Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities

Preparing a collection of radiology examinations for distribution and retrieval

OBJECTIVE: Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. MATERIALS AND METHODS: The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. RESULTS: The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. CONCLUSION: Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/)

Three cachexia phenotypes and the impact of fat-only loss on survival in FOLFIRINOX therapy for pancreatic cancer

BACKGROUND: By the traditional definition of unintended weight loss, cachexia develops in ~80% of patients with pancreatic ductal adenocarcinoma (PDAC). Here, we measure the longitudinal body composition changes in patients with advanced PDAC undergoing 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin therapy. METHODS: We performed a retrospective review of 53 patients with advanced PDAC on 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin as first line therapy at Indiana University Hospital from July 2010 to August 2015. Demographic, clinical, and survival data were collected. Body composition measurement by computed tomography (CT), trend, univariate, and multivariate analysis were performed. RESULTS: Among all patients, three cachexia phenotypes were identified. The majority of patients, 64%, had Muscle and Fat Wasting (MFW), while 17% had Fat-Only Wasting (FW) and 19% had No Wasting (NW). NW had significantly improved overall median survival (OMS) of 22.6 months vs. 13.0 months for FW and 12.2 months for MFW (P = 0.02). FW (HR = 5.2; 95% confidence interval = 1.5-17.3) and MFW (HR = 1.8; 95% confidence interval = 1.1-2.9) were associated with an increased risk of mortality compared with NW. OMS and risk of mortality did not differ between FW and MFW. Progression of disease, sarcopenic obesity at diagnosis, and primary tail tumours were also associated with decreased OMS. On multivariate analysis, cachexia phenotype and chemotherapy response were independently associated with survival. Notably, CT-based body composition analysis detected tissue loss of >5% in 81% of patients, while the traditional definition of >5% body weight loss identified 56.6%. CONCLUSIONS: Distinct cachexia phenotypes were observed in this homogeneous population of patients with equivalent stage, diagnosis, and first-line treatment. This suggests cellular, molecular, or genetic heterogeneity of host or tumour. Survival among patients with FW was as poor as for MFW, indicating adipose tissue plays a crucial role in cachexia and PDAC mortality. Adipose tissue should be studied for its mechanistic contributions to cachexia

Design, Performance, and Calibration of CMS Hadron-Barrel Calorimeter Wedges

Extensive measurements have been made with pions, electrons and muons on four production wedges of the Compact Muon Solenoid (CMS) hadron barrel (HB) calorimeter in the H2 beam line at CERN with particle momenta varying from 20 to 300 GeV/c. Data were taken both with and without a prototype electromagnetic lead tungstate crystal calorimeter (EB) in front of the hadron calorimeter. The time structure of the events was measured with the full chain of preproduction front-end electronics running at 34 MHz. Moving-wire radioactive source data were also collected for all scintillator layers in the HB. These measurements set the absolute calibration of the HB prior to first pp collisions to approximately 4%

Energy Response and Longitudinal Shower Profiles Measured in CMS HCAL and Comparison With Geant4

The response of the CMS combined electromagnetic and hadron calorimeter to beams of pions with momenta in the range 5-300 GeV/c has been measured in the H2 test beam at CERN. The raw response with the electromagnetic compartment calibrated to electrons and the hadron compartment calibrated to 300 GeV pions may be represented by sigma = (1.2) sqrt{E} oplus (0.095) E. The fraction of energy visible in the calorimeter ranges from 0.72 at 5 GeV to 0.95 at 300 GeV, indicating a substantial nonlinearity. The intrinsic electron to hadron ratios are fit as a function of energy and found to be in the range 1.3-2.7 for the electromagnetic compartment and 1.4-1.8 for the hadronic compartment. The fits are used to correct the non-linearity of the e pi response to 5% over the entire measured range resulting in a substantially improved resolution at low energy. Longitudinal shower profile have been measured in detail and compared to Geant4 models, LHEP-3.7 and QGSP-2.8. At energies below 30 GeV, the data, LHEP and QGSP are in agreement. Above 30 GeV, LHEP gives a more accurate simulation of the longitudinal shower profile

Synchronization and Timing in CMS HCAL

The synchronization and timing of the hadron calorimeter (HCAL) for the Compact Muon Solenoid has been extensively studied with test beams at CERN during the period 2003-4, including runs with 40 MHz structured beam. The relative phases of the signals from different calorimeter segments are timed to 1 ns accuracy using a laser and equalized using programmable delay settings in the front-end electronics. The beam was used to verify the timing and to map out the entire range of pulse shapes over the 25 ns interval between beam crossings. These data were used to make detailed measurements of energy-dependent time slewing effects and to tune the electronics for optimal performance

Design, Performance, and Calibration of CMS Hadron Endcap Calorimeters

Detailed measurements have been made with the CMS hadron calorimeter endcaps (HE) in response to beams of muons, electrons, and pions. Readout of HE with custom electronics and hybrid photodiodes (HPDs) shows no change of performance compared to readout with commercial electronics and photomultipliers. When combined with lead-tungstenate crystals, an energy resolution of 8\% is achieved with 300 GeV/c pions. A laser calibration system is used to set the timing and monitor operation of the complete electronics chain. Data taken with radioactive sources in comparison with test beam pions provides an absolute initial calibration of HE to approximately 4\% to 5\%

Design, Performance, and Calibration of the CMS Hadron-Outer Calorimeter

The CMS hadron calorimeter is a sampling calorimeter with brass absorber and plastic scintillator tiles with wavelength shifting fibres for carrying the light to the readout device. The barrel hadron calorimeter is complemented with an outer calorimeter to ensure high energy shower containment in the calorimeter. Fabrication, testing and calibration of the outer hadron calorimeter are carried out keeping in mind its importance in the energy measurement of jets in view of linearity and resolution. It will provide a net improvement in missing \et measurements at LHC energies. The outer hadron calorimeter will also be used for the muon trigger in coincidence with other muon chambers in CMS