Review and recommendations on deformable image registration uncertainties for radiotherapy applications

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

Abstract P2-03-01: Sarcopenia on baseline imaging is associated with toxicity-related discontinuation of endocrine therapy in women with early-stage hormone-positive breast cancer

Background Adjuvant endocrine therapy (ET) is standard of care in women with hormone receptor-positive (HR+) breast cancer (BC) with the goal to reduce recurrence. However, early discontinuation of ET occurs in 30-40% of women, largely attributable to toxicity, and leads to increased recurrence risk. There is considerable overlap in risk factors that predict toxicity from ET and chemotherapy, including age, co-morbidities, and geriatric conditions. Baseline low skeletal muscle area (SMA) on chest computed tomography (CT) is a surrogate marker for sarcopenia and predicts for significant toxicity and intolerance to chemotherapy in women with BC. No study has assessed the association of sarcopenia with toxicity-related discontinuation of ET in women with early-stage HR+ BC. Methods This single center retrospective cohort study included consecutive women with Stage 0-II HR+ BC who received ET and adjuvant radiotherapy (RT) from 01/2011-12/2017. Inclusion required a minimum of 5-year clinical follow-up after diagnosis. We used a validated deep learning pipeline to quantify SMA (cm2) at the tenth thoracic (T10) vertebral body on existing RT planning CT. The skeletal muscle index (SMI [cm2/m2] = SMA/(patient height (m))2) was calculated to adjust for patient height. Sarcopenia was defined as SMI< 32.3 cm2/m2, based on a previously validated independent cohort of young healthy women. The primary endpoint was toxicity-related discontinuation of ET less than 60 months after initiation of ET. Secondary endpoints included any NCI CTCAE v5.0 Grade 3-5 toxicity from ET and ipsilateral breast tumor recurrence. We assessed associations between ET discontinuation and SMI (continuous), as well as thoracic sarcopenia (dichotomous), using logistic regression adjusting for baseline characteristics. We used cox proportional hazards regression to assess disease-free survival (DFS), defined as ipsilateral breast tumor recurrence, locoregional recurrence, or distant metastasis adjusting for baseline and treatment characteristics. Results A total of 265 women (median age 67 years) met inclusion criteria. The majority of women had a comorbidity index of 0-1 (89%) and were Caucasian (89%). The median follow-up was 82 months, 5-year overall survival was 96% and 5-year DFS was 94%. Diagnoses included DCIS (12%), IDC (76%), or ILC (12%); most were T1 (69%) or T2 (18%) and N0 (85%), ER-positive (100%), PR-positive (85%), or HER2-negative (9%). Most common ET type was anastrozole (63%), letrozole (16%), and tamoxifen (17%). SMI (continuous) was not associated with older age, Charlson Comorbidity Index (CCI), race, or tumor stage. A total of 64 (24%) women experienced toxicity-related early discontinuation of ET. On multivariate analysis (MVA), lower SMI was associated with increased toxicity-related early discontinuation of ET (Odds Ratio [OR] 0.89 per 1 cm2/m2 SMI, p=0.001) independent of age, CCI, ET type, or receipt of adjuvant chemotherapy. Lower SMI was associated with higher risk of grade 3-5 toxicity from ET (OR 0.89 per 1 unit SMI, p=0.001) independent of age, CCI, ET type, or receipt of adjuvant chemotherapy. On MVA, sarcopenia was associated with higher risk of toxicity-related early discontinuation of ET (OR 2.43, p=0.019). DFS was associated with toxicity-related early discontinuation of ET (HR 8.06, p=0.005), grade 3 histology (HR 1.42, p=0.042), and multifocal disease (HR 2.55, p=0.040), but not age, histology, stage, or lymphovascular invasion (p>.05 for all). Conclusion Low baseline thoracic skeletal muscle is associated with toxicity-related early ET discontinuation in women with early-stage HR+ BC. Further studies should attempt to generalize this association to all HR+ BC who are candidates for ET. High-risk patients may be candidates for aggressive symptom management or alternative adjuvant therapies.

Citation Format: Anurag Saraf, Ismail Tahir, Bonnie Hu, Anna-Sophia Dietrich, Paul Erik Tonnesen, Greg Sharp, Gayle Tillman, Florian Fintelmann, Rachel Jimenez. Sarcopenia on baseline imaging is associated with toxicity-related discontinuation of endocrine therapy in women with early-stage hormone-positive breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-03-01.

Long-stay medical-surgical intensive care unit patients in South Africa: Quality of life and mortality 1 year after discharge

BACKGROUND

Although mortality is the primary measure of critical care outcome, the health-related quality of life (HRQOL) of survivors is often diminished. There is a paucity of South African research on HRQOL in intensive care unit (ICU) survivors.

OBJECTIVES

To evaluate the 1-year post-discharge data of long-stay ICU patients, a group known to consume 20 - 40% of ICU resources.

METHODS

A 1-year prospective observational study was conducted in a multidisciplinary medical-surgical ICU. Adult patients who were mechanically ventilated beyond 6 days were included. Clinical and mortality data were collected. Pre-admission and 6- and 12-month HRQOL were measured with the Short Form-36 questionnaire. Physical and mental component summary scores (PCS and MCS) were calculated. Associations between 12-month mortality and poor HRQOL scores were determined.

RESULTS

Of 119 patients enrolled, 40.3% had sustained trauma, 19.3% were post-surgical and 40.3% had medical conditions; 29.2% were HIV-positive (HIV status was known for 74.8% of the cohort). The hospital and 12-month mortality rates were 42.9% and 57.4% (n=66/115), respectively. Age, longer ICU stay, higher disease severity scores and vasopressor use were associated with 12-month mortality. The survivors' median PCS and MCS at 6 and 12 months were significantly lower compared with pre-admission scores (both p<0.001). At 12 months, 53.1% of survivors demonstrated a poor PCS and 42.9% a poor MCS. Associations with poor 12-month PCS included longer ICU stay, male gender and trauma, while trauma and sepsis were associated with a poor 12-month MCS. Among the 19 trauma survivors, 78.9% had a poor MCS and/or PCS. Of previously employed patients, 54.8% were unemployed at 12 months.

CONCLUSIONS

Patients ventilated beyond 6 days in a multidisciplinary ICU had a high mortality. Poor HRQOL at 12 months post discharge was frequently observed among survivors. Trauma was associated with poor 12-month outcomes. These findings highlight the need to further explore the outcomes of long-stay ICU patients in Africa.

Valproate-Associated Hyperammonaemic Encephalopathy

We present the case of a 55 year old who presented multiple times with altered conscious levels. He was often treated as being post-ictal, when in fact, he had Sodium Valproate induced hyperammonaemic encephalopathy. Sodium Valproate can frequently increase ammonia levels, and in some patient lead to hyperammonaemic encephalopathy.

Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentations

PURPOSE

The use of magnetic resonance imaging (MRI) in radiotherapy treatment planning has rapidly increased due to its ability to evaluate patient's anatomy without the use of ionizing radiation and due to its high soft tissue contrast. For these reasons, MRI has become the modality of choice for longitudinal and adaptive treatment studies. Automatic segmentation could offer many benefits for these studies. In this work, we describe a T2-weighted MRI dataset of head and neck cancer patients that can be used to evaluate the accuracy of head and neck normal tissue auto-segmentation systems through comparisons to available expert manual segmentations.

ACQUISITION AND VALIDATION METHODS

T2-weighted MRI images were acquired for 55 head and neck cancer patients. These scans were collected after radiotherapy computed tomography (CT) simulation scans using a thermoplastic mask to replicate patient treatment position. All scans were acquired on a single 1.5 T Siemens MAGNETOM Aera MRI with two large four-channel flex phased-array coils. The scans covered the region encompassing the nasopharynx region cranially and supraclavicular lymph node region caudally, when possible, in the superior-inferior direction. Manual contours were created for the left/right submandibular gland, left/right parotids, left/right lymph node level II, and left/right lymph node level III. These contours underwent quality assurance to ensure adherence to predefined guidelines, and were corrected if edits were necessary.

DATA FORMAT AND USAGE NOTES

The T2-weighted images and RTSTRUCT files are available in DICOM format. The regions of interest are named based on AAPM's Task Group 263 nomenclature recommendations (Glnd_Submand_L, Glnd_Submand_R, LN_Neck_II_L, Parotid_L, Parotid_R, LN_Neck_II_R, LN_Neck_III_L, LN_Neck_III_R). This dataset is available on The Cancer Imaging Archive (TCIA) by the National Cancer Institute under the collection "AAPM RT-MAC Grand Challenge 2019" (https://doi.org/10.7937/tcia.2019.bcfjqfqb).

POTENTIAL APPLICATIONS

This dataset provides head and neck patient MRI scans to evaluate auto-segmentation systems on T2-weighted images. Additional anatomies could be provided at a later time to enhance the existing library of contours.

CT images with expert manual contours of thoracic cancer for benchmarking auto-segmentation accuracy

PURPOSE

Automatic segmentation offers many benefits for radiotherapy treatment planning; however, the lack of publicly available benchmark datasets limits the clinical use of automatic segmentation. In this work, we present a well-curated computed tomography (CT) dataset of high-quality manually drawn contours from patients with thoracic cancer that can be used to evaluate the accuracy of thoracic normal tissue auto-segmentation systems.

ACQUISITION AND VALIDATION METHODS

Computed tomography scans of 60 patients undergoing treatment simulation for thoracic radiotherapy were acquired from three institutions: MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, and the MAASTRO clinic. Each institution provided CT scans from 20 patients, including mean intensity projection four-dimensional CT (4D CT), exhale phase (4D CT), or free-breathing CT scans depending on their clinical practice. All CT scans covered the entire thoracic region with a 50-cm field of view and slice spacing of 1, 2.5, or 3 mm. Manual contours of left/right lungs, esophagus, heart, and spinal cord were retrieved from the clinical treatment plans. These contours were checked for quality and edited if necessary to ensure adherence to RTOG 1106 contouring guidelines.

DATA FORMAT AND USAGE NOTES

The CT images and RTSTRUCT files are available in DICOM format. The regions of interest were named according to the nomenclature recommended by American Association of Physicists in Medicine Task Group 263 as Lung_L, Lung_R, Esophagus, Heart, and SpinalCord. This dataset is available on The Cancer Imaging Archive (funded by the National Cancer Institute) under Lung CT Segmentation Challenge 2017 (http://doi.org/10.7937/K9/TCIA.2017.3r3fvz08).

POTENTIAL APPLICATIONS

This dataset provides CT scans with well-delineated manually drawn contours from patients with thoracic cancer that can be used to evaluate auto-segmentation systems. Additional anatomies could be supplied in the future to enhance the existing library of contours.

Automatic diaphragm segmentation for real-time lung tumor tracking on cone-beam CT projections: a convolutional neural network approach

PURPOSE

To automatically segment the diaphragm on individual lung cone-beam CT projection images, to enable real-time tracking of lung tumors using kilovoltage imaging.

METHODS

The deep neural network Mask R-CNN was trained on 3500 raw cone-beam CT projection images from 10 lung cancer patients, with the diaphragm manually segmented on each image used as a ground truth label. Ground-truth breathing traces were extracted from each patient for both diaphragm hemispheres, and apex positions were compared against the predicted output of the neural network. Ten-fold cross-validation was used to evaluate the segmentation accuracy.

RESULTS

The mean diaphragm apex prediction error was 4.4 mm. The mean percentage of projection images for which a successful prediction could me made was 87.3%. Prediction accuracy at some lateral gantry angles was worse due to overlap between diaphragm hemispheres, and the increased amount of fatty tissue.

CONCLUSIONS

The neural network was able to track the diaphragm apex position successfully. This allows accurate assessment of the breathing phase, which can be used to estimate the position of the lung tumor in real time.

Hepatitis C virus among genitourinary clinic attenders in Scotland: unlinked anonymous testing

Our objective is to gauge the prevalence of hepatitis C virus (HCV) antibodies among a population at risk of contracting sexually transmitted infections (STIs) and, thus, the efficiency with which the virus is transmitted sexually. The investigators undertook an unlinked anonymous HCV antibody testing study of residual syphilis serology specimens taken from attenders of genitourinary clinics in Glasgow, Edinburgh and Aberdeen during 1996/97. The results were linked to non-identifying risk information. Anti-HCV prevalences among non-injecting heterosexual men and women, and non-injecting homosexual/bisexual males ranged between 0 and 1.2%; the only exception to this was a 7.7% (4/52) prevalence among homosexual/bisexual males in Aberdeen. The overall anti-HCV prevalence for homosexual/bisexual males was 0.6% (4/668), for heterosexual males 0.8% (32/4135), for heterosexual females 0.3% (10/3035) and for injecting drug users 49% (72/148). Only 3 (all female) of the 46 non-injectors who were antibody positive were non-UK nationals or had lived abroad. HCV antibody positive injectors were less likely to have an acute STI and more likely to know their HCV status than non-injectors; no differences in these parameters were found between positive and negative non-injectors on anonymous HCV antibody testing. Our findings are in keeping with the prevailing view that HCV can be acquired through sexual intercourse but, for most people, the probability of this occurring is extremely low. Interventions to prevent the spread of HCV should be targeted mainly at injecting drug user (IDU) populations.

Asymmetric split H-shape nanoantennas for molecular sensing

In this paper we report on a very sensitive biosensor based on gold asymmetric nanoantennas that are capable of enhancing the molecular resonances of C-H bonds. The nanoantennas are arranged as arrays of asymmetric-split H-shape (ASH) structures, tuned to produce plasmonic resonances with reflectance double peaks within the mid-infrared vibrational resonances of C-H bonds for the assay of deposited films of the molecule 17β-estradiol (E2), used as an analyte. Measurements and numerical simulations of the reflectance spectra have enabled an estimated enhancement factor on the order of 10⁵ to be obtained for a thin film of E2 on the ASH array. A high sensitivity value of 2335 nm/RIU was achieved, together with a figure of merit of approximately 8. Our experimental results were corroborated using numerical simulations for the C-H stretch vibrational resonances from the analyte, superimposed on the plasmonic resonances of the ASH nanoantennas.

Fractionated Lung IMPT Treatments

Treatment uncertainties in radiotherapy are either systematic or random. This study evaluates the sensitivity of fractionated intensity-modulated proton therapy (IMPT) lung treatments to systematic and random setup uncertainties. Treatments in which single-field homogeneity was restricted to within ±20% (IMPT20%) were compared to full IMPT (IMPTfull) for 10 patients with lung cancer. Four-dimensional Monte Carlo calculations were performed using patient computed tomography geometries with ±5 mm systematic or random setup uncertainties applied over a 35 × 2.5Gy(RBE) treatment course. Fifty fractionated courses were simulated for each patient using both IMPT delivery methods with random setup uncertainties applied each fraction and for 3 energy-dependent spot sizes (big spots, σ≈18-9 mm; intermediate spots, σ≈11-5 mm; and small spots, σ≈4-2 mm). These results were compared to Monte Carlo recalculations of the original treatment plan assuming zero setup uncertainty. Results are presented as the difference in equivalent uniform dose (ΔEUD), V95 (ΔV95), and target dose homogeneity (ΔD1-D99). Over the whole patient cohort, the ΔEUD was 2.0 ± 0.5 (big spots), 1.9 ± 0.7 (intermediate spots), and 1.3 ± 0.4 (small spots) times more sensitive to ±5 mm systematic setup uncertainties in IMPTfull compared to IMPT20%. IMPTfull is 1.9 ± 0.9 (big spots), 2.1 ± 1.1 (intermediate spots), and 1.5 ± 0.6 (small spots) times more sensitive to random setup uncertainties than IMPT20% over a fractionated treatment course. The ΔV95 is at least 1.4 times more sensitive to systematic and random setup uncertainties for IMPTfull for all spot sizes considered. The ΔD1-D99 values coincided within uncertainty limits for both IMPT delivery methods for the 3 spot sizes considered, with higher mean values always observed for IMPTfull. The paired t-test indicated that variations observed between IMPTfull and IMPT20% were significantly different for the majority of scenarios. Significantly larger variations were observed in ΔEUD and ΔV95 in IMPTfull lung treatments in addition to higher mean ΔD1−D99. The steep intra-target dose gradients in IMPTfull make it more susceptible to systematic and random setup uncertainties.

Motion mitigation for lung cancer patients treated with active scanning proton therapy

PURPOSE

Motion interplay can affect the tumor dose in scanned proton beam therapy. This study assesses the ability of rescanning and gating to mitigate interplay effects during lung treatments.

METHODS

The treatments of five lung cancer patients [48 Gy(RBE)/4fx] with varying tumor size (21.1-82.3 cm(3)) and motion amplitude (2.9-30.6 mm) were simulated employing 4D Monte Carlo. The authors investigated two spot sizes (σ ∼ 12 and ∼ 3 mm), three rescanning techniques (layered, volumetric, breath-sampled volumetric) and respiratory gating with a 30% duty cycle.

RESULTS

For 4/5 patients, layered rescanning 6/2 times (for the small/large spot size) maintains equivalent uniform dose within the target >98% for a single fraction. Breath sampling the timing of rescanning is ∼ 2 times more effective than the same number of continuous rescans. Volumetric rescanning is sensitive to synchronization effects, which was observed in 3/5 patients, though not for layered rescanning. For the large spot size, rescanning compared favorably with gating in terms of time requirements, i.e., 2x-rescanning is on average a factor ∼ 2.6 faster than gating for this scenario. For the small spot size however, 6x-rescanning takes on average 65% longer compared to gating. Rescanning has no effect on normal lung V20 and mean lung dose (MLD), though it reduces the maximum lung dose by on average 6.9 ± 2.4/16.7 ± 12.2 Gy(RBE) for the large and small spot sizes, respectively. Gating leads to a similar reduction in maximum dose and additionally reduces V20 and MLD. Breath-sampled rescanning is most successful in reducing the maximum dose to the normal lung.

CONCLUSIONS

Both rescanning (2-6 times, depending on the beam size) as well as gating was able to mitigate interplay effects in the target for 4/5 patients studied. Layered rescanning is superior to volumetric rescanning, as the latter suffers from synchronization effects in 3/5 patients studied. Gating minimizes the irradiated volume of normal lung more efficiently, while breath-sampled rescanning is superior in reducing maximum doses to organs at risk.

Contour-Driven Atlas-Based Segmentation

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images.