium determinations and via application of the agreement index. Furthermore, the distribution of all sodium determinations for all participants within a population was similar to the distribution for the mean sodium concentration for individuals within that population. Therefore, the near-normal distribution of plasma sodium measurements within a population is likely not attributable to assay-specific factors but rather to genuine and durable biological variability in the osmotic set point. In aggregate, these data strongly support the individuality of the plasma sodium concentration. They further indicate that serial plasma sodium values for any given individual tend to cluster around a patient-specific set point and that these set points vary among individuals.

Analysis and algorithmic generation of hepatic vascular systems.

A proper geometric model of the vascular systems in the liver is crucial for modeling blood flow, the connection between the organ and the rest of the organism. In vivo imaging does not provide sufficient details, so an algorithmic concept for extending measured vascular tree data is needed such that geometrically realistic structures can be generated. We develop a quantification of similarity in terms of different geometric features. This involves topological Strahler ordering of the vascular trees, statistical testing, and averaging. Invariant features are identified in human clinical in vivo CT scans. Results of the existing “Constrained Constructive Optimization” algorithm are compared to real vascular tree data. To improve bifurcation angles in the algorithmic results, we implement a postprocessing step calibrated to the measured features. This framework is finally applied to generate realistic additional details in a patient-specific hepatic vascular tree data set.

Announcing a New Open Access Journal: Cell Medicine, Part B of Cell Transplantation.

Cell therapy in medicine elicits equal jubilation and pessimism. The notion that the diseased or aging cell can be replaced with a healthy cell, in particular the use of a pluripotent stem cell, has challenged the dogma of the nonregenerative status of mature cells. To this end, a long list of new stem cell sources has emerged, including those derived from the embryo, fetus, umbilical cord, placenta, amnion, bone marrow, adipose, skin, and menstrual blood. The derivation of a patient-specific set of stem cells is key to the success of cell medicine. However, the inadvertent entry of cell therapy into the clinic in the absence of solid scientific evidence, clinical guidance, and regulatory oversight has seriously hampered the realization of the true potential of cell medicine. Indeed, “stem cell tourism” has become an international business enterprise that has put the patient in unregulated medical treatment (see 2008 Guidelines for the Clinical Translation of Stem Cells, International Society for Stem Cell Research; www.isscr.org/clinical_trans/pdfs/ISSCRGLClinicalTrans.pdf). We recognize the need to expedite the translation of laboratory findings into clinical application, in view of the debilitating and many times fatal human disorders that may benefit from cell medicine. Accordingly, we sought a platform wherein the three important translational research components—namely the academic institution, the biomedical company, and the regulatory agencies—have an equal footing in providing a critical input on the science, as well as the safety and efficacy of this therapy. A careful examination of currently available journals reveals that there exists a limited open access communication among these three translational research components, in that most of the peer-reviewed journals cater to research experiments from the academicians, with an increasing number of studies conducted under a translational theme whereby a collaborative effort between a university and a biomedical company is apparent. In addition, many professional societies, such as the Cell Transplant Society and American Society for Neural Therapy and Repair, have been equally keen in forging ahead with translational medicine, and are yearning for a translational journal that publishes peer-reviewed proceedings and papers arising from their annual meetings. More unfortunate is that many experimental data from the biomedical companies, as well as the clinical guidelines issued by the regulatory agencies, appear as in-house or interagency manifestos. In our desire to advance cell medicine to the clinic, we are launching a new journal Cell Medicine, Part B of Cell Transplantation (the subtitle to reflect that it is from the same stable as Cell Transplanation). Along the line of promoting the theme of translational research, we will build an Editorial Board consisting of academicians, biomedical experts, and regulatory administrators, who are specifically engaged in the science and translation of a cell product emerging from the laboratory to the clinic. Thus, Cell Medicine will allow Cell Transplantation to significantly increase its Editorial Board affiliation. Our overarching goal is to solicit and process, under rigorous, but fair and rapid peer review, those papers on cell therapy with direct clinical relevance. We are aware that translational studies are “milestone-driven” as opposed to routinely “mechanism-driven” experiments; thus, this further distinguishes our journal as we understand the difficulty in getting published in regular journals with strong emphasis on the latter aspect of scientific investigation. Moreover, we propose that an editorial commentary from the assigned handling editor to accompany many outstanding articles in order to outline the next steps necessary for the transition of the study under investigation closer to clinical application. We envision that this unique journal will facilitate the critical evaluation of cell medicine as a safe and an effective treatment for human disorders. Cell Medicine will be an online-only journal, with focused articles on translational research from professional societies as well as collaborations among academia, industry, and/or regulatory agencies. This new initiative is in tandem with the “Open Access” format that was introduced in 2009. Both these changes are driven by our goal to make Cell Transplantation and our new online-only journal Cell Medicine the journals of choice that cater to rapidly changing technology in the dissemination of scientific knowledge and to the current push for translational research in the field of cell transplantation.

MO‐D‐BRB‐03: Using a Database of Patient Geometric and Dosimetric Information for Quantitative IMRT Plan Quality Control

Purpose: To empower IMRT treatment planners with the ability to judge new plans against the performance of similar past plans. Method and Materials: This is accomplished by searching a database of treated patients using the geometric relationships between targets and organs at risk (OARs). We introduce the concept of a shape relationship descriptor to quantify this intuitively important relationship. The overlap volume histogram (OVH) simplifies the complex 3D relationship between a target and an OAR. The OVH is the normalized 1D histogram of the OAR volume within a distance of the target. The OVH descriptor was used to search a patient database, providing a patient specific set of dose volume histograms (DVHs). These DVHs were then presented to the planner to aid their decisions. Results: The method was applied to both parotids of 32 treated head‐and‐neck patients. The 17 parotids that promised the greatest reduction in D50 were selected for re‐planning. These 17 parotids came from 13 patients. Our method indicated that the doses of the other nine parotids of the 13 patients could not be reduced, so they were included in the re‐planning process as controls. Re‐planning with an effort to reduce D50 was conducted on the 26 parotids of these 13 patients. Average reductions of D50 were 6.6Gy for the 17 improvement candidates and 1.9Gy for the controls. Originally, several parotids violated the RTOG planning goal of V(30Gy)⩽50%. Eleven of these were improvement candidates, and re‐planning reduced this number to three. Re‐planning had no impact on the five control parotids that were violating the RTOG planning goal. According to the physician reviews, re‐planning did not degrade target coverage or OAR sparing. Conclusions: Our method offers a patient specific DVH evaluation for OARs, providing an effective mechanism of quantitative IMRT plan quality control.