Can we predict discordant RECIST 1.1 evaluations in double read clinical trials?

Background

In lung clinical trials with imaging, blinded independent central review with double reads is recommended to reduce evaluation bias and the Response Evaluation Criteria In Solid Tumor (RECIST) is still widely used. We retrospectively analyzed the inter-reader discrepancies rate over time, the risk factors for discrepancies related to baseline evaluations, and the potential of machine learning to predict inter-reader discrepancies.

Materials and methods

We retrospectively analyzed five BICR clinical trials for patients on immunotherapy or targeted therapy for lung cancer. Double reads of 1724 patients involving 17 radiologists were performed using RECIST 1.1. We evaluated the rate of discrepancies over time according to four endpoints: progressive disease declared (PDD), date of progressive disease (DOPD), best overall response (BOR), and date of the first response (DOFR). Risk factors associated with discrepancies were analyzed, two predictive models were evaluated.

Results

At the end of trials, the discrepancy rates between trials were not different. On average, the discrepancy rates were 21.0%, 41.0%, 28.8%, and 48.8% for PDD, DOPD, BOR, and DOFR, respectively. Over time, the discrepancy rate was higher for DOFR than DOPD, and the rates increased as the trial progressed, even after accrual was completed. It was rare for readers to not find any disease, for less than 7% of patients, at least one reader selected non-measurable disease only (NTL). Often the readers selected some of their target lesions (TLs) and NTLs in different organs, with ranges of 36.0-57.9% and 60.5-73.5% of patients, respectively. Rarely (4-8.1%) two readers selected all their TLs in different locations. Significant risk factors were different depending on the endpoint and the trial being considered. Prediction had a poor performance but the positive predictive value was higher than 80%. The best classification was obtained with BOR.

Conclusion

Predicting discordance rates necessitates having knowledge of patient accrual, patient survival, and the probability of discordances over time. In lung cancer trials, although risk factors for inter-reader discrepancies are known, they are weakly significant, the ability to predict discrepancies from baseline data is limited. To boost prediction accuracy, it would be necessary to enhance baseline-derived features or create new ones, considering other risk factors and looking into optimal reader associations.

Systematic Review, Meta-Analysis and Radiomics Quality Score Assessment of CT Radiomics-Based Models Predicting Tumor EGFR Mutation Status in Patients with Non-Small-Cell Lung Cancer

Assessment of the quality and current performance of computed tomography (CT) radiomics-based models in predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small-cell lung carcinoma (NSCLC). Two medical literature databases were systematically searched, and articles presenting original studies on CT radiomics-based models for predicting EGFR mutation status were retrieved. Forest plots and related statistical tests were performed to summarize the model performance and inter-study heterogeneity. The methodological quality of the selected studies was assessed via the Radiomics Quality Score (RQS). The performance of the models was evaluated using the area under the curve (ROC AUC). The range of the Risk RQS across the selected articles varied from 11 to 24, indicating a notable heterogeneity in the quality and methodology of the included studies. The average score was 15.25, which accounted for 42.34% of the maximum possible score. The pooled Area Under the Curve (AUC) value was 0.801, indicating the accuracy of CT radiomics-based models in predicting the EGFR mutation status. CT radiomics-based models show promising results as non-invasive alternatives for predicting EGFR mutation status in NSCLC patients. However, the quality of the studies using CT radiomics-based models varies widely, and further harmonization and prospective validation are needed before the generalization of these models.

Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

Background

In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We sought to document the variability of double reads at baseline, and variabilities across individual readers and lung trials.

Material and methods

We retrospectively analyzed data from five BICR clinical trials evaluating 1720 lung cancer patients treated with immunotherapy or targeted therapy. Fifteen radiologists were involved. The variability was analyzed using a set of 71 features derived from tumor selection, measurements, and disease location. We selected a subset of readers that evaluated ≥50 patients in ≥two trials, to compare individual reader’s selections. Finally, we evaluated inter-trial homogeneity using a subset of patients for whom both readers assessed the exact same disease locations. Significance level was 0.05. Multiple pair-wise comparisons of continuous variables and proportions were performed using one-way ANOVA and Marascuilo procedure, respectively.

Results

Across trials, on average per patient, target lesion (TL) number ranged 1.9 to 3.0, sum of tumor diameter (SOD) 57.1 to 91.9 mm. MeanSOD=83.7 mm. In four trials, MeanSOD of double reads was significantly different. Less than 10% of patients had TLs selected in completely different organs and 43.5% had at least one selected in different organs. Discrepancies in disease locations happened mainly in lymph nodes (20.1%) and bones (12.2%). Discrepancies in measurable disease happened mainly in lung (19.6%). Between individual readers, the MeanSOD and disease selection were significantly different (p<0.001). In inter-trials comparisons, on average per patient, the number of selected TLs ranged 2.1 to 2.8, MeanSOD 61.0 to 92.4 mm. Trials were significantly different in MeanSOD (p<0.0001) and average number of selected TLs (p=0.007). The proportion of patients having one of the top diseases was significantly different only between two trials for lung. Significant differences were observed for all other disease locations (p<0.05).

Conclusions

We found significant double read variabilities at baseline, evidence of reading patterns and a means to compare trials. Clinical trial reliability is influenced by the interplay of readers, patients and trial design.

Differences in sensitivity to new therapies between primary and metastatic breast cancer: A need to stratify the tumor response?

OBJECTIVE

We compared therapeutic response of Varlitinib + Capecitabine (VC) versus Lapatinib + Capecitabine (LC) in patients with human epidermal growth factor receptor 2-positive metastatic breast cancer after trastuzumab therapy by assessing changes in target lesion (TL) diameter and volume per location.

METHODS

We retrospectively analyzed the CT data of the ASLAN001-003 study (NCT02338245). We analyzed TL size and number at each location focusing on therapeutic response from baseline to Week 12. We used TL diameter and volume to conduct an inter-arm comparison of the response according to: RECIST 1.1; stratified per TL location and considering TLs independently. Multiple pairwise intra-arm comparisons of therapeutic responses were performed. Considering TL independently, weighted models were designed by adding weighted mean TL responses grouped by location.

RESULTS

We evaluated 42 patients (88 TL) and 35 patients (74 TL), respectively, at baseline and Week 12. We found reductions in breast TL burden in the VC arm compared to the LC arm (p = 0.002 (diameter), p < 0.001 (volume)). Responses and TL sizes at baseline were not correlated. Explained variabilities of volume change per TL location, patient and patient:TL interaction were 36%, 10% and 4% (VC), and 13%, 1% and 23%, (LC). A test of inter-arm difference of responses yielded p = 0.07 (diameter), and p < 0.001 (volume).

CONCLUSIONS

The therapeutic responses differed across tumors' locations; the magnitude of the differences of responses across the tumors' locations were drug-dependent. Stratified analysis of the response by tumor location improved drug comparisons and is a powerful tool to understand TL heterogeneity.

Actionable insights for managing inter-reader variability of RECIST overall response in lung clinical trials: A retrospective analysis

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Background: To assess drug efficacy in clinical trials with imaging endpoints, the FDA recommends blinded independent central review (BICR) with double reads to ensure robust image interpretation. However, discordance created by double-reading adds burden and costs that stakeholders strive to minimize. Given that selection of tumors at baseline is reported to cause one third of adjudications, we tested a set of risk factors arising from baseline evaluations and trained models likely to predict discrepancies in RECIST responses. Methods: We pooled and retrospectively analyzed data from five lung cancer clinical trials that used RECIST with BICR and double reads including a total of 1720 patients. Firstly, we analyzed the distribution of four kinds of response discrepancies (KoD): progression or date of progression (PD), response or date of response (OR), progression or response (ANY) and best response (BR). We derived discrepancy rates, average time-point of the first occurrence of KoD and the proportion of time-points before KoD out of total time-point number (compared using Marascuilo procedure) as key indicators of the at-risk period of discordance. Secondly, from the baseline evaluations performed by readers, we computed the odds ratios of 32 risk factors for discrepancies including differences in measurements, tumor selection and disease locations. Finally, based on 77 features, we trained a Random Forest (RF) and a deep learning (DL) model to predict KoDs. Results: On average, respectively for PD, OR, ANY and BR, discrepancy rates were 41.5%, 49.1%, 66.3% and 28.7%; number of time-points for first occurrence were 4.6, 2.7, 2.7 and 4.8; and the proportion of time-points before KoD were 30.7%, 24.7%, 33.1% and 23.2% (significantly different). The main risk factors for discrepancies were miss-detection of measurable disease, completely different disease selection, miss-selection of lung tumors and when readers’ difference in sum of diameters was between 10% and 20%. However, associations were weak, with no association when one of the readers selected infrequent diseases (e.g., skin, gastric). DL outperformed RF. Classification performances were generally poor. PD was not predictable. BR performances were positive predictive value: 81.0 [95% CI: 78.8; 83.2], negative predictive value: 73.3 [95% CI: 72.8; 73.8]. Conclusions: The KoDs have different distributions, but all occur in the first third of the patient evaluation defining a risk period. We confirmed the reported association of selection and measurement at baseline with responses' variabilities. However, the associations were weak and did not allow good prediction of the variability in responses. For BICR of lung cancer trials using RECIST, our results support the implementation of a monitoring of variability focusing on the baseline and the beginning of the evaluation of the patients.

The adjudication rates between readers in Blinded Independent Central Review (BICR) of advanced esophageal cancer trials with or without immune checkpoint initiators as first-line therapy

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Background: It is challenging to use RECIST 1.1 for the response assessment in esophageal cancer, because it excludes certain examines such as the use of barium meal and endoscopy. In some esophageal trials, the study protocols also recommend not selecting the primary tumor as a target lesion, because esophageal lesion could be infiltrative in a cavity organ and difficult to measure reliable especially after treatment. Moreover, it can even be more difficult for independent central readers, as they are often blinded to patient clinical symptoms and outcomes. The aim of this study is to analyze a pool of advanced esophageal cancer trials which used RECIST 1.1, and to document the proportion of reader discrepancies, reader performance through monitoring procedures, and to provide suggestions for the reduction of read inconsistency. This study provides benchmarks of reader adjudication rate in novel esophageal cancer therapeutic trials with or without immune checkpoint inhibitors, which will help to trigger corrective actions, such as reader initial training and follow up re-training. Methods: We analyzed 4 esophageal cancer BICR trials that included 1,875 patients (8,501 time-points) involving 14 radiologists. We analyzed the adjudication rate of each trial as well as testing inter-trial differences. The analysis of adjudication allowed to compute trial and reader adjudication rate, readers endorsement rate, root causes of adjudications. Results: Trials had an average adjudication rate of 45.28% [42.60%-47.99%], while readers endorsement rates ranged [23.1%-81.6%]. The differences of target lesion selection (34.4%) and lesion measurement (40.3%) are the two main reasons that led to discordance per adjudicators’ assessment. The difference of new lesion determination and identification of non-target lesion progression contributed 17.8% and 7.5% of the discordance reasons, respectively. Conclusions: We provided benchmark performances for monitoring reader performance in trials with double reads. The discordances of baseline lesion selection and lesion measurement in follow up visits are the main reasons triggering adjudications in esophageal cancer central reading. Appropriate reader training and monitoring are solutions which can not only mitigate a large portion of the commonly encountered reading errors and help to reach more consensus on lesion selection and measurement between readers.

Blinded Independent Central Review (BICR) in New Therapeutic Lung Cancer Trials

BACKGROUND

Double reads in blinded independent central reviews (BICRs) are recommended to control the quality of trials but they are prone to discordances. We analyzed inter-reader discordances in a pool of lung cancer trials using RECIST 1.1.

METHODS

We analyzed six lung cancer BICR trials that included 1833 patients (10,684 time points) involving 17 radiologists. We analyzed the rate of discrepancy of each trial at the time-point and patient levels as well as testing inter-trial differences. The analysis of adjudication made it possible to compute the readers' endorsement rates, the root causes of adjudications, and the proportions of "errors" versus "medically justifiable differences".

RESULTS

The trials had significantly different discrepancy rates both at the time-point (average = 34.3%) and patient (average = 59.2%) levels. When considering only discrepancies for progressive disease, homogeneous discrepancy rates were found with an average of 32.9%, while readers' endorsement rates ranged between 27.7% and 77.8%. Major causes of adjudication were different per trial, with medically justifiable differences being the most common, triggering 74.2% of total adjudications.

CONCLUSIONS

We provide baseline performances for monitoring reader performance in trials with double reads. Intelligent reading system implementation along with appropriate reader training and monitoring are solutions that could mitigate a large portion of the commonly encountered reading errors.

Letter to the editor: "Not all biases are bad: equitable and inequitable biases in machine learning and radiology"

Artificial intelligence algorithms are booming in medicine, and the question of biases induced or perpetuated by these tools is a very important topic. There is a greater risk of these biases in radiology, which is now the primary diagnostic tool in modern treatment. Some authors have recently proposed an analysis framework for social inequalities and the biases at risk of being introduced into future algorithms. In our paper, we comment on the different strategies for resolving these biases. We warn that there is an even greater risk in mixing the notion of equity, the definition of which is socio-political, into the design stages of these algorithms. We believe that rather than being beneficial, this could in fact harm the main purpose of these artificial intelligence tools, which is the care of the patient.

RECIST 1.1 and lesion selection: How to deal with ambiguity at baseline?

Response Evaluation Criteria In Solid Tumors (RECIST) is still the predominant criteria base for assessing tumor burden in oncology clinical trials. Despite several improvements that followed its first publication, RECIST continues to allow readers a lot of freedom in their evaluations. Notably in the selection of tumors at baseline. This subjectivity is the source of many suboptimal evaluations. When starting a baseline analysis, radiologists cannot always identify tumor malignancy with any certainty. Also, with RECIST, some findings can be deemed equivocal by radiologists with no confirmatory ground truth to rely on. In the specific case of Blinded Independent Central Review clinical trials with double reads using RECIST, the selection of equivocal tumors can have two major consequences: inter-reader variability and modified sensitivity of the therapeutic response. Apart from the main causes leading to the selection of an equivocal lesion, due to the uncertainty of the radiological characteristics or due to the censoring of on-site evaluations, several other situations can be described more precisely. These latter involve cases where an equivocal is selected as target or non-target lesions, the management of equivocal lymph nodes and the case of few target lesions. In all cases, awareness of the impact of selecting a non-malignant lesion will lead radiologists to make selections in the most rational way. Also, in clinical trials where the primary endpoint differs between phase 2 (response-related) and phase 3 (progression-related) trials, our impact analysis will help them to devise strategies for the management of equivocal lesions.

Harmonization of radiomic feature distributions: impact on classification of hepatic tissue in CT imaging

OBJECTIVES

Following the craze for radiomic features (RF), their lack of reliability raised the question of the generalizability of classification models. Inter-site harmonization of images therefore becomes a central issue. We compared RF harmonization processing designed to detect liver diseases in CT images.

METHODS

We retrospectively analyzed 76 multi-center portal CT series of non-diseased (NDL) and diseased liver (DL) patients. In each series, we positioned volumes of interest in spleen and liver, then extracted 9 RF (histogram and texture). We evaluated two RF harmonization approaches. First, in each series, we computed the Z-score of liver measurements based on those computed in the spleen. Second, we evaluated the ComBat method according to each imaging center; parameters were computed in the spleen and applied to the liver. We compared RF distributions and classification performances before/after harmonization. We classified NDL versus spleen and versus DL tissues.

RESULTS

The RF distributions were all different between liver and spleen (p < 0.05). The Z-score harmonization outperformed for the detection of liver versus spleen: AUC = 93.1% (p < 0.001). For the detection of DL versus NDL, in a case/control setting, we found no differences between the harmonizations: mean AUC = 73.6% (p = 0.49). Using the whole datasets, the performances were improved using ComBat (p = 0.05) AUC = 82.4% and degraded with Z-score AUC = 67.4% (p = 0.008).

CONCLUSIONS

Data harmonization requires to first focus on data structuring to not degrade the performances of subsequent classifications. Liver tissue classification after harmonization of spleen-based RF is a promising strategy for improving the detection of DL tissue.

KEY POINTS

• Variability of acquisition parameter makes radiomics of CT features non-reproducible. • Data harmonization can help circumvent the inter-site variability of acquisition protocols. • Inter-site harmonization must be carefully implemented and requires designing consistent data sets.

Targeted therapies: How can CT imaging improve evaluations and help understand mechanism of drug action?

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Background: We compared the therapeutic response between Varlitinib plus Capecitabine (VC) and Lapatinib plus Capecitabine (LC) by stratifying changes in tumor’s longest diameter (LD) and volume (VOL) per tumor location in patients with HER2+ metastatic breast cancer after trastuzumab therapy. Methods: We retrospectively analyzed the ASLAN001-003 double-arm trial (NCT02338245). We first tested the intra and inter-arm equivalence in number and size of tumors at each location of the disease.Second, we compared the inter-arm average changes in 1) tumor burden according to RECIST; 2) stratified tumor burden in summing, for each patient, the target lesions from the same organ locations; 3) tumors considered independent but grouped per organ location of the disease.Third, we tested the intra-arm differential responses of pairwise groups of tumor locations: breast-lung, breast-liver, breast-lymph nodes, lung-liver, lung-lymph nodes and liver-lymph nodes. A sensitivity analysis tested the robustness of our results. Results: We followed 74 tumors in 35 patients (14 VC; 21 LC) after 12 weeks of treatment. Primary breast tumors had a larger size than metastasis (p < 0.002). Tumor proportions at each organ location of the disease were not significantly different. The inter-arm difference in changes of tumor burden yielded: p = 0.086 (LD) and p = 0.13 (VOL); in stratifying patients per breast tumors: p = 0.002 (LD) and p < 0.001 (VOL); and for independent breast tumors: p = 0.001 (LD) and p < 0.001 (VOL). We found differential responses in the LC arm for breast-liver (p = 0.007 (VOL)) and Liver-Lymph node (p = 0.06 (VOL)). After outlier’s removal, the inter-arm difference was confirmed for breast tumors (p = 0.004 (LD); p < 0.001 (VOL)) and when considering all tumors as independent (p < 0.01(LD); p = 0.04 (VOL)). The differential Breast-Liver response in the VC arm was confirmed p < 0.05 (LD or VOL). Conclusions: Differential imaging responses were found across treatment arms and tumor locations. The stratification of changes provides new insights into responses of targeted therapies and more accurate drug comparisons. The stratification is a promising approach to better understand therapy mechanisms of action behind tumor heterogeneity.

Mental health status of cancer research center's care givers: should we worry?

The status of mental health of physicians practicing in cancer research centers is evaluated. To date little information is given in research to date concerning the burnout syndrome. Recommendations are made for a better psychological development of caregivers.

Myoma Hot Spot: Tumor-to-Tumor Metastasis of Thyroid Origin into Uterine Leiomyoma

INTRODUCTION

Distant metastases of papillary thyroid cancers are rare. Most common metastatic sites include bone and lung, whereas metastases to brain, eye, breast, liver, kidney, muscle, and skin are infrequent and almost always appear in advanced-stage tumor disease. Metastases to ovary and/or uterus are even scarcer. We report herein a very exceptional case of asymptomatic malignant-to-benign tumor-to-tumor metastasis of thyroid origin into a uterine leiomyoma.

CASE PRESENTATION

We present the case of a 53-year-old female patient who had a previous history of pT1b N0 M0 R0 papillary carcinoma of the lower left thyroid lobe, treated by total thyroidectomy and central lymph node dissection and two successive administrations of radioactive treatment with iodine-131. Six years later, follow-up imaging disclosed an asymptomatic slow-growing 40-mm-long pedicled subserous heterogeneous uterine myoma including a 12-mm hypervascular nodule, which was suspicious for thyroid malignancy on MRI.

DISCUSSION

Histopathology of a hysterectomy specimen disclosed a hypervascular well-limited poorly differentiated trabecular carcinomatous infiltration within the uterine leiomyoma. The immunohistochemical profile of the suspicious nodule was compatible with a thyroid origin.

CONCLUSION

A hypervascular "hot spot" intramyoma nodule was the diagnostic clue in a clinical context of hematogenous tumor spread of thyroid origin (increased thyroglobulin level).

One-bloc percutaneous large biopsy of soft-tissue tumours: feasibility study and possible indications

AIM

To report the early results of the Intact lesion excision system (LES) regarding feasibility, tolerance and efficiency in obtaining soft-tissue tumour samples under ultrasound guidance.

MATERIALS AND METHODS

The feasibility and tolerance of Intact LES procedures under ultrasound guidance were studied prospectively in 15 patients. The procedure was performed on an outpatient basis under local anaesthesia by a single interventional radiologist with 6 years of experience and lasted around 30 min.

RESULTS

The feasibility of the Intact LES for soft-tissue masses was good except when lesions were hard and calcified. Tolerance was good, with median pain experienced during the procedure evaluated at 4.5/10 (SD 2.2) and median post-procedural pain at day 1 evaluated at 1.8/10 (SD 2.5). No major complications were observed; however, for vascularised lesions, one case of acute wound bleeding and two post-procedural haematomas led to delayed pain.

CONCLUSION

Percutaneous biopsy of suspected soft-tissue sarcoma using the LES device under ultrasound guidance is well tolerated and feasible. After a first non-contributing core biopsy, and especially, in the case of lipomatous lesions, it is a valuable option to consider, as is surgical incision biopsy.

CT-Guided Percutaneous Gastrostomy without Preliminary Placement of a Nasogastric Tube

Percutaneous radiologic gastrostomy (PRG) requires preliminary gastric inflation through a nasogastric tube (NGT) to safely perform gastric puncture. However, in case of pharyngeal or esophageal obstruction, NGT placement may be impossible even with a hydrophilic angiography catheter and wire. This brief report describes percutaneous computed tomography (CT)-guided gastrostomy with a 2-stick approach without nasogastric insufflation in 13 patients. Technical success rate was 100% with a mean of 1.8 punctures ± 1.0 to access the gastric lumen. Traversal of the colon and liver with a 22-gauge needle was necessary in 4 and 1 patients, respectively. There were no major complications. Minor complications occurred in 6 patients (46%). CT-guided percutaneous gastrostomy is technically feasible with minimal morbidity.

Focused ultrasound for the treatment of bone metastases: effectiveness and feasibility

Background

To evaluate the effectiveness and feasibility of high-intensity focused ultrasound (HIFU) for the treatment of bone metastases.

Methods

A single-center prospective study was made involving 17 consecutive patients with symptomatic bone metastases. Patients were treated by Focused Ultrasound (FUs) performed with magnetic resonance (MR) guidance. Surgical treatment or radiotherapy treatment was not indicated for patients who underwent FUs. Lesions were located in the appendicular and axial skeleton and consisted of secondary symptomatic lesions. The clinical course of pain was evaluated using the Visual Analog Scale (VAS) before treatment, at 1 week, and at 1 month after treatment and the Oral Morphine Equivalent Daily Dose (OMEDD) was also recorded. We used Wilcoxon signed rank test to assess change in patient pain (R CRAN software V 3.1.1).

Results

We observed a significant decrease in the pain felt by patients between pre- procedure and 1 week post-procedure (p = 2.9.10-4), and pre-procedure and 1 month post-procedure (p = 3.10-4). The proportion of responders according to the International Bone Metastases Consensus Working Party was: Partial Response 50% (8/16) and Complete Response 37.5% (6/16).

Conclusions

HIFU under MR-guidance seems to be an effective and safe procedure in the treatment of symptomatic bone lesions for patients suffering from metastatic disease. A significant decrease of patient pain was observed.

Trial registration

NCT01091883. Registered 24 March 2010. Level of evidence: Level 3.

A review of existing and potential computer user interfaces for modern radiology

Abstract

The digitalization of modern imaging has led radiologists to become very familiar with computers and their user interfaces (UI). New options for display and command offer expanded possibilities, but the mouse and keyboard remain the most commonly utilized, for usability reasons. In this work, we review and discuss different UI and their possible application in radiology. We consider two-dimensional and three-dimensional imaging displays in the context of interventional radiology, and discuss interest in touchscreens, kinetic sensors, eye detection, and augmented or virtual reality. We show that UI design specifically for radiologists is key for future use and adoption of such new interfaces. Next-generation UI must fulfil professional needs, while considering contextual constraints.

Teaching Points

• The mouse and keyboard remain the most utilized user interfaces for radiologists.

• Touchscreen, holographic, kinetic sensors and eye tracking offer new possibilities for interaction.

• 3D and 2D imaging require specific user interfaces.

• Holographic display and augmented reality provide a third dimension to volume imaging.

• Good usability is essential for adoption of new user interfaces by radiologists.

How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes

Objective

To assess the reliability of ADC measurements in vitro and in cervical lymph nodes of healthy volunteers.

Methods

We used a GE 1.5 T MRI scanner and a first ice-water phantom according to recommendations released by the Quantitative Imaging Biomarker Alliance (QIBA) for assessing ADC against reference values. We analysed the target size effect by using a second phantom made of six inserted spheres with diameters ranging from 10 to 37 mm. Thirteen healthy volunteers were also scanned to assess the inter- and intra-observer reproducibility of volumetric ADC measurements of cervical lymph nodes.

Results

On the ice-water phantom, the error in ADC measurements was less than 4.3 %. The spatial bias due to the non-linearity of gradient fields was found to be 24 % at 8 cm from the isocentre. ADC measure reliability decreased when addressing small targets due to partial volume effects (up to 12.8 %). The mean ADC value of cervical lymph nodes was 0.87.10^-3 ± 0.12.10^-3 mm²/s with a good intra-observer reliability. Inter-observer reproducibility featured a bias of -5.5 % due to segmentation issues.

Conclusion

ADC is a potentially important imaging biomarker in oncology; however, variability issues preclude its broader adoption. Reliable use of ADC requires technical advances and systematic quality control.

Key Points

• ADC is a promising quantitative imaging biomarker.

• ADC has a fair inter-reader variability and good intra-reader variability.

• Partial volume effect, post-processing software and non-linearity of scanners are limiting factors.

• No threshold values for detecting cervical lymph node malignancy can be drawn.

Electronic supplementary material

The online version of this article (10.1007/s00330-017-5265-2) contains supplementary material, which is available to authorized users.

Computer tomography-based body surface area evaluation for drug dosage: Quantitative radiology versus anthropomorphic evaluation

OBJECTIVE

The measure of body surface area (BSA) is a standard for planning optimal dosing in oncology. This index is derived from a model having questionable performances. In this study, we proposed measurement of BSA from whole body CT images (iBSA). We tested the reliability of iBSA assessments and simulated the impact of our approach on patient chemotherapy dosage planning.

METHODS

We first evaluated accuracy and precision of iBSA in measuring 14 phantom and 11 CT test-retest images.Secondly, we retrospectively analyzed 26 whole body PET-CT scans to evaluate inter-method variability between iBSA and the most used anthropomorphic models, notably the "Du Bois and Du Bois" model. Finally, we simulated the impact on chemotherapy dose planning of capecitabine based on iBSA.

RESULTS

Precision and accuracy of iBSA measurement featured a standard deviation of 1.11% and a mean error of 1.53%. Inter-method variability between iBSA and "Du Bois and Du Bois" assessment featured a standard deviation of 4.11% leading to a reclassification rate of capecitabine of 32.5%.

CONCLUSIONS

iBSA could help the oncologist in standardizing assessments for chemotherapy planning. iBSA could also be relevant for applications such as comprehensive body composition and provide a sensitive measurement for changes related to nutritional intake or other metabolism.

Current concepts in tumor imaging with whole-body MRI with diffusion imaging (WB-MRI-DWI) in multiple myeloma and lymphoma

Whole-body MRI (WB-MRI) with diffusion-weighted imaging (DWI) can now be used to stage and restage multiple myeloma (MM) and lymphoma. Magnetic resonance imaging (MRI) is the standard tool to detect BM involvement (BMI). The 2016 diagnostic criteria of the International Myeloma Working Group identify WB-MRI and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) as the most sensitive imaging techniques for detecting skeletal and extra-skeletal MM invasion, respectively. Preliminary findings have also shown that WB-MRI is better than CT and equal to PET/CT in staging aggressive lymphoma and Hodgkin lymphoma, whereas MRI is better for diagnosing BMI in patients with low-grade lymphoma. Signal intensity (SI) and the apparent diffusion coefficient (ADC) are useful metrics to quantify the chemotherapy response in WB-MRI.

Interest of systematic tomosynthesis (3D mammography) with synthetic 2D mammography in breast cancer screening

Full field digital mammography (FFDM) is the current pillar of breast cancer screening program. However, the emerging technique digital breast tomosynthesis (DBT) has demonstrated a significant increase in the sensibility of cancer detection in several large cohort trials. DBT is particularly helpful for young patients, dense breasts and soft masses due to its ability to reduce overlapping of tissue. In such a population of women, radiologists are more confident and the recall rates are reduced together with a higher positive predictive value. To reduce the breast absorbed doses of screened women and facilitate the workflow, a synthetized two-dimensional (2D) digital mammography (sDM) is obtained from DBT to replace the FFDM. No significant differences regarding detection of anomalies have been reported with respect to FFDM. These results validate a modern strategy for breast cancer screening supported by two views of DBT with sDM. In terms of mean absorbed doses, this strategy is around 1.5 mGy/view and almost equivalent to FFDM. In Europe, major limitations to such evolution are public health policies especially agreements and reimbursement for the technique being used in organized screening.

Estimation of spinopelvic muscles' volumes in young asymptomatic subjects: a quantitative analysis

PURPOSE

Muscles have been proved to be a major component in postural regulation during pathological evolution or aging. Particularly, spinopelvic muscles are recruited for compensatory mechanisms such as pelvic retroversion, or knee flexion. Change in muscles' volume could, therefore, be a marker of greater postural degradation. Yet, it is difficult to interpret spinopelvic muscular degradation as there are few reported values for young asymptomatic adults to compare to. The objective was to provide such reference values on spinopelvic muscles. A model predicting the muscular volume from reduced set of MRI segmented images was investigated.

METHODS

A total of 23 asymptomatic subjects younger than 24 years old underwent an MRI acquisition from T12 to the knee. Spinopelvic muscles were segmented to obtain an accurate 3D reconstruction, allowing precise computation of muscle's volume. A model computing the volume of muscular groups from less than six MRI segmented slices was investigated.

RESULTS

Baseline values have been reported in tables. For all muscles, invariance was found for the shape factor [ratio of volume over (area times length): SD < 0.04] and volume ratio over total volume (SD < 1.2 %). A model computing the muscular volume from a combination of two to five slices has been evaluated. The five-slices model prediction error (in  % of the real volume from 3D reconstruction) ranged from 6 % (knee flexors and extensors and spine flexors) to 11 % (spine extensors).

CONCLUSION

Spinopelvic muscles' values for a reference population have been reported. A new model predicting the muscles' volumes from a reduced set of MRI slices is proposed. While this model still needs to be validated on other populations, the current study appears promising for clinical use to determine, quantitatively, the muscular degradation.

Changes of lung tumour volume on CT - prediction of the reliability of assessments

Background

For oncological evaluations, quantitative radiology gives clinicians significant insight into patients’ response to therapy. In regard to the Response Evaluation Criteria in Solid Tumours (RECIST), the classification of disease evolution partly consists in applying thresholds to the measurement of the relative change of tumour. In the case of tumour volumetry, response thresholds have not yet been established. This study proposes and validates a model for calculating thresholds for the detection of minimal tumour change when using the volume of pulmonary lesions on CT as imaging biomarker.

Methods

Our work is based on the reliability analysis of tumour volume measurements documented by the Quantitative Imaging Biomarker Alliance. Statistics of measurements were entered into a multi-parametric mathematical model of the relative changes derived from the Geary-Hinkley transformation. The consistency of the model was tested by comparing modelled thresholds against Monte Carlo simulations of tumour volume measurements with additive random error. The model has been validated by repeating measurements on real patient follow ups.

Results

For unchanged tumour volume, relying on a normal distribution of error, the agreement between model and simulations featured a type I error of 5.25 %. Thus, we established that a threshold of 35 % of volume reduction corresponds to a partial response (PR) and a 55 % volume increase corresponds to progressive disease (PD). Changes between −35 and +55 % are categorized as stable disease (SD). Tested on real clinical data, 97.1 % [95.7; 98.0] of assessments fall into the range of variability predicted by our model of confidence interval.

Conclusions

Our study indicates that the Geary Hinkley model, using published statistics, is appropriate to predict response thresholds for the volume of pulmonary lesions on CT.

Primary multicentric angiosarcoma of bone: true entity or metastases from an unknown primary? Value of comparative genomic hybridization on paraffin embedded tissues

Multicentric primary angiosarcoma of bone has been described as a distinct entity from bone metastases from angiosarcoma. Bone angiosarcoma accounts for less than 1% of sarcomas. It has dismal prognosis overall, but the multicentric expression does not confer worse prognosis. We describe the case of an old male with bone angiosarcoma of the extremities with multicentric presentation. He soon after had soft tissue angiosarcoma of the head and neck. Histology and immunohistochemistry were consistent with the diagnosis of high-grade angiosarcoma. Comparative genomic hybridization on paraffin-embedded samples of the bone and head and neck samples suggested additional abnormalities in the bone fragment, thus suggesting than bone lesions were indeed metastatic from his head and neck angiosarcoma; although these preliminary analyses warrant confirmation in other similar rare cases. The patient died after 3 years of relapsed acute leukemia with progressive angiosarcoma.

Determination of thresholds for the assessment of response to therapy relying on volume-based tumor burden in pulmonary CT images

e18508

Background: Image-based biomarkers play an increasing role in the assessment of response to therapy. The widely adopted Response Evaluation Criteria in Solid Tumor (RECIST) mainly rely on the assessment of the Longest Axial Diameter (LAD) of tumors. A growing community suggests that quantifying the tumor volume addresses some of the RECIST limitations. However no consensus has yet emerged regarding the applicable thresholds classifying volume-based response. This study aims at determining such threshold values for tumors observable in pulmonary CT images. Methods: Our study is based on published data from the Quantitative Imaging Biomarker Alliance (QIBA) which reports a 15% variability in measuring the tumor volume. We analyzed additional clinical data in a retrospective study involving 10 patients with Non-Small Cell Lung Cancer (NSCLC), followed over 7 time points in average with CT. 2 expert radiologists and 5 imaging scientists measured the volume of each tumor at each time point. Response evaluation was modelled according to statistical inference of the ratio of two longitudinal measurements by the Geary-Hinkley (GH) transformation. We hypothesised a normal distribution of the measurements. Results: The study confirmed the previously published 15% variability in measuring tumor volume. From our data, the GH transformation appeared suitable to infer the evaluation while considering a normal distribution of the variability.We found that, using the volume of lesions, a tumor burden reduction corresponds to a decrease of at least -35 %, whereas a tumor burden growth is associated with an increase of at least +55%. These thresholds featured a 5% type I error. Applying the model to clinical data, we confirmed the impact on inter-reader agreement. Conclusions: Based on a well established evaluation of the variability of measurement and relying on an analytical model, we determined thresholds required to classify patient’s response to treatment when monitoring the volume of lesions. Our approach provides a couple of threshold values for given precisions of measurements and Type I error, making our approach generic and applicable to other longitudinal evaluations.

Reliability of imaging biomarkers for response assessment in advanced lung cancer: Influence of expertise and automation

e13547

Background: Image-based biomarkers play an important role in the assessment of the response to therapy. The value of imaging biomarkers relies on their reproducibility, which depends on the reviewer and on the measuring system. This study aims at evaluating the impact of readers’ expertise and automation of measurements. Methods: A retrospective study was performed on 10 patients with at least one Non-Small Cell Lung Cancer (NSCLC) lesion, and followed over time (7 time points in average) with Computed Tomography (CT). 2 expert radiologists (ERs) and 5 imaging scientists (ISs) measured the Longest Axial Diameter (LAD) and the volume (VOL) of each lesion at each time point. ERs and ISs segmented the lesions by using a proprietary software providing semi-automatic segmentation processing with manual adjustment. ISs performed an additional session using manual segmentation tools only. From each segmentation, VOL and LAD were automatically computed. The variability of the measurements was calculated by using standard statistics. The response to treatment was assessed according to RECIST thresholds for LAD and with +/-30% thresholds for volume. The inter-reader agreement was measured trough the Kappa coefficient. Finally, the reviewing time with and without automation was analyzed. Results: The use of automated tools by ISs reduced the standard deviation of LAD difference from 10.7% to 8.4%. The inter-reader agreement improved Kappa from 0.57 to 0.68 for LAD, and from 0.52 to 0.69 for VOL. The automation reduced the reviewing time by a factor 4 with respect to the manual assessment. No significant differences in variability were found between ISs and the first ER, but significant differences were observed with respect to the second ER. Conclusions: In a RECIST context, automation improved significantly inter-reader agreement. When using volume as a biomarker, automation not only improved the inter-reader agreement, but also decreased notably the reviewing time. No evidence was found about the influence of the expertise on the volume measurement. The difference in the lesions interpretation by the experts is a relevant factor to account for.