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Our purpose was to report 5-year efficacy and toxicity of intraprostatic lesion boosting using standard and hypofractionated radiation therapy.DELINEATE (ISRCTN 04483921) is a single center phase 2 multicohort study including standardly fractionated (cohort A: 74 Gy/37F to prostate and seminal vesicles [PSV]; cohort C 74 Gy/37F to PSV plus 60 Gy/37F to pelvic lymph nodes) and moderately hypofractionated (cohort B: 60 Gy/20F to PSV) prostate intensity-modulated radiation therapy patients with National Comprehensive Cancer Network intermediate/high-risk disease. Patients received an integrated boost of 82 Gy (cohorts A and C) or 67 Gy (cohort B) to multiparametric magnetic resonance imaging identified lesion(s). Primary endpoint was late Radiation Therapy Oncology Group (RTOG) gastrointestinal (GI) toxicity at 1 year. Secondary endpoints were acute and late toxicity (clinician and patient reported) and freedom from biochemical/clinical failure at 5 years.Two hundred and sixty-five men were recruited and 256 were treated (55 cohort A, 153 cohort B, and 48 cohort C). Median follow-up for each cohort was5 years. Cumulative late RTOG grade 2+ GI toxicity at 1 year was 3.6% (95% confidence interval [CI], 0.9%-13.8%) (cohort A), 7.2% (95% CI, 4%-12.6%) (cohort B), and 8.4% (95% CI, 3.2%-20.8%) (cohort C). Cumulative late RTOG grade 2+ GI toxicity to 5 years was 12.8% (95% CI, 6.3%-25.1%) (cohort A), 14.6% (95% CI, 9.9%-21.4%) (cohort B), and 20.7% (95% CI, 11.2%-36.2%) (cohort C). Cumulative RTOG grade 2+ genitourinary toxicity to 5 years was 12.9% (95% CI, 6.4%-25.2%) (cohort A), 18.2% (95% CI, 12.8%-25.4%) (cohort B), and 18.2% (95% CI, 9.5%-33.2%) (cohort C). Five-year freedom from biochemical/clinical failure was 98.2% (95% CI, 87.8%-99.7%) (cohort A), 96.7% (95% CI, 91.3%- 98.8%) (cohort B), and 95.1% (95% CI, 81.6-98.7%) (cohort C).The DELINEATE trial has shown safety, tolerability, and feasibility of focal boosting in 20 or 37 fractions. Efficacy results indicate a low chance of prostate cancer recurrence 5 years after radiation therapy. Evidence from ongoing phase 3 randomized trials is awaited.

This manuscript is the third in a five-part series related to statistical assessment methodology for technical performance of multi-parametric quantitative imaging biomarkers (mp-QIBs). We outline approaches and statistical methodologies for developing and evaluating a phenotype classification model from a set of multiparametric QIBs. We then describe validation studies of the classifier for precision, diagnostic accuracy, and interchangeability with a comparator classifier. We follow with an end-to-end real-world example of development and validation of a classifier for atherosclerotic plaque phenotypes. We consider diagnostic accuracy and interchangeability to be clinically meaningful claims for a phenotype classification model informed by mp-QIB inputs, aiming to provide tools to demonstrate agreement between imaging-derived characteristics and clinically established phenotypes. Understanding that we are working in an evolving field, we close our manuscript with an acknowledgement of existing challenges and a discussion of where additional work is needed. In particular, we discuss the challenges involved with technical performance and analytical validation of mp-QIBs. We intend for this manuscript to further advance the robust and promising science of multiparametric biomarker development.

This paper is the fifth in a five-part series on statistical methodology for performance assessment of multi-parametric quantitative imaging biomarkers (mpQIBs) for radiomic analysis. Radiomics is the process of extracting visually imperceptible features from radiographic medical images using data-driven algorithms. We refer to the radiomic features as data-driven imaging markers (DIMs), which are quantitative measures discovered under a data-driven framework from images beyond visual recognition but evident as patterns of disease processes irrespective of whether or not ground truth exists for the true value of the DIM. This paper aims to set guidelines on how to build machine learning models using DIMs in radiomics and to apply and report them appropriately. We provide a list of recommendations, named RANDAM (an abbreviation of "Radiomic ANalysis and DAta Modeling"), for analysis, modeling, and reporting in a radiomic study to make machine learning analyses in radiomics more reproducible. RANDAM contains five main components to use in reporting radiomics studies: design, data preparation, data analysis and modeling, reporting, and material availability. Real case studies in lung cancer research are presented along with simulation studies to compare different feature selection methods and several validation strategies.

Background Textural features extracted from MRI potentially provide prognostic information additional to volume for influencing surgical management of cervical cancer. Purpose To identify textural features that differ between cervical tumors above and below the volume threshold of eligibility for trachelectomy and determine their value in predicting recurrence in patients with low-volume tumors. Methods Of 378 patients with Stage1–2 cervical cancer imaged prospectively (3T, endovaginal coil), 125 had well-defined, histologically-confirmed squamous or adenocarcinomas with >100 voxels (>0.07 cm3) suitable for radiomic analysis. Regions-of-interest outlined the whole tumor on T2-W images and apparent diffusion coefficient (ADC) maps. Textural features based on grey-level co-occurrence matrices were compared (Mann-Whitney test with Bonferroni correction) between tumors greater (n = 46) or less (n = 79) than 4.19 cm3. Clustering eliminated correlated variables. Significantly different features were used to predict recurrence (regression modelling) in surgically-treated patients with low-volume tumors and compared with a model using clinico-pathological features. Results Textural features (Dissimilarity, Energy, ClusterProminence, ClusterShade, InverseVariance, Autocorrelation) in 6 of 10 clusters from T2-W and ADC data differed between high-volume (mean ± SD 15.3 ± 11.7 cm3) and low-volume (mean ± SD 1.3 ± 1.2 cm3) tumors. (p, Highlights • Texture features differed significantly between high-compared to low-volume cervical tumors (p

Oligometastatic disease has been proposed as an intermediate state between localised and systemically metastasised disease. In the absence of randomised phase 3 trials, early clinical studies show improved survival when radical local therapy is added to standard systemic therapy for oligometastatic disease. However, since no biomarker for the identification of patients with true oligometastatic disease is clinically available, the diagnosis of oligometastatic disease is based solely on imaging findings. A small number of metastases on imaging could represent different clinical scenarios, which are associated with different prognoses and might require different treatment strategies. 20 international experts including 19 members of the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer OligoCare project developed a comprehensive system for characterisation and classification of oligometastatic disease. We first did a systematic review of the literature to identify inclusion and exclusion criteria of prospective interventional oligometastatic disease clinical trials. Next, we used a Delphi consensus process to select a total of 17 oligometastatic disease characterisation factors that should be assessed in all patients treated with radical local therapy for oligometastatic disease, both within and outside of clinical trials. Using a second round of the Delphi method, we established a decision tree for oligometastatic disease classification together with a nomenclature. We agreed oligometastatic disease as the overall umbrella term. A history of polymetastatic disease before diagnosis of oligometastatic disease was used as the criterion to differentiate between induced oligometastatic disease (previous history of polymetastatic disease) and genuine oligometastatic disease (no history of polymetastatic disease). We further subclassified genuine oligometastatic disease into repeat oligometastatic disease (previous history of oligometastatic disease) and de-novo oligometastatic disease (first time diagnosis of oligometastatic disease). In de-novo oligometastatic disease, we differentiated between synchronous and metachronous oligometastatic disease. We did a final subclassification into oligorecurrence, oligoprogression, and oligopersistence, considering whether oligometastatic disease is diagnosed during a treatment-free interval or during active systemic therapy and whether or not an oligometastatic lesion is progressing on current imaging. This oligometastatic disease classification and nomenclature needs to be prospectively evaluated by the OligoCare study.

Dynamic-contrast enhanced (DCE) and diffusion-weighted (DW) MR imaging are invaluable in the detection, staging, and characterization of uterine and ovarian malignancies, for monitoring treatment response, and for identifying disease recurrence. When used as adjuncts to morphologic T2-weighted (T2-W) MR imaging, these techniques improve accuracy of disease detection and staging. DW-MR imaging is preferred because of its ease of implementation and lack of need for an extrinsic contrast agent. MR spectroscopy is difficult to implement in the clinical workflow and lacks both sensitivity and specificity. If used quantitatively in multicenter clinical trials, standardization of DCE- and DW-MR imaging techniques and rigorous quality assurance is mandatory.

Aim The aim of this study is to validate high-resolution endovaginal T2- and diffusion-weighted MRI measurements (tumour size, volume and length of uninvolved cervical canal) against histology in patients undergoing trachelectomy. Patients/interventions 55 consecutive patients 25–44 years with cervical cancer being considered for trachelectomy were prospectively assessed with endovaginal T2-W and diffusion-weighted MRI. Two independent observers blinded to histology recorded maximum tumour dimension, volume and distance from the superior aspect of the tumour to the internal os. Following trachelectomy, pathologist-outlined tumour sections were photographed with a set scale and similar measurements were recorded. Results Fifteen of 45 patients subsequently treated with fertility-sparing surgery had residual tumour (median histological volume: 0.28 cm3, IQR = 0.14–1.06 cm3). Sensitivity, specificity, positive and negative predictive values for detecting tumour: Observer1: 86.7%, 80.0%, 68.4%, and 92.3%, respectively; Observer2: 86.7%, 90.0%, 81.0%, and 93.1%, respectively. Size and volume correlated between observers (r = 0.96, 0.84, respectively, p, Highlights • High spatial resolution endovaginal MRI of the cervix in patients potentially selected for trachelectomy • Correlation of MRI with histopathology in subcentimetre cervical tumours • Interobserver comparison of measured tumour maximum dimension and volume on endovaginal MRI

Magnetic resonance imaging (MRI) can be made sensitive to diffusion of water molecules in biological tissues: this phenomenon can be quantitated to provide a biomarker, the apparent diffusion coefficient (ADC). Over the past decade, evidence has accumulated from numerous clinical and animal studies that ADC is abnormal in tumours; that elevated ADC reflects an elevated non-cellular fraction; and that acute increases in ADC following therapy can indicate that tumour cells have been killed. However there remain substantial challenges in ensuring robust and valid ADC measurements, particularly in multicentre studies in common sites of metastasis such as lung and liver. Moreover, there is uncertainty about how best to select the timing of observation post-therapy to avoid false-negatives, and how to minimise the confounding factors which could decouple drug-induced ADC increase from drug-induced cell kill. In this review we summarise the physical basis of the biomarker, the evidence that it reflects non-viable fraction, particularly in extracranial tumours, and suggest a roadmap for validation and qualification.

Imaging data have the potential to provide information on disease profiling pertaining to diagnosis, prognosis, selection of therapy, monitoring of response to therapy and pharmacokinetic information of drugs. Selection of the most appropriate imaging modality for a specific task will be vital for diagnosis, stratification, treatment response or treatment efficacy, toxicity assessment, and treatment outcome measures (progression-free survival). The EORTC Imaging Group was formed to establish and maintain the scientific and clinical value of advanced imaging in EORTC clinical trials. The group focuses on the development of specific analytical and review procedures as well as quality control procedures, in the context of clinical trials conducted by the EORTC groups. (C) 2012 European Organisation for Research and Treatment of Cancer. All rights reserved.

To evaluate the effects of previous cone biopsy and lesion size on detectability of stage 1a/1b cervical cancer using endovaginal T2- and diffusion-weighted magnetic resonance imaging.One hundred and thirteen patients with cervical tumor were imaged using an endovaginal coil with T2-weighted (T2-W) and diffusion-weighted single-shot echo-planar sequences; 85 managed surgically (58 with prior cone biopsy/LLETZ) were evaluated. T2-W images and ADC maps viewed simultaneously were scored positive or negative for tumor and compared with histology at surgery. MRI tumor volumes, maximum radiological and histological dimensions were recorded. ROC analysis determined the MRI volume with optimal sensitivity/specificity for identifying tumor in those without and with prior cone biopsy/LLETZ and the maximum histological dimension for correctly identifying tumor with MRI. Mean apparent diffusion coefficients (ADCs) from tumor and adjacent normal epithelium were compared.Sensitivity and specificity for detecting tumor in those without (100%; 100% respectively) and with (80%; 78.9% respectively) prior cone biopsy/LLETZ were significantly different (p0.001). Following cone biopsy/LLETZ, MRI tumor volume of 83 mm3 detected tumor with 80% sensitivity, 94.7% specificity; a 5.3mm maximal histological dimension was detected on MRI with 100% sensitivity, 100% specificity. Tumor ADCs were significantly lower (p0.001) than paired normal epithelial tissue (median, 988×10(-6) mm2/s vs. 1564×10(-6) mm2/s) but neither tumor nor epithelial ADCs differed significantly between patients with or without prior cone biopsy/LLETZ (p=0.48 and 0.15, respectively).Endovaginal MRI with T2- and diffusion-weighted sequences has significantly lower sensitivity and specificity for tumor detection following cone biopsy/LLETZ.

AIM: To evaluate diffusion-weighted magnetic resonance imaging (DW-MRI) as a marker for disease aggressiveness by comparing tumour apparent diffusion coefficients (ADCs) between patients with low- versus higher-risk localized prostate cancer. METHOD: Forty-four consecutive patients classified as low- [n = 26, stageT1/T2a, Gleason score = T2b and/or Gleason score >= 7, and/or PSA > 10 (group 2)] risk, who subsequently were monitored with active surveillance or started neoadjuvant hormone and radiotherapy, respectively, underwent endorectal MRI. T2-weighted (T2W) and DW images (5 b values, 0-800 s/mm(2)) were acquired and isotropic ADC maps generated. Regions of interest (ROIs) on T2W axial images [around whole prostate, central gland (CG), and tumour] were transferred to ADC maps. Tumour, CG, and peripheral zone (PZ = whole prostate minus CG and tumour) ADCs (fast component from b = 0-100 s/mm(2), slow component from b = 100-800 s/mm(2)) were compared. RESULTS: T2W-defined tumour volume medians, and quartiles were 1.2 cm(3), 0.7 and 3.3 cm(3) (group 1); and 6 cm(3), 1.3 and 16.5 cm(3) (group 2). There were significant differences in both ADC(fast) (1778 +/- 264 x 10(-6) versus 1583 +/- 283 x 10(-6) mm(2)/s, p = 0.03) and ADC(slow) (1379 +/- 321 x 10(-6) versus 1196 +/- 158 x 10(-6) mm(2)/s, p = 0.001) between groups. Tumour volume (p = 0.002) and ADC(slow) (p = 0.005) were significant differentiators of risk group. CONCLUSION: Significant differences in tumour ADCs exist between patients with low-risk, and those with higher-risk localized prostate cancer. DW-MRI merits further study with respect to clinical outcomes. (C) 2008 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Background. Estimation of tumor volume by endovaginal magnetic resonance (MR) imaging is a better indicator of prognosis than FIGO stage in women with cervical cancer treated by standard modalities. However, the introduction of fertility conserving surgical techniques makes fresh demands upon imaging of these small tumors. Objective. To determine the sensitivity and specificity of endovaginal MRI in detecting small volume disease and assessing parametrial extension in uterine cervical cancer by comparing the findings with those at radical hysterectomy in order to establish its role in guiding the surgical decision-making process preoperatively. Methods. A retrospective study was performed in 119 patients who underwent endovaginal and external phased array MR imaging at 0.5 T or 1.5 T before radical hysterectomy. Tumor presence within the cervix and parametrial extension was noted on the endovaginal images. Histopathological findings were correlated with MR imaging results for all patients. Results. The sensitivity and specificity for detecting tumor by endovaginal MR imaging in the 119 patients were 96.9 and 59.0%, respectively. Thirty-six percent of tumors were ≤1 cm 3 in volume. For these, sensitivity and specificity for tumor detection were 87% and 65% respectively. For evaluation of parametrial status, sensitivity was 80%, and specificity was 91.3%. A cut-off MRI tumor volume of 5.2 cm 3 predicted histologically confirmed lymph node metastases with a sensitivity of 78.6% and specificity of 72.5%. Conclusion. Endovaginal magnetic resonance imaging has high sensitivity in the preoperative staging of uterine cervical cancer even for tumors ≤1 cm 3 . It is an invaluable technique in planning fertility-conserving or radical surgical treatment of early stage cervical cancer.

The high sensitivity but poor specificity of contrast enhanced magnetic resonance (MR) imaging for delineating malignant breast lesions is increasing the demand for MR guide breast biopsy. However, the poor patient access offered by conventional MR systems makes such procedures extremely difficult. We describe a method of performing breast biopsy outside the bore of the magnet using the 3-D MR imaging data. This involves a frameless stereotactic technique using an ultrasonic localizer. The position in space of the tip of a pointer with a handle which incorporates two ultrasound emitters can be tracked using an array of ultrasound detectors. MR visible marker beads (fiducials) placed on the breast and imaged at the same time are identified to the computer in relation to images of the breast. The ultrasonic localizer is used to register the position in space of the fiducials by touching them with the tip of the pointer. The image of the lesion within the breast can then be displayed in relation to the position of the tip of the pointer and the needle approach planned. Nine women with foci of enhancement on their dynamic contrast enhanced MR images underwent frameless stereotactic breast cytology. Needle placement within 2 mm of the lesion was achieved at first pass in eight out of nine (89%) cases: in one case the needle had to be re-positioned prior to sampling. This technique provides a means of targetting MR visible lesions using the MR imaging data whilst performing the procedure outside the magnet bore.