Assessment and clinical validation of margins for adaptive simultaneous integrated boost in neo-adjuvant radiochemotherapy for rectal cancer

PurposeAn adaptive concomitant boost (ACB) for the neo-adjuvant treatment of rectal cancer was clinically implemented. In this study population margins M(90,90) considering rectal deformation were derived for 10 consecutive patients treated at 18 × 2.3 Gy with Helical Tomotherapy (HT) and prospectively validated on 20 additional patients treated with HT, delivering ACB in the last 6 fractions.MethodsSectorial margins M(90,90) of the whole and second treatment parts were assessed for 90% population through a method combining the 90% coverage probability maps of rectal positions (CPC90%) with 3D local distance measurements between the CPC90% and a reference rectal contour. M(90,90) were compared with the margins M(90,90)^95%/99%, ensuring CPC90% coverage with 95%/99% confidence level. M(90,90) of the treatment second part were chosen as ACB margins which were clinically validated for each patient by means of %volume missing of CPC5/6 excluded by the ACB margins.ResultsThe whole treatment M(90,90) ranged between 1.9 mm and 9 mm in the lower-posterior and upper-anterior sectors, respectively. Regarding ACB, M(90,90) were 7 mm in the anterior direction and <5 mm elsewhere. M(90,90)^95%/99% did not significantly differ from M(90,90). The %volume excluded by the ACB margin was<2% for all male and <5% for 9/10 female patients. The dosimetry impact on R_adapt for the patients with the largest residual error was negligible.ConclusionsLocal deformation measurements confirm an anisotropic motion of rectum once set-up error is rigidly corrected. Margins of 7 mm anterior and 5 mm elsewhere are adequate for ACB. Female patients show a slightly larger residual error.     

Novel knowledge-based treatment planning model for hypofractionated radiotherapy of prostate cancer patients

PurposeTo demonstrate the strength of an innovative knowledge-based model-building method for radiotherapy planning using hypofractionated, multi-target prostate patients.Material and methodsAn initial RapidPlan model was trained using 48 patients who received 60 Gy to prostate (PTV60) and 44 Gy to pelvic nodes (PTV44) in 20 fractions. To improve the model's goodness-of-fit, an intermediate model was generated using the dose-volume histograms of best-spared organs-at-risk (OARs) of the initial model. Using the intermediate model and manual tweaking, all 48 cases were re-planned. The final model, trained using these re-plans, was validated on 50 additional patients. The validated final model was used to determine any planning advantage of using three arcs instead of two on 16 VMAT cases and tested on 25 additional cases to determine efficacy for single-PTV (PTV60-only) treatment planning.ResultsFor model validation, PTV V_95% of 99.9% was obtained by both clinical and knowledge-based planning. D_1% was lower for model plans: by 1.23 Gy (PTV60, CI = [1.00, 1.45]), and by 2.44 Gy (PTV44, CI = [1.72, 3.16]). OAR sparing was superior for knowledge-based planning: ΔD_mean = 3.70 Gy (bladder, CI = [2.83, 4.57]), and 3.22 Gy (rectum, CI = [2.48, 3.95]); ΔD_2% = 1.17 Gy (bowel bag, CI = [0.64, 1.69]), and 4.78 Gy (femoral heads, CI = [3.90, 5.66]). Using three arcs instead of two, improvements in OAR sparing and PTV coverage were statistically significant, but of magnitudes < 1 Gy. The model failed at reliable DVH predictions for single PTV plans.ConclusionsOur knowledge-based model delivers efficient, consistent plans with excellent PTV coverage and improved OAR sparing compared to clinical plans.     

Automatic VMAT planning for post-operative prostate cancer cases using particle swarm optimization: A proof of concept study

ObjectiveTo investigate the potential of Particle Swarm Optimization (PSO) for fully automatic VMAT radiotherapy (RT) treatment planning.Material and MethodsIn PSO a solution space of planning constraints is searched for the best possible RT plan in an iterative, statistical method, optimizing a population of candidate solutions. To identify the best candidate solution and for final evaluation a plan quality score (PQS), based on dose volume histogram (DVH) parameters, was introduced.Automatic PSO-based RT planning was used for N = 10 postoperative prostate cancer cases, retrospectively taken from our clinical database, with a prescribed dose of EUD = 66 Gy in addition to two constraints for rectum and one for bladder. Resulting PSO-based plans were compared dosimetrically to manually generated VMAT plans.ResultsPSO successfully proposed treatment plans comparable to manually optimized ones in 9/10 cases. The median (range) PTV EUD was 65.4 Gy (64.7–66.0) for manual and 65.3 Gy (62.5–65.5) for PSO plans, respectively. However PSO plans achieved significantly lower doses in rectum D_2% 67.0 Gy (66.5–67.5) vs. 66.1 Gy (64.7–66.5, p = 0.016). All other evaluated parameters (PTV D_98% and D_2%, rectum V_40Gy and V_60Gy, bladder D_2% and V_60Gy) were comparable in both plans. Manual plans had lower PQS compared to PSO plans with −0.82 (−16.43–1.08) vs. 0.91 (−5.98–6.25).ConclusionPSO allows for fully automatic generation of VMAT plans with plan quality comparable to manually optimized plans. However, before clinical implementation further research is needed concerning further adaptation of PSO-specific parameters and the refinement of the PQS.     

Assessing the need for adaptive radiotherapy in head and neck cancer patients using an automatic planning tool

BackgroundUnbiased analysis of the impact of adaptive radiotherapy (ART) is necessary to evaluate dosimetric benefit and optimize clinics’ workflows. The aim of the study was to assess the need for adaptive radiotherapy (ART) in head and neck (H&N) cancer patients using an automatic planning tool in a retrospective planning study.Materials and methodsThirty H&N patients treated with adaptive radiotherapy were analysed. Patients had a CT scan for treatment planning and a verification CT during treatment according to the clinic’s protocol. Considering these images, three plans were retrospectively generated using the iCycle tool to simulate the scenarios with and without adaptation: 1) the optimized plan based on the planning CT; 2) the optimized plan based on the verification CT (ART-plan); 3) the plan obtained by considering treatment plan 1 re-calculated in the verification CT (non-ART plan). The dosimetric endpoints for both target volumes and OAR were compared between scenarios 2 and 3 and the SPIDERplan used to evaluate plan quality.ResultsThe most significant impact of ART was found for the PTVs, which demonstrated decreased D98% in the non-ART plan. A general increase in the dose was observed for the OAR but only the spinal cord showed a statistical significance. The SPIDERplan analysis indicated an overall loss of plan quality in the absence of ART.ConclusionThese results confirm the advantages of ART in H&N patients, especially for the coverage of target volumes. The usage of an automatic planning tool reduces planner-induced bias in the results, guaranteeing that the observed changes derive from the application of ART.     

Current treatment of rectal cancer adapted to the individual patient

Preoperative radiochemotherapy and total mesorectal excision surgery is a recommended standard therapy for patients with locally advanced rectal cancer. However, some subgroups of patients benefit more than others from this approach. In order to avoid long-term complications of radiation and chemotherapy, efforts are being made to subdivide T3N0 stage using advanced imaging techniques, and to analyze prognostic factors that help to define subgroup risk patients. Long-course radiochemotherapy has the potential of downsizing the tumor before surgery and may increase the chance of sphincter preservation in some patients. Short-course radiotherapy (SCRT), on the other hand, is a practical schedule that better suits patients with intermediated risk tumors, located far from the anal margin. SCRT is also increasingly being used among patients with disseminated disease, before resection of the rectal tumor. Improvements in radiation technique, such as keeping the irradiation target below S2/S3 junction, and the use of IMRT, can reduce the toxicity associated with radiation, specially long-term small bowel toxicity.     

Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study

BackgroundThe aim of this study was to investigate the performance of the RapidPlan (RP ) using models registered pseudostructures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer.Materials and methodsPseudo-structures around the PTV were retrospectively contoured for patients who had completed treatment at five institutions. For 22 common patients, plans were generated with a single optimization for models with two (RP_2), four (RP_4), and five (RP_5) registered structures, and the dosimetric parameters of these models were compared with a clinical plan with several optimizations.ResultsMost dosimetric parameters showed no major differences between each RP model. In particular, the rectum D_max, V_50Gy, and V_40Gy with RP_2, RP_4, and RP_5 were not significantly different, and were lower than those of the clinical plan. The average proportions of plans achieving acceptable criteria for dosimetric parameters were close to 100% for all models. Using RP_2, the average time for the VMAT planning was reduced by 88 minutes compared with the clinical plan.ConclusionThe RapidPlan model with two registered pseudo-structures could generate clinically acceptable plans while saving time.     

A new split arc VMAT technique for lymph node positive breast cancer

PurposeTo investigate different volumetric modulated arc therapy (VMAT) field designs for lymph node positive breast cancer patients when compared to conventional static fields and standard VMAT designs.MethodsNineteen breast cancer patients with lymph node involvement (eleven left and eight right sided) were retrospectively analyzed with different arc designs. Proposed split arc designs with total rotations of 2 × 190° and 2 × 240° were compared to conventional field in field (FinF) and previously published non-split arc techniques with the same amount of total rotations.ResultsAll VMAT plans were superior in dose conformity, when compared to the FinF plans. Split arc design decreased significantly ipsilateral lung dose and heart V5Gy for both left and right sided cases, when compared to non-split VMAT designs. For left sided cases no significant differences were seen in contralateral lung mean dose or V5Gy between different VMAT designs. For right sided cases the contralateral lung dose V5Gy was significantly higher in split VMAT group, when compared to non-split VMAT designs. The contralateral breast dose V5Gy increased significantly for split VMAT plans for both sides, when compared to non-split VMAT designs or FinF plans.ConclusionsThe proposed split VMAT technique was shown to be superior to previously published non-split VMAT and conventional FinF techniques significantly reducing dose to the ipsilateral lung and heart. However, this came with the expense of an increase in the dose to the contralateral breast and for right-sided cases to the contralateral lung.     

Characterization of robust optimization for VMAT plan for liver cancer

PurposeWe investigated the feasibility of robust optimization for volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) for liver cancer in comparison with planning target volume (PTV)-based optimized plans. Treatment plan quality, robustness, complexity, and accuracy of dose delivery were assessed.MethodsTen liver cancer patients were selected for this study. PTV-based optimized plans with an 8-mm PTV margin and robust optimized plans with an 8-mm setup uncertainty were generated. Plan perturbed doses were evaluated using a setup error of 8 mm in all directions from the isocenter. The dosimetric comparison parameters were clinical target volume (CTV) doses (D_98%, D_50%, and D_2%), liver doses, and monitor unit (MU). Plan complexity was evaluated using the modulation complexity score for VMAT (MCSv).ResultsThere was no significant difference between the two optimizations with respect to CTV doses and MUs. Robust optimized plans had a higher liver dose than did PTV-based optimized plans. Plan perturbed dose evaluations showed that doses to the CTV for the robust optimized plans had small variations. Robust optimized plans were less complex than PTV-based optimized plans. Robust optimized plans had statistically significant fewer leaf position errors than did PTV-based optimized plans.ConclusionsComparison of treatment plan quality, robustness, and plan complexity of both optimizations showed that robust optimization could be feasibile for VMAT of liver cancer.     

Techniques for adaptive prostate radiotherapy

Variations in the position and shape of the prostate make accurate setup and treatment challenging. Adaptive radiation therapy (ART) techniques seek to alter the treatment plan, at one or more points throughout the treatment course, in response to changes in patient anatomy observed between planning and pre-treatment images. This article reviews existing and developing ART techniques for prostate cancer along with an overview of supporting in-room imaging technologies. Challenges to the clinical implementation of adaptive radiotherapy are also discussed.     

Implementation of automatic plan optimization in Italy: Status and perspectives

PurposeTo investigate and report on the diffusion and clinical use of automated radiotherapy planning systems in Italy and to assess the perspectives of the community of Italian medical physicists involved in radiotherapy on the use of these tools.Materials and MethodsA survey of medical physicists (one per Institute) of 175 radiotherapy centers in Italy was conducted between February 21st and April 1st, 2021. The information collected included the institute’s characteristics, plan activity, availability/use of automatic tools and related issues regarding satisfaction, criticisms, expectations, and perceived professional modifications. Responses were analysed, including the impact of a few variables such as the institute type and experience.Results125 of the centers (71%) answered the survey, with regional variability (range: 47%–100%); among these, 49% have a TPS with some automatic option. Clinical use of automatic planning is present in 33% of the centers, with 13% applying it in >50% of their plans.Among the 125 responding centres the most used systems are Pinnacle (16%), Raystation (9%) and Eclipse (4%). The majority of participants consider the use of automated techniques to be beneficial, while only 1% do not see any advantage; 83% of respondents see the possibility of enriching their professional role as a potential benefit, while 3% see potential threats.ConclusionsOur survey shows that 49% of the responding centres have an automatic planning solution although clinically used in only 33% of the cases. Most physicists consider the use of automated techniques to be beneficial and show a prevalently positive attitude.     

Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer

PurposeThis study evaluated whether RapidPlan based plans (RP plans) created by a single optimization, are usable in volumetric modulated arc therapy (VMAT) for patients with prostate cancer.MethodsWe used 51 previously administered VMAT plans to train a RP model. Thirty RP plans were created by a single optimization without planner intervention during optimization. Differences between RP plans and clinical manual optimization (CMO) plans created by an experienced planner for the same patients were analyzed (Wilcoxon tests) in terms of homogeneity index (HI), conformation number (CN), D_95%, and D_2% to planning target volume (PTV), mean dose, V_50Gy, V_70Gy, V_75Gy, and V_78Gy to rectum and bladder, monitor unit (MU), and multi-leaf collimator (MLC) sequence complexity.ResultsRP and CMO values for PTV D_95%, PTV D_2%, HI, and CN were significantly similar (p < 0.05 for all). RP mean dose, V_50Gy, and V_70Gy to rectum were superior or comparable to CMO values; RP V_75Gy and V_78Gy were higher than in CMO plans (p < 0.05). RP bladder dose-volume parameter values (except V_78Gy) were lower than in CMO plans (p < 0.05). MU values were RP: 730 ± 55 MU and CMO: 580 ± 37 MU (p < 0.05); and MLC sequence complexity scores were RP: 0.25 ± 0.02 and CMO: 0.35 ± 0.03 (p < 0.05).ConclusionsRP plans created by a single optimization were clinically acceptable in VMAT for patient with prostate cancer. Our simple model could reduce optimization time, independently of planner’s skill and knowledge.     

A perspective on the current treatment strategies for locally advanced rectal cancer

The introduction of total mesorectal excision (TME) and preoperative multimodality treatment have substantially improved the management of rectal cancer reducing local recurrence and increasing sphincter-saving surgery; distant metastases however remain a clinical challenge. Besides, although surgery remains the mainstay for cure of rectal cancer with the multimodality approach (chemotherapy, radiotherapy and surgery) being the standard of care for the majority of rectal cancer patients, there is a need of individualized risk-adapted treatment schemes based on clinico-pathological features because of treatment-induced morbidity and quality of life deterioration. This short viewpoint describes the emerging strategies addressing all these issues.     

Performance evaluation of TRIBES, an adaptive particle swarm optimization algorithm

This paper presents a study of the performance of TRIBES, an adaptive particle swarm optimization algorithm. Particle Swarm Optimization (PSO) is a biologically-inspired optimization method. Recently, researchers have used it effectively in solving various optimization problems. However, like most optimization heuristics, PSO suffers from the drawback of being greatly influenced by the selection of its parameter values. Thus, the common belief is that the performance of a PSO algorithm is directly related to the tuning of such parameters. Usually, such tuning is a lengthy, time consuming and delicate process. A new adaptive PSO algorithm called TRIBES avoids manual tuning by defining adaptation rules which aim at automatically changing the particles’ behaviors as well as the topology of the swarm. In TRIBES, the topology is changed according to the swarm behavior and the strategies of displacement are chosen according to the performances of the particles. A comparative study carried out on a large set of benchmark functions shows that the performance of TRIBES is quite competitive compared to most other similar PSO algorithms that need manual tuning of parameters. The performance evaluation of TRIBES follows the testing procedure introduced during the 2005 IEEE Conference on Evolutionary Computation. The main objective of the present paper is to perform a global study of the behavior of TRIBES under several conditions, in order to determine strengths and drawbacks of this adaptive algorithm.     

Fully automatic and robust segmentation of the clinical target volume for radiotherapy of breast cancer using big data and deep learning

PurposeTo train and evaluate a very deep dilated residual network (DD-ResNet) for fast and consistent auto-segmentation of the clinical target volume (CTV) for breast cancer (BC) radiotherapy with big data.MethodsDD-ResNet was an end-to-end model enabling fast training and testing. We used big data comprising 800 patients who underwent breast-conserving therapy for evaluation. The CTV were validated by experienced radiation oncologists. We performed a fivefold cross-validation to test the performance of the model. The segmentation accuracy was quantified by the Dice similarity coefficient (DSC) and the Hausdorff distance (HD). The performance of the proposed model was evaluated against two different deep learning models: deep dilated convolutional neural network (DDCNN) and deep deconvolutional neural network (DDNN).ResultsMean DSC values of DD-ResNet (0.91 and 0.91) were higher than the other two networks (DDCNN: 0.85 and 0.85; DDNN: 0.88 and 0.87) for both right-sided and left-sided BC. It also has smaller mean HD values of 10.5 mm and 10.7 mm compared with DDCNN (15.1 mm and 15.6 mm) and DDNN (13.5 mm and 14.1 mm). Mean segmentation time was 4 s, 21 s and 15 s per patient with DDCNN, DDNN and DD-ResNet, respectively. The DD-ResNet was also superior with regard to results in the literature.ConclusionsThe proposed method could segment the CTV accurately with acceptable time consumption. It was invariant to the body size and shape of patients and could improve the consistency of target delineation and streamline radiotherapy workflows.     

Total neoadjuvant treatment in locally advanced rectal cancer

Locally advanced rectal cancer requires a multidisciplinary management, traditionally based on neo-adjuvant (chemo) radiotherapy, conservative surgery with total mesorectal excision and adjuvant chemotherapy. Despite effective in term of local control, this strategy is linked to a high risk of distant metastasis (up to 30%). In this context, recent published randomized phase III clinical trials have tested the potential benefits with a different sequencing and/or intensification of the standard components of the trimodal therapy.Here, we briefly assess the efficacy and discuss the clinical relevance of total neoadjuvant treatment with a focus on indications and results in the short-course radiotherapy followed by chemotherapy use for this setting of patients. Long term results and additional prospective studies are necessary to more accurately estimate the clinical benefit and further establish the role of total neoadjuvant therapy in locally advanced rectal cancer disease.     

Postoperative radio-chemotherapy for rectal cancer: A retrospective analysis from a tertiary referral hospital

AimTo report results of postoperative radio-chemotherapy (RT-CHT) for rectal cancer (RC).BackgroundTotal mesorectal excision (TME) is an essential treatment method in rectal cancer (RC). Perioperative radiotherapy in locally advanced RC improves loco-regional free survival (LRFS). Preoperative radiotherapy is a preferred option; however, some patients are not referred for it. In case of the risk of loco-regional failure postoperative radio-chemotherapy (RT-CHT) is indicated.Material and methodsBetween 2004 and 2010, 182 patients with pathological stage II-III RC (TME performed — 41%, resection R0 — 88%, circumferential resection margin evaluated — 55.5% and was above 2 mm in 66% of them) received postoperative RT-CHT in our institution. Overall survival (OS) and LRFS were estimated with the Kaplan–Meier method. Univariate and multivariate analysis were performed to compare the impact of prognostic factors on survival.ResultsFive-year OS and LRFS rates were 63% and 85%, respectively. Loco-regional recurrence and isolated distant metastases rates were 11.5% and 19%, respectively. Multivariate analysis showed stage (III vs. II), HR: 2.3 (95% confidence interval [CI]: 1.4–3.8), p = 0.0001; extent of resection (R1−2 vs. R0), HR: 2.14 (95%CI: 1.14–3.99), p = 0.017, and age (>65 vs. ≤65 years), HR: 1.66 (95%CI: 1.06–2.61), p = 0.027 as prognostic factors for OS. Extent of resection (R1−2 vs. R0), HR: 3.65 (95%CI: 1.41–9.43), p = 0.008 had significant impact on LRFS.ConclusionDespite a suboptimal quality of surgery and pathological reports, the outcome in our series is close to that reported in the literature. We confirm a strong impact of the extent of resection on patient’s outcome, which confirms the pivotal role of surgery in the management of RC.     

Prediction of multi-criteria optimization (MCO) parameter efficiency in volumetric modulated arc therapy (VMAT) treatment planning using machine learning (ML)

PurposeTo predict the impact of optimization parameter changes on dosimetric plan quality criteria in multi-criteria optimized volumetric-modulated-arc therapy (VMAT) planning prior to optimization using machine learning (ML).MethodsA data base comprising a total of 21,266 VMAT treatment plans for 44 cranial and 18 spinal patient geometries was generated. The underlying optimization algorithm is governed by three highly composite parameters which model a combination of important aspects of the solution. Patient geometries were parametrized via volume- and shape properties of the voxel objects and overlap-volume histograms (OVH) of the planning-target-volume (PTV) and a relevant organ-at-risk (OAR). The impact of changes in one of the three optimization parameters on the maximally achievable value range of five dosimetric properties of the resulting dose distributions was studied. To predict the extent of this impact based on patient geometry, treatment site, and current parameter settings prior to optimization, three different ML-models were trained and tested. Precision-recall curves, as well as the area-under-curve (AUC) of the resulting receiver-operator-characteristic (ROC) curves were analyzed for model assessment.ResultsSuccessful identification of parameter regions resulting in a high variability of dosimetric plan properties depended on the choice of geometry features, the treatment indication and the plan property under investigation. AUC values between 0.82 and 0.99 could be achieved. The best average-precision (AP) values obtained from the corresponding precision/recall curves ranged from 0.71 to 0.99.ConclusionsMachine learning models trained on a database of pre-optimized treatment plans can help finding relevant optimization parameter ranges prior to optimization.     

The robustness of dual isocenter VMAT radiation therapy for bilateral lymph node positive breast cancer

PurposeTo investigate the use of dual isocenters for VMAT planning in patients with lymph node positive synchronous bilateral breast cancer (BBC) compared to a single isocenter option.MethodsTreatment plans of 11 patients with lymph node positive BBC were retrospectively analyzed using two different VMAT planning techniques: dual-isocenter split-arc VMAT plans (Iso2) were compared with mono-isocenter VMAT plans (Iso1). For Iso2 plans, PTV dose was investigated after introducing ±2 and ±5 mm couch shift errors between the two isocenters in the lateral, longitudinal and vertical direction.ResultsFor both techniques the planning aims for PTV coverage and OARs were met. The mean dose for the bilateral lungs and heart was reduced from 11.3 Gy and 3.8 Gy to 10.9 Gy (p < .05) and 3.6 Gy (p < .05), respectively, for Iso2 plans when compared to Iso1 plans. Positive statistically significant correlation (rho = 0.76, p = .006) was found between PTV volume and D2cc_PTV for Iso1 plans. No clinically significant change was seen in the D98_CTV or D2cc_PTV after the 2 and 5 mm errors were introduced between isocenters for Iso2 plans.ConclusionsThe split arc method was shown to be a feasible treatment technique in the case of synchronous BBC for both mono and dual isocenter techniques. The dose parameters were slightly favoring dual-isocenter option instead of mono-isocenter. The dual-isocenter method was shown to be a robust treatment option in the presence of ≤5 mm errors in the shifts between the two isocenters.     

Clinical impact of HLA class I expression in rectal cancer

Purpose To determine the clinical impact of human leukocyte antigen (HLA) class I expression in irradiated and non-irradiated rectal carcinomas. Experimental design Tumor samples in tissue micro array format were collected from 1,135 patients. HLA class I expression was assessed after immunohistochemical staining with two antibodies (HCA2 and HC10). Results Tumors were split into two groups: (1) tumors with >50% of tumor cells expressing HLA class I (high) and (2) tumors with ≤50% of tumor cells expressing HLA class I (low). No difference in distribution or prognosis of HLA class I expression was found between irradiated and non-irradiated patients. Patients with low expression of HLA class I (15% of all patients) showed an independent significantly worse prognosis with regard to overall survival and disease-free survival. HLA class I expression had no effect on cancer-specific survival or recurrence-free survival. Conclusions Down-regulation of HLA class I in rectal cancer is associated with poor prognosis. In contrast to our results, previous reports on HLA class I expression in colorectal cancer described a large population of patients with HLA class I negative tumors, having a good prognosis. This difference might be explained by the fact that a large proportion of HLA negative colon tumors are microsatellite instable (MSI). MSI tumors are associated with a better prognosis than microsatellite stable (MSS). As rectal tumors are mainly MSS, our results suggest that it is both, oncogenic pathway and HLA class I expression, that dictates patient’s prognosis in colorectal cancer. Therefore, to prevent confounding in future prognostic analysis on the impact of HLA expression in colorectal tumors, separate analysis of MSI and MSS tumors should be performed. Frank M. Speetjens and Elza C. de Bruin contributed equally to this work. Cornelis J.H. van de Velde is the Chairperson of the Total Mesorectal Excision Trial.