Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology

Introduction

Artificial intelligence (AI)-based technologies embody countless solutions in radiation oncology, yet translation of AI-assisted software tools to actual clinical environments remains unrealized. We present the Deep Learning On-Demand Assistant (DL-ODA), a fully automated, end-to-end clinical platform that enables AI interventions for any disease site featuring an automated model-training pipeline, auto-segmentations, and QA reporting.

Materials and methods

We developed, tested, and prospectively deployed the DL-ODA system at a large university affiliated hospital center. Medical professionals activate the DL-ODA via two pathways (1): On-Demand, used for immediate AI decision support for a patient-specific treatment plan, and (2) Ambient, in which QA is provided for all daily radiotherapy (RT) plans by comparing DL segmentations with manual delineations and calculating the dosimetric impact. To demonstrate the implementation of a new anatomy segmentation, we used the model-training pipeline to generate a breast segmentation model based on a large clinical dataset. Additionally, the contour QA functionality of existing models was assessed using a retrospective cohort of 3,399 lung and 885 spine RT cases. Ambient QA was performed for various disease sites including spine RT and heart for dosimetric sparing.

Results

Successful training of the breast model was completed in less than a day and resulted in clinically viable whole breast contours. For the retrospective analysis, we evaluated manual-versus-AI similarity for the ten most common structures. The DL-ODA detected high similarities in heart, lung, liver, and kidney delineations but lower for esophagus, trachea, stomach, and small bowel due largely to incomplete manual contouring. The deployed Ambient QAs for heart and spine sites have prospectively processed over 2,500 cases and 230 cases over 9 months and 5 months, respectively, automatically alerting the RT personnel.

Discussion

The DL-ODA capabilities in providing universal AI interventions were demonstrated for On-Demand contour QA, DL segmentations, and automated model training, and confirmed successful integration of the system into a large academic radiotherapy department. The novelty of deploying the DL-ODA as a multi-modal, fully automated end-to-end AI clinical implementation solution marks a significant step towards a generalizable framework that leverages AI to improve the efficiency and reliability of RT systems.

Assessing the Feasibility of Using Artificial Intelligence-Segmented Dominant Intraprostatic Lesion for Focal Intraprostatic Boost With External Beam Radiation Therapy

PURPOSE

The delineation of dominant intraprostatic gross tumor volumes (GTVs) on multiparametric magnetic resonance imaging (mpMRI) can be subject to interobserver variability. We evaluated whether deep learning artificial intelligence (AI)-segmented GTVs can provide a similar degree of intraprostatic boosting with external beam radiation therapy (EBRT) as radiation oncologist (RO)-delineated GTVs.

METHODS AND MATERIALS

We identified 124 patients who underwent mpMRI followed by EBRT between 2010 and 2013. A reference GTV was delineated by an RO and approved by a board-certified radiologist. We trained an AI algorithm for GTV delineation on 89 patients, and tested the algorithm on 35 patients, each with at least 1 PI-RADS (Prostate Imaging Reporting and Data System) 4 or 5 lesion (46 total lesions). We then asked 5 additional ROs to independently delineate GTVs on the test set. We compared lesion detectability and geometric accuracy of the GTVs from AI and 5 ROs against the reference GTV. Then, we generated EBRT plans (77 Gy prostate) that boosted each observer-specific GTV to 95 Gy. We compared reference GTV dose (D98%) across observers using a mixed-effects model.

RESULTS

On a lesion level, AI GTV exhibited a sensitivity of 82.6% and positive predictive value of 86.4%. Respective ranges among the 5 RO GTVs were 84.8% to 95.7% and 95.1% to 100.0%. Among 30 GTVs mutually identified by all observers, no significant differences in Dice coefficient were detected between AI and any of the 5 ROs. Across all patients, only 2 of 5 ROs had a reference GTV D98% that significantly differed from that of AI by 2.56 Gy (P = .02) and 3.20 Gy (P = .003). The presence of false-negative (-5.97 Gy; P < .001) but not false-positive (P = .24) lesions was associated with reference GTV D98%.

CONCLUSIONS

AI-segmented GTVs demonstrate potential for intraprostatic boosting, although the degree of boosting may be adversely affected by false-negative lesions. Prospective review of AI-segmented GTVs remains essential.

An Automated, Dynamic Radiation Oncology Prescription Checking System

PURPOSE

Despite serving as a critical communication tool, radiation oncology prescriptions are entered manually and prone to error. An automated prescription checking system was developed and implemented to help address this problem.

METHODS AND MATERIALS

Rules defining clinically appropriate prescriptions were generated, examining specific types of errors: (1) unapproved dose per fraction for a given disease site; (2) dose per fraction too large for nonstereotactic treatment technique; and (3) dose per fraction too low. With a goal of catching errors as upstream as possible to minimize their propagation, a report was created and ran every 30 minutes to check all newly written or approved prescriptions against the 3 rules. When a prescription violated these rules, an automated email was immediately sent to the prescriber alerting them of the potential error. System performance was continuously monitored and the criteria triggering an alert adjusted to balance error detection against false positives. Alerts leading to prescription amendment were considered true errors.

RESULTS

From June 2021 to November 2022, the system checked 24,047 prescriptions. A total of 241 email alerts were triggered, for an average alert rate of 1%. Of the 241 alerts, 198 (82.2%) were unapproved doses per fraction for the disease site, 14 (5.8%) were doses per fraction that were too low, and 29 (12%) were doses too large for nonstereotactic treatment technique. Thirty-one percent of alerts led to a change of prescription, suggesting they were true errors. The baseline rate of erroneous prescription entry was 0.3%. A regression model showed that trainee prescription entry and dose per fraction <150 cGy were significantly associated with true errors.

CONCLUSIONS

Given the significant consequences of erroneous prescription entry, which ranged from wasted resources and treatment delays to potentially serious misadministration, there is significant value in implementing automated prescription checking systems in radiation oncology clinics.

Prospective Evaluation of Implementation of a Tattoo-less Workflow for Non-Spine Bone SBRT

PURPOSE/OBJECTIVE(S)

Oligometastatic disease has expanded the clinical indications for non-spine bone (NSB) SBRT. Optical surface monitoring systems (OSMS) may reduce treatment time if it represents an effective surrogate for bone intrafraction motion monitoring. We aimed to identify whether OSMS could substitute for 2D-3D mid-imaging and enable a tattoo-less set up in NSB SBRT.

MATERIALS/METHODS

Beginning 11/2019, OSMS was incorporated in parallel with an existing workflow using CBCT and mid 2D-3D kV/kV imaging for pre- and mid-imaging for NSB SBRT. The ability of OSMS to detect both observed out-of-tolerance (>2mm/>2deg) shifts and manual couch shifts was analyzed. A workflow incorporating OSMS reference captures, CBCT for pre-treatment verification and OSMS/triggered imaging (TI) for intrafraction monitoring was developed and deployed for rib/sternum SBRT beginning 11/2021 and all NSB SBRT beginning 2/2022. All NSB SBRT treatment appointments were analyzed through statistical process control (SPC) with use of an XmR chart of average set up and total treatment time per quarter from 2/2019 to 2/2023. Special cause rules were based on IHI rules and conduced with spreadsheet software.

RESULTS

From 2/2019 to 2/2023, 1962 NSB SBRT fractions were delivered, including 337 rib, 150 sternum, 197 femur, 266 ilium, 222 multi-site. Over 104 femur and 87 ilium images, there were no over tolerance intra-fraction events detected with 2D-3D or OSMS. Over 20 manual shifts, OSMS could detect 2mm shifts to within 0.4mm 67% of the time and 0.8mm 95% of time. There was no difference in treatment set up time following adoption of an OSMS/TI workflow as a replacement for 2D-3D mid-imaging. A reduction in rib SBRT delivery and multi-site treatment set-up times was significantly associated with the adoption of OSMS/TI and OSMS, respectively, as assessed based on special cause variation with 8 consecutive points below the mean.

CONCLUSION

Integration of OSMS and triggered imaging has enabled the transition to a completely tattoo-less workflow, thus sparing patients the need for permanent tattoos whilst also allowing more continuous motion monitoring and reduced radiation exposure related to unnecessary 2D-3D or CBCT mid-imaging. Treatment times were significantly reduced for patients receiving rib SBRT or multi-site NSB SBRT with this workflow.

Deep Learning-Based Automated Quality Assurance for Palliative Spinal Treatment Planning in Radiotherapy

PURPOSE/OBJECTIVE(S)

Robustquality assurance (QA) for palliative spine radiation therapy (RT) remains critical due to the risk of wrong anatomic level treatment on account of human error in enumerating vertebral bodies accurately based on morphology with incomplete imaging of the spine and prevalence of anatomic variants (10%). We propose a rapid, fully automated deep learning-based QA (DL-QA) tool for segmenting and enumerating vertebral structures from image data, capable of identifying misalignment based on discrepancies in calculated dose coverage.

MATERIALS/METHODS

Ina retrospective cohort of 514 patients who received palliative spine radiation treatment at a single institution for spinal metastases, vertebral volumes for each individual spine level were automatically segmented on RT planning computed tomography scans using a publicly available deep learning algorithm, Total Segmentator (TS) deployed in the treatment planning system (Wasserthal et al, 2022). Departmental policy requires that the prescription/plan name include all spinal levels that receive a prescribed dosimetric threshold of V50% > 50%. By comparing the intended spine level target in the prescription and plan name against the TS volumes, the DL-QA flagged all cases for which any target vertebrae did not receive this threshold dose and/or any non-targeted vertebrae that received V50% > 50%. To detect spine anomalies, cases were also flagged if any vertebrae volume was not within ±1σ of the entire population of vertebrae volumes. Flagged cases were either categorized as: (1) wrong spine level RT error; (2) documentation error, in which treatment was correct but the prescription/plan name did not follow Departmental policy; or (3) potential spinal geometric error. All flagged cases were verified manually by checking the original images and treatment planning data.

RESULTS

Outof 514 patients, 29 cases were flagged as potential errors. Manual review revealed that one of these was a previously discovered true treatment error (due to anatomic variant with 4 lumbar bodies) while 10 were treated as intended but showed documentation errors due to variants in the number of vertebral bodies, kyphosis of the spine causing non-targeted vertebrae to appear in the treatment field, or improper observation of the Departmental plan naming policy. The remaining 18 cases were associated with flagged vertebrae volumes. Reviewing those patients, we identified spinal anomalies where TS attempted to account for extra or missing vertebrae (N = 9) and cases where TS made segmentation errors (N = 9).

CONCLUSION

Theproposed automated DL-QA system successfully identified patients with spine anomalies, flagged documentation errors, verified the correct target levels of spine RT treatments, and detected a known misadministration. The next phase will involve prospective testing of the system in a clinical setting upstream of treatment delivery.

Feasibility of the Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) System for Anesthesia Avoidance in Pediatric Patients: A Multicenter Trial

PURPOSE

The Audio-Visual Assisted Therapeutic Ambience in Radiotherapy (AVATAR) system was the first published radiation therapy (RT)-compatible system to reduce the need for pediatric anesthesia through video-based distraction. We evaluated the feasibility of AVATAR implementation and effects on anesthesia use, quality of life, and anxiety in a multicenter pediatric trial.

METHODS AND MATERIALS

Pediatric patients 3 to 10 years of age preparing to undergo RT at 10 institutions were prospectively enrolled. Children able to undergo at least 1 fraction of RT using AVATAR without anesthesia were considered successful (S). Patients requiring anesthesia for their entire treatment course were nonsuccessful (NS). The PedsQL3.0 Cancer Module (PedsQL) survey assessed quality of life and was administered to the patient and guardian at RT simulation, midway through RT, and at final treatment. The modified Yale Preoperative Anxiety Scale (mYPAS) assessed anxiety and was performed at the same 3 time points. Success was evaluated using the χ2 test. PedsQL and mYPAS scores were assessed using mixed effects models with time points evaluated as fixed effects and a random intercept on the subject.

RESULTS

Eighty-one children were included; median age was 7 years. AVATAR was successful at all 10 institutions and with photon and proton RT. There were 63 (78%) S patients; anesthesia was avoided for a median of 20 fractions per patient. Success differed by age (P = .04) and private versus public insurance (P < .001). Both patient (P = .008) and parent (P = .006) PedsQL scores significantly improved over the course of RT for patients aged 5 to 7. Anxiety in the treatment room decreased for both S and NS patients over RT course (P < .001), by age (P < .001), and by S versus NS patients (P < .001).

CONCLUSIONS

In this 10-center prospective trial, anesthesia avoidance with AVATAR was 78% in children aged 3 to 10 years, higher than among age-matched historical controls (49%; P < .001). AVATAR implementation is feasible across multiple institutions and should be further studied and made available to patients who may benefit from video-based distraction.

Cost of cardiac stereotactic body radioablation therapy versus catheter ablation for treatment of ventricular tachycardia

AIMS

To compare the cost of cardiac stereotactic body radiotherapy (SBRT) vs catheter ablation for treating ventricular tachycardia (VT).

BACKGROUND

Cardiac SBRT is a novel way of treating refractory VT that may be less costly than catheter ablation, owing to its non-invasive, outpatient nature. However, the true costs of either procedure are not well described, which could help inform a more appropriate reimbursement for cardiac SBRT than simply cross-indexing existing procedural rates.

METHODS

Process maps were derived for the full patient care cycle of both procedures using time-driven activity-based costing. Step-by-step timestamps were collected prospectively from a 10-patient SBRT cohort and retrospectively from a 59-patient catheter ablation cohort. Individual costs were estimated by multiplying timestamps with capacity cost rates (CCRs) for personnel, space, equipment, consumable, and indirect resources. These were summed into total cost, which for cardiac SBRT was compared with current catheter ablation and single-fraction lung SBRT reimbursements, both potential reference rates for cardiac SBRT.

RESULTS

The direct and total procedural costs of cardiac SBRT ($7,549 and $10,621) were 49% and 54% less than those of VT ablation ($14,707 and $23,225). These costs were significantly different from current reimbursement for catheter ablation ($22,692) and lung SBRT ($6,329). After including hospitalization expenses (≥$15,000), VT ablation cost at least $27,604 more to furnish than cardiac SBRT.

CONCLUSIONS

TDABC can be a helpful tool for assessing healthcare costs, including novel treatment approaches. In addition to its clinical benefits, cardiac SBRT may provide significant cost reduction opportunities for treatment of VT. This article is protected by copyright. All rights reserved.

Patient specific distortion detection and mitigation in MR images used for stereotactic radiosurgery

Objective. In MRI-based radiation therapy planning, mitigating patient-specific distortion with standard high bandwidth scans can result in unnecessary sacrifices of signal to noise ratio. This study investigates a technique for distortion detection and mitigation on a patient specific basis. Approach. Fast B0 mapping was performed using a previously developed technique for high-resolution, large dynamic range field mapping without the need for phase unwrapping algorithms. A phantom study was performed to validate the method. Distortion mitigation was validated by reducing geometric distortion with increased acquisition bandwidth and confirmed by both the B0 mapping technique and manual measurements. Images and contours from 25 brain stereotactic radiosurgery patients and 95 targets were analyzed to estimate the range of geometric distortions expected in the brain and to estimate bandwidth required to keep all treatment targets within the ±0.5 mm iso-distortion contour. Main Results. The phantom study showed, at 3 T, the technique can measure distortions with a mean absolute error of 0.12 mm (0.18 ppm), and a maximum error of 0.37 mm (0.6 ppm). For image acquisition at 3 T and 1.0 mm resolution, mean absolute distortion under 0.5 mm in patients required bandwidths from 109 to 200 Hz px−1 for patients with the least and most distortion, respectively. Maximum absolute distortion under 0.5 mm required bandwidths from 120 to 390 Hz px−1. Significance. The method for B0 mapping was shown to be valid and may be applied to assess distortion clinically. Future work will adapt the readout bandwidth to prospectively mitigate distortion with the goal to improve radiosurgery treatment outcomes by reducing healthy tissue exposure.

A bi-institutional multi-disciplinary failure mode and effects analysis (FMEA) for a Co-60 based total body irradiation technique

BACKGROUND

We aim to assess the risks associated with total body irradiation (TBI) delivered using a commercial dedicated Co-60 irradiator, and to evaluate inter-institutional and inter-professional variations in the estimation of these risks.

METHODS

A failure mode and effects analysis (FMEA) was generated using guidance from the AAPM TG-100 report for quantitative estimation of prospective risk metrics. Thirteen radiation oncology professionals from two institutions rated possible failure modes (FMs) for occurrence (O), severity (S), and detectability (D) indices to generate a risk priority number (RPN). The FMs were ranked by descending RPN value. Absolute gross differences (AGD) in resulting RPN values and Jaccard Index (JI; for the top 20 FMs) were calculated. The results were compared between professions and institutions.

RESULTS

A total of 87 potential FMs (57, 15, 10, 3, and 2 for treatment, quality assurance, planning, simulation, and logistics respectively) were identified and ranked, with individual RPN ranging between 1-420 and mean RPN values ranging between 6 and 74. The two institutions shared 6 of their respective top 20 FMs. For various institutional and professional comparison pairs, the number of common FMs in the top 20 FMs ranged from 6 to 13, with JI values of 18-48%. For the top 20 FMs, the trend in inter-professional variability was institution-specific. The mean AGD values ranged between 12.5 and 74.5 for various comparison pairs. AGD values differed the most for medical physicists (MPs) in comparison to other specialties i.e. radiation oncologists (ROs) and radiation therapists (RTs) [MPs-vs-ROs: 36.3 (standard deviation SD = 34.1); MPs-vs-RTs: 41.2 (SD = 37.9); ROs-vs-RTs: 12.5 (SD = 10.8)]. Trends in inter-professional AGD values were similar for both institutions.

CONCLUSION

This inter-institutional comparison provides prospective risk analysis for a new treatment delivery unit and illustrates the institution-specific nature of FM prioritization, primarily due to operational differences. Despite being subjective in nature, the FMEA is a valuable tool to ensure the identification of the most significant risks, particularly when implementing a novel treatment modality. The creation of a bi-institutional, multidisciplinary FMEA for this unique TBI technique has not only helped identify potential risks but also served as an opportunity to evaluate clinical and safety practices from the perspective of both multiple professional roles and different institutions.

Cardiac stereotactic body radiation therapy for ventricular tachycardia: Current experience and technical gaps

INTRODUCTION

Despite advances in drug and catheter ablation therapy, long-term recurrence rates for ventricular tachycardia remain suboptimal. Cardiac stereotactic body radiotherapy (SBRT) is a novel treatment that has demonstrated reduction of arrhythmia episodes and favorable short-term safety profile in treatment-refractory patients. Nevertheless, the current clinical experience is early and limited. Recent studies have highlighted variable duration of treatment effect and substantial recurrence rates several months postradiation. Contributing to these differential outcomes are disparate approaches groups have taken in planning and delivering radiation, owing to both technical and knowledge gaps limiting optimization and standardization of cardiac SBRT.

METHODS AND FINDINGS

In this report, we review the historical basis for cardiac SBRT and existing clinical data. We then elucidate the current technical gaps in cardiac radioablation, incorporating the current clinical experience, and summarize the ongoing and needed efforts to resolve them.

CONCLUSION

Cardiac SBRT is an emerging therapy that holds promise for the treatment of ventricular tachycardia. Technical gaps remain, to be addressed by ongoing research and growing clincial experience.

Ultrasound-based sensors to monitor physiological motion

PURPOSE

Medical procedures can be difficult to perform on anatomy that is constantly moving. Respiration displaces internal organs by up to several centimeters with respect to the surface of the body, and patients often have limited ability to hold their breath. Strategies to compensate for motion during diagnostic and therapeutic procedures require reliable information to be available. However, current devices often monitor respiration indirectly, through changes on the outline of the body, and they may be fixed to floors or ceilings, and thus unable to follow a given patient through different locations. Here we show that small ultrasound-based sensors referred to as "organ configuration motion" (OCM) sensors can be fixed to the abdomen and/or chest and provide information-rich, breathing-related signals.

METHODS

By design, the proposed sensors are relatively inexpensive. Breathing waveforms were obtained from tissues at varying depths and/or using different sensor placements. Validation was performed against breathing waveforms derived from magnetic resonance imaging (MRI) and optical tracking signals in five and eight volunteers, respectively.

RESULTS

Breathing waveforms from different modalities were scaled so they could be directly compared. Differences between waveforms were expressed in the form of a percentage, as compared to the amplitude of a typical breath. Expressed in this manner, for shallow tissues, OCM-derived waveforms on average differed from MRI and optical tracking results by 13.1% and 15.5%, respectively.

CONCLUSION

The present results suggest that the proposed sensors provide measurements that properly characterize breathing states. While OCM-based waveforms from shallow tissues proved similar in terms of information content to those derived from MRI or optical tracking, OCM further captured depth-dependent and position-dependent (i.e., chest and abdomen) information. In time, the richer information content of OCM-based waveforms may enable better respiratory gating to be performed, to allow diagnostic and therapeutic equipment to perform at their best.

Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation. These new features include C++-based code optimization for fast individual fiber tracking, Java-based synthetic fiber generator module for method validation, automatic tumor boundary generation for fiber relative quantification, parallel computing for large-scale batch mode processing, region-of-interest analysis for user-specified quantification, and pre- and post-processing modules for individual fiber visualization. We present a validation of the tracking of individual fibers and fiber orientations by using synthesized fibers generated by the synthetic fiber generator. In addition, we provide a comparison of the fiber orientation calculation on pancreatic tissue images between our tool and three other quantitative approaches. Lastly, we demonstrate the use of our software tool for the automatic tumor boundary creation and the relative alignment quantification of collagen fibers in human breast cancer pathology images, as well as the alignment quantification of in vivo mouse xenograft breast cancer images.

Technical Note: Quality assurance and relative dosimetry testing of a 60 Co total body irradiator using optical imaging

PURPOSE

The aim of this study was to create an optical imaging-based system for quality assurance (QA) testing of a dedicated Co-60 total body irradiation (TBI) machine. Our goal is to streamline the QA process by minimizing the amount time necessary for tests such as verification of dose rate and field homogeneity.

METHODS

Plastic scintillating rods were placed directly on the patient treatment couch of a dedicated TBI ⁶⁰ Co irradiator. A tripod-mounted intensified camera was placed directly adjacent to the couch. Images were acquired over a 30-s period once the cobalt source was fully exposed. Real-time image filtering was used; cumulative images were flatfield corrected as well as background and darkfield subtracted. Scintillators were used to measure light-radiation field correspondence, dose rate, field homogeneity, and symmetry. Dose rate effects were measured by modifying the height of the treatment couch and scintillator response was compared to ionization chamber (IC) measurements. Optically stimulated luminesce detector (OSLD) used as reference dosimeters during field symmetry and homogeneity testing.

RESULTS

The scintillator-based system accurately reported changes in dose rate. When comparing normalized output values for IC vs scintillators over a range of source-to-surface distances, a linear relationship (R²  = 0.99) was observed. Normalized scintillator signal matched OSLD measurements with <1.5% difference during field homogeneity and symmetry testing. Beam symmetry across both axes of the field was within 2%. The light field was found to correspond to 90 ± 3% of the isodose maximum along the longitudinal and latitudinal axis, respectively. Scintillator imaging output results using a single image stack requiring no postexposure processing (needed for OSLD) or repeat manual measurements (needed for IC).

CONCLUSION

Imaging of scintillation light emission from plastic rods is a viable and efficient method for carrying out TBI ⁶⁰ Co irradiator QA. We have shown that this technique can accurately measure field homogeneity, symmetry, light-radiation field correspondence, and dose rate effects.

Collagen organization of renal cell carcinoma differs between low and high grade tumors

Background

The traditional pathologic grading for human renal cell carcinoma (RCC) has low concordance between biopsy and surgical specimen. There is a need to investigate adjunctive pathology technique that does not rely on the nuclear morphology that defines the traditional grading. Changes in collagen organization in the extracellular matrix have been linked to prognosis or grade in breast, ovarian, and pancreatic cancers, but collagen organization has never been correlated with RCC grade. In this study, we used Second Harmonic Generation (SHG) based imaging to quantify possible differences in collagen organization between high and low grades of human RCC.

Methods

A tissue microarray (TMA) was constructed from RCC tumor specimens. Each TMA core represents an individual patient. A 5 μm section from the TMA tissue was stained with standard hematoxylin and eosin (H&E). Bright field images of the H&E stained TMA were used to annotate representative RCC regions. In this study, 70 grade 1 cores and 51 grade 4 cores were imaged on a custom-built forward SHG microscope, and images were analyzed using established software tools to automatically extract and quantify collagen fibers for alignment and density assessment. A linear mixed-effects model with random intercepts to account for the within-patient correlation was created to compare grade 1 vs. grade 4 measurements and the statistical tests were two-sided.

Results

Both collagen density and alignment differed significantly between RCC grade 1 and RCC grade 4. Specifically, collagen fiber density was greater in grade 4 than in grade 1 RCC (p < 0.001). Collagen fibers were also more aligned in grade 4 compared to grade 1 (p < 0.001).

Conclusions

Collagen density and alignment were shown to be significantly higher in RCC grade 4 vs. grade 1. This technique of biopsy sampling by SHG could complement classical tumor grading approaches. Furthermore it might allow biopsies to be more clinically relevant by informing diagnostics. Future studies are required to investigate the functional role of collagen organization in RCC.

Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma In Situ

Background: Collagen fibers surrounding breast ducts may influence breast cancer progression. Syndecan-1 interacts with constituents in the extracellular matrix, including collagen fibers, and may contribute to cancer cell migration. Thus, the orientation of collagen fibers surrounding ductal carcinoma in situ (DCIS) lesions and stromal syndecan-1 expression may predict recurrence.Methods: We evaluated collagen fiber alignment and syndecan-1 expression in 227 women diagnosed with DCIS in 1995 to 2006 followed through 2014 (median, 14.5 years; range, 0.7-17.6). Stromal collagen alignment was evaluated from diagnostic tissue slides using second harmonic generation microscopy and fiber analysis software. Univariate analysis was conducted using χ2 tests and ANOVA. The association between collagen alignment z-scores, syndecan-1 staining intensity, and time to recurrence was evaluated using HRs and 95% confidence intervals (CIs).Results: Greater fiber angles surrounding DCIS lesions, but not syndecan-1 staining intensity, were related to positive HER2 (P = 0.002) status, comedo necrosis (P = 0.03), and negative estrogen receptor (P = 0.002) and progesterone receptor (P = 0.02) status. Fiber angle distributions surrounding lesions included more angles closer to 90 degrees than normal ducts (P = 0.06). Collagen alignment z-scores for DCIS lesions were positively related to recurrence (HR = 1.25; 95% CI, 0.84-1.87 for an interquartile range increase in average fiber angles).Conclusions: Although collagen alignment and stromal syndecan-1 expression did not predict recurrence, collagen fibers perpendicular to the duct perimeter were more frequent in DCIS lesions with features typical of poor prognosis.Impact: Follow-up studies are warranted to examine whether additional features of the collagen matrix may more strongly predict patient outcomes. Cancer Epidemiol Biomarkers Prev; 27(2); 138-45. ©2017 AACR.

The impact of a high-definition multileaf collimator for spine SBRT

Purpose

Advanced radiotherapy delivery systems designed for high‐dose, high‐precision treatments often come equipped with high‐definition multi‐leaf collimators (HD‐MLC) aimed at more finely shaping radiation dose to the target. In this work, we study the effect of a high definition MLC on spine stereotactic body radiation therapy (SBRT) treatment plan quality and plan deliverability.

Methods and Materials

Seventeen spine SBRT cases were planned with VMAT using a standard definition MLC (M120), HD‐MLC, and HD‐MLC with an added objective to reduce monitor units (MU). M120 plans were converted into plans deliverable on an HD‐MLC using in‐house software. Plan quality and plan deliverability as measured by portal dosimetry were compared among the three types of plans.

Results

Only minor differences were noted in plan quality between the M120 and HD‐MLC plans. Plans generated with the HD‐MLC tended to have better spinal cord sparing (3% reduction in maximum cord dose). HD‐MLC plans on average had 12% more MU and 55% greater modulation complexity as defined by an in‐house metric. HD‐MLC plans also had significantly degraded deliverability. Of the VMAT arcs measured, 94% had lower gamma passing metrics when using the HD‐MLC.

Conclusion

Modest improvements in plan quality were noted when switching from M120 to HD‐MLC at the expense of significantly less accurate deliverability in some cases.

Synthetic CT for MRI-based liver stereotactic body radiotherapy treatment planning

A technique for generating MRI-derived synthetic CT volumes (MRCTs) is demonstrated in support of adaptive liver stereotactic body radiation therapy (SBRT). Under IRB approval, 16 subjects with hepatocellular carcinoma were scanned using a single MR pulse sequence (T1 Dixon). Air-containing voxels were identified by intensity thresholding on T1-weighted, water and fat images. The envelope of the anterior vertebral bodies was segmented from the fat image and fuzzy-C-means (FCM) was used to classify each non-air voxel as mid-density, lower-density, bone, or marrow in the abdomen, with only bone and marrow classified within the vertebral body envelope. MRCT volumes were created by integrating the product of the FCM class probability with its assigned class density for each voxel. MRCTs were deformably aligned with corresponding planning CTs and 2-ARC-SBRT-VMAT plans were optimized on MRCTs. Fluence was copied onto the CT density grids, dose recalculated, and compared. The liver, vertebral bodies, kidneys, spleen and cord had median Hounsfield unit differences of less than 60. Median target dose metrics were all within 0.1 Gy with maximum differences less than 0.5 Gy. OAR dose differences were similarly small (median: 0.03 Gy, std:0.26 Gy). Results demonstrate that MRCTs derived from a single abdominal imaging sequence are promising for use in SBRT dose calculation.

Implementation of the validation testing in MPPG 5.a "Commissioning and QA of treatment planning dose calculations-megavoltage photon and electron beams"

The AAPM Medical Physics Practice Guideline (MPPG) 5.a provides concise guidance on the commissioning and QA of beam modeling and dose calculation in radiotherapy treatment planning systems. This work discusses the implementation of the validation testing recommended in MPPG 5.a at two institutions. The two institutions worked collaboratively to create a common set of treatment fields and analysis tools to deliver and analyze the validation tests. This included the development of a novel, open‐source software tool to compare scanning water tank measurements to 3D DICOM‐RT Dose distributions. Dose calculation algorithms in both Pinnacle and Eclipse were tested with MPPG 5.a to validate the modeling of Varian TrueBeam linear accelerators. The validation process resulted in more than 200 water tank scans and more than 50 point measurements per institution, each of which was compared to a dose calculation from the institution's treatment planning system (TPS). Overall, the validation testing recommended in MPPG 5.a took approximately 79 person‐hours for a machine with four photon and five electron energies for a single TPS. Of the 79 person‐hours, 26 person‐hours required time on the machine, and the remainder involved preparation and analysis. The basic photon, electron, and heterogeneity correction tests were evaluated with the tolerances in MPPG 5.a, and the tolerances were met for all tests. The MPPG 5.a evaluation criteria were used to assess the small field and IMRT/VMAT validation tests. Both institutions found the use of MPPG 5.a to be a valuable resource during the commissioning process. The validation testing in MPPG 5.a showed the strengths and limitations of the TPS models. In addition, the data collected during the validation testing is useful for routine QA of the TPS, validation of software upgrades, and commissioning of new algorithms.

Second-harmonic generation imaging of cancer

The last 30 years has seen great advances in optical microscopy with the introduction of sophisticated fluorescence-based imaging methods such as confocal and multiphoton laser scanning microscopy. There is increasing interest in using these methods to quantitatively examine sources of intrinsic biological contrast including autofluorescent endogenous proteins and light interactions such as second-harmonic generation (SHG) in collagen. In particular, SHG-based microscopy has become a widely used quantitative modality for imaging noncentrosymmetric proteins such as collagen in a diverse range of tissues. Due to the underlying physical origin of the SHG signal, it is highly sensitive to collagen fibril/fiber structure and, importantly, to collagen-associated changes that occur in diseases such as cancer, fibrosis, and connective tissue disorders. An overview of SHG physics background and technologies is presented with a focused review on applications of SHG primarily as applied to cancer.

Automated quantification of aligned collagen for human breast carcinoma prognosis

Background:

Mortality in cancer patients is directly attributable to the ability of cancer cells to metastasize to distant sites from the primary tumor. This migration of tumor cells begins with a remodeling of the local tumor microenvironment, including changes to the extracellular matrix and the recruitment of stromal cells, both of which facilitate invasion of tumor cells into the bloodstream. In breast cancer, it has been proposed that the alignment of collagen fibers surrounding tumor epithelial cells can serve as a quantitative image-based biomarker for survival of invasive ductal carcinoma patients. Specific types of collagen alignment have been identified for their prognostic value and now these tumor associated collagen signatures (TACS) are central to several clinical specimen imaging trials. Here, we implement the semi-automated acquisition and analysis of this TACS candidate biomarker and demonstrate a protocol that will allow consistent scoring to be performed throughout large patient cohorts.

Methods:

Using large field of view high resolution microscopy techniques, image processing and supervised learning methods, we are able to quantify and score features of collagen fiber alignment with respect to adjacent tumor-stromal boundaries.

Results:

Our semi-automated technique produced scores that have statistically significant correlation with scores generated by a panel of three human observers. In addition, our system generated classification scores that accurately predicted survival in a cohort of 196 breast cancer patients. Feature rank analysis reveals that TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction.

Conclusion:

These results demonstrate the utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.

Abstract P1-06-06: Alteration of stromal collagen fiber orientation in DCIS

Approximately 20% of new diagnoses of breast cancer are ductal carcinoma in situ (DCIS), a non-invasive form of breast cancer. Treatment decision-making for DCIS is challenging since current predictors of disease-free survival are limited, so that most women are presented with options for surgery, radiation and tamoxifen - all options with consequences for quality of life. Prior studies of prognostic factors for DCIS have focused on morphologic, genetic, and protein expression patterns of the DCIS cells. However, laboratory evidence suggests that the tumor microenvironment may play a key role in tumor invasion and progression. Collagen is the most abundant component of the stroma surrounding the breast ducts in which cancers develop. We previously observed that, in invasive breast cancer, tumors with greater numbers of collagen fibers aligned perpendicularly from the tumor were more likely to predict poor survival than tumors with collagen fibers in primarily parallel patterns near the tumor boundary (Conklin Am J Pathol 2011). To improve our ability to predict breast cancer outcomes in women with DCIS, we examined the alignment of collagen adjacent to ducts affected by DCIS to test whether alignment patterns were similar to patterns observed in tissue labeled as “normal” from biopsy and surgical sections. We evaluated collagen alignment in 255 Wisconsin women diagnosed with DCIS in 1997-2000 and followed for a median of 11.2 years (range 1-15). Stromal collagen alignment was evaluated from routine H&E tissue slides prepared at the time of diagnosis using second harmonic generation (SHG) microscopy, a label-free multiphoton laser scanning technique that selectively images collagen. SHG images were acquired and evaluated for 3-5 regions on each DCIS and normal slide for each patient; the angles of collagen fibers with respect to the DCIS lesion/stroma boundary were calculated using customized imaging software. Data for the distribution of angles were compared for normal ducts and DCIS lesions using compositional data analysis with the number of fibers totaled according to 5-angle bins (1-5, 6-10, 11-15, …, 86-90 degrees). Repeated measures linear regression models were fit to log-transformed ratios of binned counts as a function of tissue type. Dependence among repeated counts within a single region was modeled using an unstructured variance-covariance matrix. Dependence among measurements within a single subject was modeled using a compound symmetry correlation structure. Overall, the distribution of collagen fiber angles from DCIS lesions differed significantly (P = 0.0002) from the distribution of collagen fibers surrounding normal ducts. Collagen fibers surrounding DCIS lesions were 11-18% more likely to orient at 75-90 degrees relative to the lesion boundary than fibers surrounding normal ducts; fibers were more similarly aligned in both DCIS lesions and normal ducts at other smaller angles. These results underscore the relevance of the tumor microenvironment, in particular the arrangement of the collagen fiber matrix. Planned data analysis will next examine whether collagen fiber alignment patterns differ between DCIS patients who did and did not experience a second breast cancer diagnosis over the course of follow-up.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-06-06.

Pulse shaping strategies for nonlinear interferometric vibrational imaging optimized for biomolecular imaging

Nonlinear interferometric vibrational imaging (NIVI) measures the temporal cross-correlation of anti-Stokes radiation from coherent anti-Stokes Raman scattering (CARS) processes to achieve increased sensitivity, stray light rejection, and nonresonant background rejection. Because the intensity of CARS radiation is proportional to the square of the molecular density of a target resonance, it is critical to maximize the recoverable signal for a given illumination level. Especially if one desires to measure several resonances, there can be a sensitivity as well as a speed advantage to measuring them simultaneously rather than serially. We discuss the methods of sample excitation that NIVI allows and their potential sensitivity advantages, as well as present experimental results demonstrating Raman signal recovery using these pulse sequences.

Molecularly sensitive optical coherence tomography

Molecular contrast in optical coherence tomography (OCT) is demonstrated by use of coherent anti-Stokes Raman scattering (CARS) for molecular sensitivity. Femtosecond laser pulses are focused into a sample by use of a low-numerical-aperture lens to generate CARS photons, and the backreflected CARS signal is interferometrically measured. With the chemical selectivity provided by CARS and the advanced imaging capabilities of OCT, this technique may be useful for molecular contrast imaging in biological tissues. CARS can be generated and interferometrically measured over at least 600 microm of the depth of field of a low-numerical-aperture objective.