Measurement Matters: A Metrological Approach to Renal Preimplantation Biopsy Evaluation to Address Uncertainty in Organ Selection.

Background: Preimplantation biopsy combines measurements of injury into a composite index to inform organ acceptance. The uncertainty in these measurements remains poorly characterized, raising concerns variability may contribute to inappropriate clinical decisions. Methods: We adopted a metrological approach to evaluate biopsy score reliability. Variability was assessed by performing repeat biopsies (n = 293) on discarded allografts (n = 16) using 3 methods (core, punch, and wedge). Uncertainty was quantified using a bootstrapping analysis. Observer effects were controlled by semi-blinded scoring, and the findings were validated by comparison with standard glass evaluation. Results: The surgical method strongly determined the size (core biopsy area 9.04 mm2, wedge 37.9 mm2) and, therefore, yield (glomerular yield r = 0.94, arterial r = 0.62) of each biopsy. Core biopsies yielded inadequate slides most frequently. Repeat biopsy of the same kidney led to marked variation in biopsy scores. In 10 of 16 cases, scores were contradictory, crossing at least 1 decision boundary (ie, to transplant or to discard). Bootstrapping demonstrated significant uncertainty associated with single-slide assessment; however, scores were similar for paired kidneys from the same donor. Conclusions: Our investigation highlights the risks of relying on single-slide assessment to quantify organ injury. Biopsy evaluation is subject to uncertainty, meaning each slide is better conceptualized as providing an estimate of the kidney's condition rather than a definitive result. Pooling multiple assessments could improve the reliability of biopsy analysis, enhancing confidence. Where histological quantification is necessary, clinicians should seek to develop new protocols using more tissue and consider automated methods to assist pathologists in delivering analysis within clinical time frames.

Patient-specific dosimetry for intracavitary 32P-chromic phosphate colloid therapy of cystic brain tumours.

PURPOSE: (32)P-chromic phosphate colloid treatments of astrocytoma and craniopharyngioma cystic brain tumours in paediatric patients are conventionally based on a sphere model under the assumption of uniform uptake. The aims of this study were to determine the distribution of the absorbed dose delivered by (32)P on a patient-specific basis and to evaluate the accuracy with which this can be predicted from a pretherapy administration of (99m)Tc-Sn colloid. METHODS: Three patients were treated with (32)P-chromic phosphate colloid following (99m)Tc-Sn colloid administrations. Convolution dosimetry was performed using pretherapy and posttherapy sequential SPECT imaging, and verified with EGSnrc Monte Carlo radiation transport simulations. Mean absorbed doses to the cyst wall and dose-volume histograms were also calculated and compared with those obtained by the sphere model approach. RESULTS: Highly nonuniform uptake distributions of both the (99m)Tc and (32)P colloids were observed and characterized by dose-volume histograms to the cyst wall. Mean absorbed doses delivered to the cyst wall, obtained with the convolution method, were on average 21 % (SD 18 %) and 50 % (SD 30 %) lower than those predicted by the (99m)Tc distribution and the uniform assumption of the sphere model, respectively. CONCLUSION: Absorbed doses delivered to the cyst wall by (32)P are more accurately predicted from image-based patient-specific convolution dosimetry than from simple sphere models. These results indicate the necessity to perform personalized treatment planning and verification for intracavitary irradiation of cystic brain tumours treated with radiocolloids. Patient-specific dosimetry can be used to guide the frequency and levels of repeated administrations and would facilitate data collection and comparison to support the multicentre trials necessary to progress this therapy.

A Framework for User-Configurable Data Quality Assurance of Electronic Patient Records.

Electronic Patient Records (EPRs) are valuable data resources for clinical and operational research. The heterogeneity of medical software coupled with the changing data formats and long lifespan of the patient datasets stored in EPRs results in data inconsistencies that hinder operational activities and increase personnel efforts for data lookup and cleaning. This study presents an approach for automated data quality reporting that was developed and tested within a real-world hospital setting at Royal Surrey County Hospital NHS Foundation Trust in 2020. 81 data quality tests configurable via spreadsheets were defined and executed to yield standardised human-readable reports in comma-separated value format. The data evaluation and reporting routines provided manyfold improvement over existing data quality reporting mechanisms.

The need for measurement science in digital pathology.

Background: Pathology services experienced a surge in demand during the COVID-19 pandemic. Digitalisation of pathology workflows can help to increase throughput, yet many existing digitalisation solutions use non-standardised workflows captured in proprietary data formats and processed by black-box software, yielding data of varying quality. This study presents the views of a UK-led expert group on the barriers to adoption and the required input of measurement science to improve current practices in digital pathology. Methods: With an aim to support the UK's efforts in digitalisation of pathology services, this study comprised: (1) a review of existing evidence, (2) an online survey of domain experts, and (3) a workshop with 42 representatives from healthcare, regulatory bodies, pharmaceutical industry, academia, equipment, and software manufacturers. The discussion topics included sample processing, data interoperability, image analysis, equipment calibration, and use of novel imaging modalities. Findings: The lack of data interoperability within the digital pathology workflows hinders data lookup and navigation, according to 80% of attendees. All participants stressed the importance of integrating imaging and non-imaging data for diagnosis, while 80% saw data integration as a priority challenge. 90% identified the benefits of artificial intelligence and machine learning, but identified the need for training and sound performance metrics.Methods for calibration and providing traceability were seen as essential to establish harmonised, reproducible sample processing, and image acquisition pipelines. Vendor-neutral data standards were seen as a "must-have" for providing meaningful data for downstream analysis. Users and vendors need good practice guidance on evaluation of uncertainty, fitness-for-purpose, and reproducibility of artificial intelligence/machine learning tools. All of the above needs to be accompanied by an upskilling of the pathology workforce. Conclusions: Digital pathology requires interoperable data formats, reproducible and comparable laboratory workflows, and trustworthy computer analysis software. Despite high interest in the use of novel imaging techniques and artificial intelligence tools, their adoption is slowed down by the lack of guidance and evaluation tools to assess the suitability of these techniques for specific clinical question. Measurement science expertise in uncertainty estimation, standardisation, reference materials, and calibration can help establishing reproducibility and comparability between laboratory procedures, yielding high quality data and providing higher confidence in diagnosis.

Building confidence in digital health through metrology.

Healthcare is increasingly and routinely generating large volumes of data from different sources, which are difficult to handle and integrate. Confidence in data can be established through the knowledge that the data are validated, well-curated and with minimal bias or errors. As the National Measurement Institute of the UK, the National Physical Laboratory (NPL) is running an interdisciplinary project on digital health data curation. The project addresses one of the key challenges of the UK's Measurement Strategy, to provide confidence in the intelligent and effective use of data. A workshop was organised by NPL in which important stakeholders from NHS, industry and academia outlined the current and future challenges in healthcare data curation. This paper summarises the findings of the workshop and outlines NPL's views on how a metrological approach to the curation of healthcare data sets could help solve some of the important and emerging challenges of utilising healthcare data.

Primary Care Prostate Cancer Case Ascertainment.

Although routine healthcare data are not collected for research, they are increasingly used in epidemiology and are key real-world evidence for improving healthcare. This study presents a method to identify prostate cancer cases from a large English primary care database. 19,619 (1.3%) men had a code for prostate cancer diagnosis. Codes for medium and high Gleason grading enabled identification of additional 94 (0.5%) cases. Many studies do not report codes used to identify patients, and if published, the lists of codes differ from study to study. This can lead to poor research reproducibility and hinder validation. This work demonstrates that carefully developed comprehensive lists of clinical codes can be used to identify prostate cancer; and that approaches that do not solely rely on clinical codes such as ontologies or data linkage should also be considered.

Associations between voxel-level accumulated dose and rectal toxicity in prostate radiotherapy.

BACKGROUND AND PURPOSE: Associations between dose and rectal toxicity in prostate radiotherapy are generally poorly understood. Evaluating spatial dose distributions to the rectal wall (RW) may lead to improvements in dose-toxicity modelling by incorporating geometric information, masked by dose-volume histograms. Furthermore, predictive power may be strengthened by incorporating the effects of interfraction motion into delivered dose calculations.Here we interrogate 3D dose distributions for patients with and without toxicity to identify rectal subregions at risk (SRR), and compare the discriminatory ability of planned and delivered dose. MATERIAL AND METHODS: Daily delivered dose to the rectum was calculated using image guidance scans, and accumulated at the voxel level using biomechanical finite element modelling. SRRs were statistically determined for rectal bleeding, proctitis, faecal incontinence and stool frequency from a training set (n = 139), and tested on a validation set (n = 47). RESULTS: SRR patterns differed per endpoint. Analysing dose to SRRs improved discriminative ability with respect to the full RW for three of four endpoints. Training set AUC and OR analysis produced stronger toxicity associations from accumulated dose than planned dose. For rectal bleeding in particular, accumulated dose to the SRR (AUC 0.76) improved upon dose-toxicity associations derived from planned dose to the RW (AUC 0.63). However, validation results could not be considered significant. CONCLUSIONS: Voxel-level analysis of dose to the RW revealed SRRs associated with rectal toxicity, suggesting non-homogeneous intra-organ radiosensitivity. Incorporating spatial features of accumulated delivered dose improved dose-toxicity associations. This may be an important tool for adaptive radiotherapy in the future.

Anatomical change during radiotherapy for head and neck cancer, and its effect on delivered dose to the spinal cord.

BACKGROUND AND PURPOSE: The impact of weight loss and anatomical change during head and neck (H&N) radiotherapy on spinal cord dosimetry is poorly understood, limiting evidence-based adaptive management strategies. MATERIALS AND METHODS: 133 H&N patients treated with daily mega-voltage CT image-guidance (MVCT-IG) on TomoTherapy, were selected. Elastix software was used to deform planning scan SC contours to MVCT-IG scans, and accumulate dose. Planned (DP) and delivered (DA) spinal cord D2% (SCD2%) were compared. Univariate relationships between neck irradiation strategy (unilateral vs bilateral), T-stage, N-stage, weight loss, and changes in lateral separation (LND) and CT slice surface area (SSA) at C1 and the superior thyroid notch (TN), and ΔSCD2% [(DA - DP) D2%] were examined. RESULTS: The mean value for (DA - DP) D2% was -0.07 Gy (95%CI -0.28 to 0.14, range -5.7 Gy to 3.8 Gy), and the mean absolute difference between DP and DA (independent of difference direction) was 0.9 Gy (95%CI 0.76-1.04 Gy). Neck treatment strategy (p = 0.39) and T-stage (p = 0.56) did not affect ΔSCD2%. Borderline significance (p = 0.09) was seen for higher N-stage (N2-3) and higher ΔSCD2%. Mean reductions in anatomical metrics were substantial: weight loss 6.8 kg; C1LND 12.9 mm; C1SSA 12.1 cm2; TNLND 5.3 mm; TNSSA 11.2 cm2, but no relationship between weight loss or anatomical change and ΔSCD2% was observed (all r2 < 0.1). CONCLUSIONS: Differences between delivered and planned spinal cord D2% are small in patients treated with daily IG. Even patients experiencing substantial weight loss or anatomical change during treatment do not require adaptive replanning for spinal cord safety.

Automated customized retrieval of radiotherapy data for clinical trials, audit and research.

OBJECTIVE: To enable fast and customizable automated collection of radiotherapy (RT) data from tomotherapy storage. METHODS: Human-readable data maps (TagMaps) were created to generate DICOM-RT (Digital Imaging and Communications in Medicine standard for Radiation Therapy) data from tomotherapy archives, and provided access to "hidden" information comprising delivery sinograms, positional corrections and adaptive-RT doses. RESULTS: 797 data sets totalling 25,000 scans were batch-exported in 31.5 h. All archived information was restored, including the data not available via commercial software. The exported data were DICOM-compliant and compatible with major commercial tools including RayStation, Pinnacle and ProSoma. The export ran without operator interventions. CONCLUSION: The TagMap method for DICOM-RT data modelling produced software that was many times faster than the vendor's solution, required minimal operator input and delivered high volumes of vendor-identical DICOM data. The approach is applicable to many clinical and research data processing scenarios and can be adapted to recover DICOM-RT data from other proprietary storage types such as Elekta, Pinnacle or ProSoma. Advances in knowledge: A novel method to translate data from proprietary storage to DICOM-RT is presented. It provides access to the data hidden in electronic archives, offers a working solution to the issues of data migration and vendor lock-in and paves the way for large-scale imaging and radiomics studies.

Long-term tumour control in sacral chordoma following high-dose palliative image-guided intensity-modulated radiotherapy (IG-IMRT).

Chordomas can present a challenge to the radiation oncologist and surgeon owing to the proximity to neurological structures. We describe a case of long-term tumour control in a chordoma of the lumbar spine following high-dose palliative radiotherapy. Image-guided intensity-modulated radiotherapy with photons provided a good solution to deliver 65 Gy to the tumour in a technically challenging case, and local control has been sustained over a period of years.

Applying physical science techniques and CERN technology to an unsolved problem in radiation treatment for cancer: the multidisciplinary 'VoxTox' research programme.

The VoxTox research programme has applied expertise from the physical sciences to the problem of radiotherapy toxicity, bringing together expertise from engineering, mathematics, high energy physics (including the Large Hadron Collider), medical physics and radiation oncology. In our initial cohort of 109 men treated with curative radiotherapy for prostate cancer, daily image guidance computed tomography (CT) scans have been used to calculate delivered dose to the rectum, as distinct from planned dose, using an automated approach. Clinical toxicity data have been collected, allowing us to address the hypothesis that delivered dose provides a better predictor of toxicity than planned dose.

Recalculation of dose for each fraction of treatment on TomoTherapy.

OBJECTIVE: The VoxTox study, linking delivered dose to toxicity requires recalculation of typically 20-37 fractions per patient, for nearly 2000 patients. This requires a non-interactive interface permitting batch calculation with multiple computers. METHODS: Data are extracted from the TomoTherapy(®) archive and processed using the computational task-management system GANGA. Doses are calculated for each fraction of radiotherapy using the daily megavoltage (MV) CT images. The calculated dose cube is saved as a digital imaging and communications in medicine RTDOSE object, which can then be read by utilities that calculate dose-volume histograms or dose surface maps. The rectum is delineated on daily MV images using an implementation of the Chan-Vese algorithm. RESULTS: On a cluster of up to 117 central processing units, dose cubes for all fractions of 151 patients took 12 days to calculate. Outlining the rectum on all slices and fractions on 151 patients took 7 h. We also present results of the Hounsfield unit (HU) calibration of TomoTherapy MV images, measured over an 8-year period, showing that the HU calibration has become less variable over time, with no large changes observed after 2011. CONCLUSION: We have developed a system for automatic dose recalculation of TomoTherapy dose distributions. This does not tie up the clinically needed planning system but can be run on a cluster of independent machines, enabling recalculation of delivered dose without user intervention. ADVANCES IN KNOWLEDGE: The use of a task management system for automation of dose calculation and outlining enables work to be scaled up to the level required for large studies.

Accumulated dose to the rectum, measured using dose-volume histograms and dose-surface maps, is different from planned dose in all patients treated with radiotherapy for prostate cancer.

OBJECTIVE: We sought to calculate accumulated dose (DA) to the rectum in patients treated with radiotherapy for prostate cancer. We were particularly interested in whether dose-surface maps (DSMs) provide additional information to dose-volume histograms (DVHs). METHODS: Manual rectal contours were obtained for kilovoltage and daily megavoltage CT scans for 10 participants from the VoxTox study (380 scans). Daily delivered dose recalculation was performed using a ray-tracing algorithm. Delivered DVHs were summated to create accumulated DVHs. The rectum was considered as a cylinder, cut and unfolded to produce daily delivered DSMs; these were summated to produce accumulated DSMs. RESULTS: Accumulated dose-volumes were different from planned in all participants. For one participant, all DA levels were higher and all volumes were larger than planned. For four participants, all DA levels were lower and all volumes were smaller than planned. For each of these four participants, ≥1% of pixels on the accumulated DSM received ≥5 Gy more than had been planned. CONCLUSION: Differences between accumulated and planned dose-volumes were seen in all participants. DSMs were able to identify differences between DA and planned dose that could not be appreciated from the DVHs. Further work is needed to extract the dose data embedded in the DSMs. These will be correlated with toxicity as part of the VoxTox Programme. ADVANCES IN KNOWLEDGE: DSMs are able to identify differences between DA and planned dose that cannot be appreciated from DVHs alone and should be incorporated into future studies investigating links between DA and toxicity.