Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

Background: Positron emission tomography (PET) is routinely used for cancer staging and treatment follow-up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV—including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end, a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge. Methods: In this study, we compare two semi-automatic artificial intelligence (AI)-based segmentation methods with conventional semi-automatic segmentation approaches in terms of repeatability. One segmentation approach is based on a textural feature (TF) segmentation approach designed for accurate and repeatable segmentation of primary tumors and metastasis. Moreover, a convolutional neural network (CNN) is trained. The algorithms are trained, validated and tested using a lung cancer PET dataset. The segmentation accuracy of both segmentation approaches is compared using the Jaccard coefficient (JC). Additionally, the approaches are externally tested on a fully independent test–retest dataset. The repeatability of the methods is compared with those of two majority vote (MV2, MV3) approaches, 41%SUVMAX, and a SUV > 4 segmentation (SUV4). Repeatability is assessed with test–retest coefficients (TRT%) and intraclass correlation coefficient (ICC). An ICC > 0.9 was regarded as representing excellent repeatability. Results: The accuracy of the segmentations with the reference segmentation was good (JC median TF: 0.7, CNN: 0.73). Both segmentation approaches outperformed most other conventional segmentation methods in terms of test–retest coefficient (TRT% mean: TF: 13.0%, CNN: 13.9%, MV2: 14.1%, MV3: 28.1%, 41%SUVMAX: 28.1%, SUV4: 18.1%) and ICC (TF: 0.98, MV2: 0.97, CNN: 0.99, MV3: 0.73, SUV4: 0.81, and 41%SUVMAX: 0.68). Conclusion: The semi-automatic AI-based segmentation approaches used in this study provided better repeatability than conventional segmentation approaches. Moreover, both algorithms lead to accurate segmentations for both primary tumors as well as metastasis and are therefore good candidates for PET tumor segmentation

The effect of lip closure on palatal growth in patients with unilateral clefts

Objectives The objective of this study was to compare maxillary dimensions and growth in newborns with Complete Unilateral Cleft Lip and Palate (UCLP) to healthy newborns before and after cheiloplasty. Additionally, a palatal growth curve is constructed to give more information about the natural growth before surgical intervention. Methods Twenty-eight newborns with complete UCLP were enrolled in this study. Multiple plaster-casts of each child during their first year were collected and grouped in before and after cheiloplasty. A previous developed semi-automatic segmentation tool was used to assess the maxillary dimensions and were compared to a healthy control group. Z-scores were calculated to indicate differences between the two populations and if cheiloplasty had influence on maxillary growth. Furthermore, the prediction model created in a previous study was used to indicate differences between predictions and the outcome in UCLP measurements. The analysis was tested for inter- and intra-observer variability. Results Results show differences in alveolar and palatal shape in UCLP patients in comparison with healthy controls. Prior to cheiloplasty an increased width and alveolar length was observed while the palatal depth was decreased. After cheiloplasty the widths moved towards normal but were still significantly larger

PET segmentation of bulky tumors:Strategies and workflows to improve inter-observer variability

Background PET-based tumor delineation is an error prone and labor intensive part of image analysis. Especially for patients with advanced disease showing bulky tumor FDG load, segmentations are challenging. Reducing the amount of user-interaction in the segmentation might help to facilitate segmentation tasks especially when labeling bulky and complex tumors. Therefore, this study reports on segmentation workflows/strategies that may reduce the inter-observer variability for large tumors with complex shapes with different levels of user-interaction. Methods Twenty PET images of bulky tumors were delineated independently by six observers using four strategies: (I) manual, (II) interactive threshold-based, (III) interactive threshold-based segmentation with the additional presentation of the PET-gradient image and (IV) the selection of the most reasonable result out of four established semi-automatic segmentation algorithms (Select-the-best approach). The segmentations were compared using Jaccard coefficients (JC) and percentage volume differences. To obtain a reference standard, a majority vote (MV) segmentation was calculated including all segmentations of experienced observers. Performed and MV segmentations were compared regarding positive predictive value (PPV), sensitivity (SE), and percentage volume differences. Results The results show that with decreasing user-interaction the inter-observer variability decreases. JC values and percentage volume differences of Select-the-best and a workflow including gradient information were significantly better than the measurements of the other segmentation strategies (p-value&lt;0.01). Interactive threshold-based and manual segmentations also result in significant lower and more variable PPV/SE values when compared with the MV segmentation. Conclusions FDG PET segmentations of bulky tumors using strategies with lower user-interaction showed less inter-observer variability. None of the methods led to good results in all cases, but use of either the gradient or the Select-the-best workflow did outperform the other strategies tested and may be a good candidate for fast and reliable labeling of bulky and heterogeneous tumors.</p

Evaluation of diffusion-weighted MRI and (18F) fluorothymidine-PET biomarkers for early response assessment in patients with operable non-small cell lung cancer treated with neoadjuvant chemotherapy

Objective: To correlate changes in the apparent diffusion coefficient (ADC) from diffusion-weighted (DW)-MRI and standardised uptake value (SUV) from fluorothymidine (18FLT)-PET/CT with histopathological estimates of response in patients with non-small cell lung cancer (NSCLC) treated with neoadjuvant chemotherapy and track longitudinal changes in these biomarkers in a multicentre, multivendor setting. Methods: 14 patients with operable NSCLC recruited to a prospective, multicentre imaging trial (EORTC-1217) were treated with platinum-based neoadjuvant chemotherapy. 13 patients had DW-MRI and FLT-PET/CT at baseline (10 had both), 12 were re-imaged at Day 14 (eight dual-modality) and nine after completing chemotherapy, immediately before surgery (six dual-modality). Surgical specimens (haematoxylin-eosin and Ki67 stained) estimated the percentage of residual viable tumour/necrosis and proliferation index. Results: Despite the small numbers,significant findings were possible. ADCmedian increased (p 30% reduction in unidimensional measurement pre-surgery), showed an increase at Day 14 in ADC75th centile and reduction in total lesion proliferation (SUVmean x proliferative volume) greater than established measurement variability. Change in imaging biomarkers did not correlate with histological response (residual viable tumour, necrosis). Conclusion: Changes in ADC and FLT-SUV following neoadjuvant chemotherapy in NSCLC were measurable by Day 14 and preceded changes in unidimensional size but did not correlate with histopathological response. However, the magnitude of the changes and their utility in predicting (non-) response (tumour size/clinical outcome) remains to be established. Advances in knowledge: During treatment, ADC increase precedes size reductions, but does not reflect histopathological necrosis

Permanent tooth agenesis in non-syndromic Robin sequence and cleft palate: prevalence and patterns

Objectives: Partial tooth agenesis is frequently observed in Robin sequence. Tooth anomalies are increasingly considered as an extended phenotype of the cleft palate population. The study objective was to compare the prevalence and patterns of tooth agenesis in a group of patients with non-syndromic Robin sequence (ns-RS) and a group with non-syndromic cleft palate (ns-CP). Materials and methods: The panoramic radiographs of 115 ns-RS and 191 ns-CP patients were assessed for agenesis of the permanent dentition (excluding third molars) and the patterns recorded using the Tooth Agenesis Code. Results: Partial tooth agenesis was observed in 47.8% of ns-RS and 29.8% of ns-CP patients with a greater prevalence in the mandibula than in the maxilla, particularly in ns-RS. The teeth most frequently absent in both groups were the mandibular second premolars and maxillary lateral incisors. Tooth agenesis was bilateral in two-thirds of affected ns-RS patients and one-half of ns-CP patients. In ns-RS, bilateral agenesis of the mandibular second premolars was more frequently observed in female than that in male patients. Completely symmetrical patterns of hypodontia were found in around 45% of ns-RS patients with tooth agenesis compared to 35% in ns-CP. No association was found between the extent of the palatal cleft and the severity of hypodontia. Conclusion: Tooth agenesis is more prevalent in ns-RS than that in ns-CP, demonstrates a much greater predilection for the mandible in ns-RS, and bears no relation to the extent of the palatal cleft. Clinical relevance: When compared to ns-CP, additional developmental disturbances are likely involved in the etiology of tooth agenesis in ns-RS. Future research could help identify the underlying genetic traits and aid in classifying patients in those with and without expected tooth agenesis in order to facilitate orthodontic management strategies

Use of modern imaging methods to facilitate trials of metastasis-directed therapy for oligometastatic disease in prostate cancer: a consensus recommendation from the EORTC Imaging Group

Oligometastatic disease represents a clinical and anatomical manifestation between localised and polymetastatic disease. In prostate cancer, as with other cancers, recognition of oligometastatic disease enables focal, metastasisdirected therapies. These therapies potentially shorten or postpone the use of systemic treatment and can delay further metastatic progression, thus increasing overall survival. Metastasis-directed therapies require imaging methods that definitively recognise oligometastatic disease to validate their efficacy and reliably monitor response, particularly so that morbidity associated with inappropriately treating disease subsequently recognised as polymetastatic can be avoided. In this Review, we assess imaging methods used to identify metastatic prostate cancer at first diagnosis, at biochemical recurrence, or at the castration-resistant stage. Standard imaging methods recommended by guidelines have insufficient diagnostic accuracy for reliably diagnosing oligometastatic disease. Modern imaging methods that use PET-CT with tumour-specific radiotracers (choline or prostate-specific membrane antigen ligand), and increasingly whole-body MRI with diffusion-weighted imaging, allow earlier and more precise identification of metastases. The European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group suggests clinical algorithms to integrate modern imaging methods into the care pathway at the various stages of prostate cancer to identify oligometastatic disease. The EORTC proposes clinical trials that use modern imaging methods to evaluate the benefits of metastasis-directed therapies

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Reproducibility and Repeatability of Semiquantitative F-Fluorodihydrotestosterone Uptake Metrics in Castration-Resistant Prostate Cancer Metastases: A Prospective Multicenter Study

F-fluorodihydrotestosterone (F-FDHT) is a radiolabeled analog of the androgen receptor's primary ligand that is currently being credentialed as a biomarker for prognosis, response, and pharmacodynamic effects of new therapeutics. As part of the biomarker qualification process, we prospectively assessed its reproducibility and repeatability in men with metastatic castration-resistant prostate cancer. We conducted a prospective multiinstitutional study of metastatic castration-resistant prostate cancer patients undergoing 2 (test/retest) F-FDHT PET/CT scans on 2 consecutive days. Two independent readers evaluated all examinations and recorded SUVs, androgen receptor-positive tumor volumes, and total lesion uptake for the most avid lesion detected in each of 32 predefined anatomic regions. The relative absolute difference and reproducibility coefficient (RC) of each metric were calculated between the test and retest scans. Linear regression analyses, intraclass correlation coefficients (ICCs), and Bland-Altman plots were used to evaluate repeatability of F-FDHT metrics. The coefficient of variation and ICC were used to assess interobserver reproducibility. Twenty-seven patients with 140 F-FDHT-avid regions were included. The best repeatability among F-FDHT uptake metrics was found for SUV metrics (SUV SUV, and SUV), with no significant differences in repeatability among them. Correlations between the test and retest scans were strong for all SUV metrics ( ≥ 0.92; ICC ≥ 0.97). The RCs of the SUV metrics ranged from 21.3% (SUV) to 24.6% (SUV). The test and retest androgen receptor-positive tumor volumes and TLU, respectively, were highly correlated ( and ICC ≥ 0.97), although variability was significantly higher than that for SUV (RCs > 46.4%). The prostate-specific antigen levels, Gleason score, weight, and age did not affect repeatability, nor did total injected activity, uptake measurement time, or differences in uptake time between the 2 scans. Including the most avid lesion per patient, the 5 most avid lesions per patient, only lesions 4.2 mL or more, only lesions with an SUV of 4 g/mL or more, or normalizing of SUV to area under the parent plasma activity concentration-time curve did not significantly affect repeatability. All metrics showed high interobserver reproducibility (ICC > 0.98; coefficient of variation < 0.2%-10.8%). Uptake metrics derived from F-FDHT PET/CT show high repeatability and interobserver reproducibility

MRI protocol optimization for quantitative DCE-MRI of the spine

Purpose In this study we systematically investigated different Dynamic Contrast Enhancement (DCE)-MRI protocols in the spine, with the goal of finding an optimal protocol that provides data suitable for quantitative pharmacokinetic modelling (PKM). Materials and methods In 13 patients referred for MRI of the spine, DCE-MRI of the spine was performed with 2D and 3D MRI protocols on a 3T Philips Ingenuity MR system. A standard bolus of contrast agent (Dotarem - 0.2 ml/kg body weight) was injected intravenously at a speed of 3 ml/s. Different techniques for acceleration and motion compensation were tested: parallel imaging, partial-Fourier imaging and flow compensation. The quality of the DCE MRI images was scored on the basis of SNR, motion artefacts due to flow and respiration, signal enhancement, quality of the T1 map and of the arterial input function, and quality of pharmacokinetic model fitting to the extended Tofts model. Results Sagittal 3D sequences are to be preferred for PKM of the spine. Acceleration techniques were unsuccessful due to increased flow or motion artefacts. Motion compensating gradients failed to improve the DCE scans due to the longer echo time and the T2* decay which becomes more dominant and leads to signal loss, especially in the aorta. The quality scoring revealed that the best method was a conventional 3D gradient–echo acquisition without any acceleration or motion compensation technique. The priority in the choice of sequence parameters should be given to reducing echo time and keeping the dynamic temporal resolution below 5 s. Increasing the number of acquisition, when possible, helps towards reducing flow artefacts. In our setting we achieved this with a sagittal 3D slab with 5 slices with a thickness of 4.5 mm and two acquisitions. Conclusion The proposed DCE protocol, encompassing the spine and the descending aorta, produces a realistic arterial input function and dynamic data suitable for PKM