It is commonly assumed that essentially all of the water in cells has the same ideal motional and colligative properties as does water in bulk liquid state. This assumption is used in studies of volume regulation, transmembrane movement of solutes and electrical potentials, solute and solution motion, solute solubility and other phenomena. To get at the extent and the source of non-ideally behaved water (an operational term dependent on the measurement method), we studied the motional and colligative properties of water in cells, in solutions of amino acids and glycine peptides whose surface characteristics are known, and in solution of bovine serum albumin, hemoglobin and some synthetic polypeptides. Solutions of individual amino acids with progressively larger hydrophobic side chains showed one perturbed water molecule (structured-slowed in motion) per nine square angstroms of hydrophobic surface area. Water molecules adjacent to hydrophobic surfaces form pentagonal structural arrays, as shown by X-ray diffraction studies, that are reported to be disrupted by heat, electric field, hydrostatic pressure and phosphorylation state. Hydrophilic amino acids demonstrated water destructuring (increased motion) that was attributed to dielectric realignment of dipolar water molecules in the electric field between charge groups. In solutions of proteins, several methods indicate the equivalent of 2-8 layers of structured water molecules extending beyond the protein surface, and we have recently demonstrated that induced protein conformational change modifies the extent of non-ideally behaved water. Water self-diffusion rate as measured in three different cell types was about half that of bulk water, indicating that most of the water in these cells was slower in motion than bulk water. In different cell types the extent of osmotically perturbed water ranged from less that half to almost all of the intracellular water. The assumption that essentially all intracellular water has ideal osmotic and motional behavior is not supported by the experimental findings. The non-ideally of cell water is an operational term. Therefore, the amount of non-ideally behaving water is dependent on the characteristics of water targeted, i.e. the measurement method, and a large fraction of it is explainable in mechanistic terms at a molecular level based on solute-solvent interactions.

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By measuring the freezing-point depression for dilute, aqueous solutions of all water-soluble amino acids, we test the hypothesis that nonideality in aqueous solutions is due to solute-induced water structuring near hydrophobic surfaces and solute-induced water destructuring in the dipolar electric fields generated by the solute. Nonideality is expressed with a single solute/solvent interaction parameter I, calculated from experimental measure of delta T. A related parameter, I(n), gives a method of directly relating solute characteristics to solute-induced water structuring or destructuring. I(n)-values correlate directly with hydrophobic surface area and inversely with dipolar strength. By comparing the nonideality of amino acids with progressively larger hydrophobic side chains, structuring is shown to increase with hydrophobic surface area at a rate of one perturbed water molecule per 8.8 square angstroms, implying monolayer coverage. Destructuring is attributed to dielectric realignment as described by the Debye-Hückel theory, but with a constant separation of charges in the amino-carboxyl dipole. By using dimers and trimers of glycine and alanine, this destructuring is shown to increase with increasing dipole strength using increased separation of fixed dipolar charges. The capacity to predict nonideal solution behavior on the basis of amino acid characteristics will permit prediction of free energy of transfer to water, which may help predict the energetics of folding and unfolding of proteins based on the characteristics of constituent amino acids.

A Hindmarsh‐Rose model perceptibility phantom containing inserts with various in vitro atherosclerotic plaque compositions was constructed and imaged on a clinical 64 slice multidetector (MDCT) system using 80 and 120 kVp settings and two other cone‐beam (CBCT) systems at 80 kVp. Perceptibility of the simulated lipid‐fibrotic plaque solutions in the images was evaluated by six observers. The effective doses of the protocols employed were estimated using phantom CTDI‐vol measurements placed at identical settings. The CBCT system allowed reduction in effective dose in comparison with the conventional MDCT system for imaging of the carotid plaque phantoms without degrading image quality. The CBCT dose was less than MDCT, with a mean dose of 1.14±0.01 mSv and 1.11±0.02 mSv for MDCT using two measuring techniques vs. 0.35±0.01 mSv for CBCT. The image quality analysis showed no significant differences in the contrast‐detail (C‐D) curves of the best performing CBCT vs. clinical MDCT false(p>0.05false) using a Mann‐Whitney U test. Results indicate that low‐tube‐potential CBCT may produce comparable C‐D resolution for phantom‐based representations of soft plaque types with respect to MDCT systems. This study suggests that the utility of low kVp CT techniques for evaluating carotid vulnerable atherosclerotic plaque merits further study.PACS numbers: 87.53.Bn, 87.57.N‐, 87.57.Q‐, 87.57.cj

The FDA requires that new mammography modalities follow a QC program which is similar to the MQSA final rules for film‐screen mammography. Early full‐field digital mammography (FFDM) manufacturers fulfilled this requirement by publishing QC manuals which covered all the required medical physicist and technologist QC tests for their FFDM unit and soft‐copy review work station. In recent years, the FDA has allowed FFDM users to interpret digital mammograms on monitors other than the those provided by the FFDM manufacturer. There are several 5MP monitor manufacturers each with their own mammography QC requirements, documentation, software, and photometers. These monitors may also be rebranded and installed by PACS vendors with their own QC manuals. A physicist surveying a FFDM unit may find many combinations of FFDM manufacturer, monitor manufacture and PACS vendor QC requirements for the review workstation. Further complicating this, a single FFDM unit may use multiple, work stations from different manufacturers or a single work station may be used by multiple FFDM units perhaps from different manufacturers. A consulting medical physicist visiting multiple sites is especially likely to find a changing variety of combinations. Because these are all covered under MQSA regulations, it is important the physicist perform and document the correct QC tests. This lecture will review the various monitor QC tests suggested or required by TG‐18, the major FFDM manufacturers, current 5MP monitor manufacturers, and PACS vendors. Suggestions will be offered on sets of tests which can be performed on a large number of monitors regardless of their manufacturers. Suggestions will also be made on surveys which will fulfill the requirements of nearly all manufacturers. Such a surveys may include may tests which are not required for the monitor tested but are simple to perform. Learning Objectives: 1. Understand the review workstation tests required by FFDM manufacturers and the requirements those manufacturers have for third‐party monitors. 2. Understand the TQ18 monitor tests which are applicable to current 5MP monitors. 3. Learn the QC tests required by various 5MP monitor manufacturers and PACS vendors.

In recent years, the American College of Radiology (ACR) Magnetic Resonance Accreditation Program (MRAP) has been adopted by over 4600 sites, nearly half of the estimated MRI facilities in the United States. Those sites agree to follow a weekly QC program set up and monitored by a qualified medical physicist or MR scientist. This lecture will overview the QC requirements for high and low field MRI units from multiple vendors. Each unit has different terminology for center frequency and transmitter gain and different methods of locating them. These need to be known by the medical physicist and shown to the technologist. Suggestions will be given for teaching the QC to technologists. Suggestions will be given for establishing baselines and monitoring the QC program. Examples will be shown of evaluations of both properly functioning MRI scanners and poorly functioning units. Learning Objectives: 1. Learn the technologist QC requirements for the ACR MR accreditation program and the physicist / MR scientist's role in setting up the program. 2. Learn how to locate the applicable QC parameters on different MRI systems. 3. Learn how to establish MR QC baselines and evaluate the technologist QC program.

In recent years, the American College of Radiology (ACR) Magnetic Resonance Accreditation Program (MRAP) has been adopted by over 3000 sites, nearly half of the estimated MRI facilities in the United States. Those sites agree to follow a weekly QC program set up and monitored by a qualified medical physicist or MR scientist. They also agree to undergo initial and annual equipment performance evaluations by a qualified medical physicist/MR scientist. There are several published documents, including the ACR Phantom Testing Guidance and the 2004 ACR MRI QC Manual, which describe the tests and the performance criteria. These documents are helpful in providing guidance on submitting phantom images for accreditation. However, they allow considerable discretion to physicists doing these tests, and the scanners change more frequently than the published guidance. A consulting medical physicist may see a variety of scanners, each for a short period of time, and needs to provide the sites with useful recommendations beyond the pass/fail status of the phantom tests. The physicist must gather this information from existing data and tests performed with the ACR and other available phantoms. This lecture will describe information which can be derived from those data and how it may be used for improving MR image quality. Educational Objectives: 1. Learn the current status of the ACR MRAP program and the role of the medical physicist in that program. 2. Understand how to perform required phantom and annual tests on various scanners and the performance criteria for those tests. 3. Understand how the results of those tests can be combined and analyzed to troubleshoot problems. 4. Understand how QC test and phantom availability and results may vary depending on scanner manufacturer.

In recent years, the American College of Radiology (ACR) MR Accreditation Program (MRAP) has been adopted by more than 3000 facilities. Those sites agree to follow a quality control program set up and monitored by the medical physicist or MR scientist. They also agree to undergo initial and annual equipment evaluations by the medical physicist / MR scientist. There are several published documents, including the ACR Phantom Test Guidance and the 2001 ACR MR QC Manual, which describe required phantom tests and performance criteria. While helpful in assisting sites with the submission of phantom images for accreditation, these documents allow great discretion to the medical physicist in setting up the QC program without providing similar guidance in troubleshooting problems for a wide variety of scanners. A consulting medical physicist may see a wide variety of scanners, each for a short period of time, and needs to be able to provide the site with useful recommendations beyond the pass/fail status of the phantom tests. The physicist must gather this information from existing QC data and tests performed with the ACR and other readily‐available phantoms. This lecture will describe additional information which can be gathered from those data to produce recommendations for improving MR image quality. Educational Objectives: 1. Understand basic MR QC tests using the ACR and on‐site phantoms and how the results of those tests can be combined and analyzed to troubleshoot problems. 2. Understand how QC test availability and results may vary depending on scanner manufacturer. 3. Understand how technologist QC data may be analyzed to troubleshoot QC problems.