61 research outputs found

    MRI and PET/MRI in hematologic malignancies

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    The role of MRI differs considerably between the three main groups of hematological malignancies: lymphoma, leukemia, and myeloma. In myeloma, whole-body MRI (WB-MRI) is recognized as a highly sensitive test for the assessment of myeloma, and is also endorsed by clinical guidelines, especially for detection and staging. In lymphoma, WB-MRI is presently not recommended, and merely serves as an alternative technique to the current standard imaging test, [18F]FDG-PET/CT, especially in pediatric patients. Even for lymphomas with variable FDG avidity, such as extranodal mucosa-associated lymphoid tissue lymphoma (MALT), contrast-enhanced computed tomography (CT), but not WB-MRI, is presently recommended, despite the high sensitivity of diffusion-weighted MRI and its ability to capture treatment response that has been reported in the literature. In leukemia, neither MRI nor any other cross-sectional imaging test (including positron emission tomography [PET]) is currently recommended outside of clinical trials. This review article discusses current clinical applications as well as the main research topics for MRI, as well as PET/MRI, in the field of hematological malignancies, with a focus on functional MRI techniques such as diffusion-weighted imaging and dynamic contrast-enhanced MRI, on the one hand, and novel, non-FDG PET imaging probes such as the CXCR4 radiotracer [68Ga]Ga-Pentixafor and the amino acid radiotracer [11C]methionine, on the other hand. Level of Evidence: 5. Technical Efficacy Stage: 3

    Primary retroperitoneal soft tissue sarcoma: Imaging appearances, pitfalls and diagnostic algorithm.

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    Although retroperitoneal sarcomas are rare tumours, they can be encountered by a wide variety of clinicians as they can be incidental findings on imaging or present with non specific symptoms and signs. Surgical resection can offer hope of cure and patient outcomes are improved when patients are managed in high-volume specialist centers. Failure to recognize retroperitoneal sarcomas on imaging can lead to inappropriate management in inexperienced centers. Therefore it is critical that a diagnosis of retroperitoneal sarcoma should be considered in the differential diagnosis of a retroperitoneal mass with prompt referral to a soft tissue sarcoma unit. In particular, the most common retroperitoneal sarcoma subtypes, liposarcoma and leiomyosarcoma, have characteristic imaging appearances which are discussed. This review therefore aims to set the context and guide clinicians through a diagnostic pathway for retroperitoneal masses in adults which arise extrinsic to the solid abdominal viscera

    Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

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    BACKGROUND: The aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patients with clear cell renal cell carcinoma (ccRCC) and demonstrate the impact of novel feature selection strategies and sub-segmentations on model interpretability. METHODS: Contrast-enhanced CT scans from the first 101 patients recruited to the TRACERx Renal Cancer study (NCT03226886) were used to derive radiomics classification models to predict 20 molecular, histopathology and clinical target variables. Manual 3D segmentation was used in conjunction with automatic sub-segmentation to generate radiomics features from the core, rim, high and low enhancing sub-regions, and the whole tumour. Comparisons were made between two classification model pipelines: a Conventional pipeline reflecting common radiomics practice, and a Proposed pipeline including two novel feature selection steps designed to improve model interpretability. For both pipelines nested cross-validation was used to estimate prediction performance and tune model hyper-parameters, and permutation testing was used to evaluate the statistical significance of the estimated performance measures. Further model robustness assessments were conducted by evaluating model variability across the cross-validation folds. RESULTS: Classification performance was significant (p  0.1. Five of these targets (necrosis on histology, presence of renal vein invasion, overall histological stage, linear evolutionary subtype and loss of 9p21.3 somatic alteration marker) had AUROC > 0.8. Models derived using the Proposed pipeline contained fewer feature groups than the Conventional pipeline, leading to more straightforward model interpretations without loss of performance. Sub-segmentations lead to improved performance and/or improved interpretability when predicting the presence of sarcomatoid differentiation and tumour stage. CONCLUSIONS: Use of the Proposed pipeline, which includes the novel feature selection methods, leads to more interpretable models without compromising prediction performance. TRIAL REGISTRATION: NCT03226886 (TRACERx Renal

    Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

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    Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens.Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667).Results: Upper and lower 95% limits of agreement were 7.1 and −6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = −0.42, p = 0.01, 95% confidence interval (CI) −0.22 to −0.59 for ADC; r = −0.45, p = 0.005, 95% CI −0.25 to −0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10−7, 95% CI 0.69–0.86).Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas

    Daratumumab, Cyclophosphamide, Bortezomib, Lenalidomide, and Dexamethasone as Induction and Extended Consolidation Improves Outcome in Ultra-High-Risk Multiple Myeloma

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    Purpose: The multicenter OPTIMUM (MUKnine) phase II trial investigated daratumumab, low-dose cyclophosphamide, lenalidomide, bortezomib, and dexamethasone (Dara-CVRd) before and after autologous stem-cell transplant (ASCT) in newly diagnosed patients with molecularly defined ultra–high-risk (UHiR) multiple myeloma (NDMM) or plasma cell leukemia (PCL). To provide clinical context, progression-free survival (PFS) and overall survival (OS) were referenced to contemporaneous outcomes seen in patients with UHiR NDMM treated in the recent Myeloma XI (MyeXI) trial.Methods: Transplant-eligible all-comers NDMM patients were profiled for UHiR disease, defined by presence of ≥2 genetic risk markers t(4;14)/t(14;16)/t(14;20), del(1p), gain(1q), and del(17p), and/or SKY92 gene expression risk signature. Patients with UHiR MM/PCL were offered treatment with Dara-CVRd induction, V-augmented ASCT, extended Dara-VR(d) consolidation, and Dara-R maintenance. UHiR patients treated in MyeXI with carfilzomib, lenalidomide, dexamethasone, and cyclophosphamide, or lenalidomide, dexamethasone, and cyclophosphamide, ASCT, and R maintenance or observation were identified by mirrored molecular screening. OPTIMUM PFS at 18 months (PFS18m) was compared against MyeXI using a Bayesian framework, and patients were followed up to the end of consolidation for PFS and OS.Results: Of 412 screened NDMM OPTIMUM patients, 103 were identified as UHiR or PCL and subsequently treated on trial with Dara-CVRd; 117 MyeXI patients identified as UHiR formed the external comparator arm, with comparable clinical and molecular characteristics to OPTIMUM. Comparison of PFS18m per Bayesian framework resulted in a 99.5% chance of OPTIMUM being superior to MyeXI. At 30 months' follow-up, PFS was 77% for OPTIMUM versus 39.8% for MyeXI, and OS 83.5% versus 73.5%, respectively. Extended post-ASCT Dara-VRd consolidation therapy was highly deliverable, with limited toxicity.Conclusion: Our results suggest that Dara-CVRd induction and extended post-ASCT Dara-VRd consolidation markedly improve PFS for UHiR NDMM patients over conventional management, supporting further evaluation of this strategy.</p

    Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study

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    OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times. MATERIALS AND METHODS: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken. Disease sites were manually labeled using Streamline reference standard. Whole-body MRI scans were randomly allocated to training and testing sets. A model for malignant lesion detection was developed based on convolutional neural networks and a 2-stage training strategy. The final algorithm generated lesion probability heat maps. Using a concurrent reader paradigm, 25 radiologists (18 experienced, 7 inexperienced in WB-/MRI) were randomly allocated WB-MRI scans with or without ML support to detect malignant lesions over 2 or 3 reading rounds. Reads were undertaken in the setting of a diagnostic radiology reading room between November 2019 and March 2020. Reading times were recorded by a scribe. Prespecified analysis included sensitivity, specificity, interobserver agreement, and reading time of radiology readers to detect metastases with or without ML support. Reader performance for detection of the primary tumor was also evaluated. RESULTS: Four hundred thirty-three evaluable WB-MRI scans were allocated to algorithm training (245) or radiology testing (50 patients with metastases, from primary 117 colon [n = 117] or lung [n = 71] cancer). Among a total 562 reads by experienced radiologists over 2 reading rounds, per-patient specificity was 86.2% (ML) and 87.7% (non-ML) (-1.5% difference; 95% confidence interval [CI], -6.4%, 3.5%; P = 0.39). Sensitivity was 66.0% (ML) and 70.0% (non-ML) (-4.0% difference; 95% CI, -13.5%, 5.5%; P = 0.344). Among 161 reads by inexperienced readers, per-patient specificity in both groups was 76.3% (0% difference; 95% CI, -15.0%, 15.0%; P = 0.613), with sensitivity of 73.3% (ML) and 60.0% (non-ML) (13.3% difference; 95% CI, -7.9%, 34.5%; P = 0.313). Per-site specificity was high (>90%) for all metastatic sites and experience levels. There was high sensitivity for the detection of primary tumors (lung cancer detection rate of 98.6% with and without ML [0.0% difference; 95% CI, -2.0%, 2.0%; P = 1.00], colon cancer detection rate of 89.0% with and 90.6% without ML [-1.7% difference; 95% CI, -5.6%, 2.2%; P = 0.65]). When combining all reads from rounds 1 and 2, reading times fell by 6.2% (95% CI, -22.8%, 10.0%) when using ML. Round 2 read-times fell by 32% (95% CI, 20.8%, 42.8%) compared with round 1. Within round 2, there was a significant decrease in read-time when using ML support, estimated as 286 seconds (or 11%) quicker (P = 0.0281), using regression analysis to account for reader experience, read round, and tumor type. Interobserver variance suggests moderate agreement, Cohen κ = 0.64; 95% CI, 0.47, 0.81 (with ML), and Cohen κ = 0.66; 95% CI, 0.47, 0.81 (without ML). CONCLUSIONS: There was no evidence of a significant difference in per-patient sensitivity and specificity for detecting metastases or the primary tumor using concurrent ML compared with standard WB-MRI. Radiology read-times with or without ML support fell for round 2 reads compared with round 1, suggesting that readers familiarized themselves with the study reading method. During the second reading round, there was a significant reduction in reading time when using ML support

    Predictive and prognostic factors associated with soft tissue sarcoma response to chemotherapy: a subgroup analysis of the European Organisation for Research and Treatment of Cancer 62012 study

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    Background: The European Organization for Research and Treatment of Cancer (EORTC) 62012 study was a Phase III trial of doxorubicin versus doxorubicin–ifosfamide chemotherapy in 455 patients with advanced soft tissue sarcoma (STS). Analysis of the main study showed that combination chemotherapy improved tumor response and progression-free survival, but differences in overall survival (OS) were not statistically significant. We analyzed factors prognostic for tumor response and OS, and assessed histological subgroup and tumor grade as predictive factors to identify patients more likely to benefit from combination chemotherapy. Methods: Central pathology review was performed by six reference pathologists. Gender, age, performance status, time from first presentation with sarcoma to starting palliative chemotherapy, tumor grade, histological subgroup, primary tumor site involvement, and sites of metastases were assessed as prognostic factors. Results: Three hundred and ten patients were included in this study. Discordance between local and central pathology opinion of tumor histology and tumor grade was observed in 98 (32%) and 122 (39%) cases, respectively. In multivariate analysis, liposarcoma patients had improved tumor response compared to other histological subgroups, whilst patients with metastases other than lung, liver or bone had a poorer response [odds ratio (OR) 0.42, 95% confidence interval (CI) 0.23–0.78; p = 0.006]. Patients with bone metastases had reduced OS [hazard ratio (HR) 1.56, 95% CI 1.16–2.09; p = 0.003]. By central pathology review, patients with undifferentiated pleomorphic sarcoma (UPS) had improved tumor response and OS with doxorubicin–ifosfamide compared to single-agent doxorubicin (OR 9.90, 95% CI 1.93–50.7 and HR 0.44, 95% CI 0.26–0.79, respectively). Grade III tumors had improved response with combination chemotherapy but there was no interaction between chemotherapy and grade on OS. Conclusions: Prospective central pathology review of tumor histology should be integrated into future STS clinical trials. Doxorubicin–ifosfamide may be most appropriate for young, fit patients with poorly differentiated Grade III tumors including UPS

    Extracranial soft-tissue Tumors: repeatability of apparent diffusion coefficient estimates from diffusion-weighted MR imaging

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    Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%–6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = −0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P < .05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies—a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations

    The management of desmoid tumours: A joint global consensus-based guideline approach for adult and paediatric patients

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    Abstract Desmoid tumor (DT; other synonymously used terms: Desmoid-type fibromatosis, aggressive fibromatosis) is a rare and locally aggressive monoclonal, fibroblastic proliferation characterised by a variable and often unpredictable clinical course. Previously surgery was the standard primary treatment modality; however, in recent years a paradigm shift towards a more conservative management has been introduced and an effort to harmonise the strategy amongst clinicians has been made. We present herein an evidence-based, joint global consensus guideline approach to the management of this disease focussing on: molecular genetics, indications for an active treatment, and available systemic therapeutic options. This paper follows a one-day consensus meeting held in Milan, Italy, in June 2018 under the auspices of the European Reference Network for rare solid adult cancers, EURACAN, the European Organisation for Research and Treatment of Cancer (EORTC) Soft Tissue and Bone Sarcoma Group (STBSG) as well as Sarcoma Patients EuroNet (SPAEN) and The Desmoid tumour Research Foundation (DTRF). The meeting brought together over 50 adult and pediatric sarcoma experts from different disciplines, patients and patient advocates from Europe, North America and Japan
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