Abstract: The "left ventricular mass" (LVM) using Tc-99m Sestamibi SPECT imaging may be a useful parameter to quantitatively assess the left ventricle and hence its function. The LVM was determined without reorienting the images along the long axis of the left ventricle. A comparison with reoriented SPECT images was then performed. The LVM showed the expected variations among different pathological heart conditions and the control subjects. The left ventricular mass obtained from non-reoriented tomographic views of the myocardium can be a useful index to quantitatively assess various heart conditions where the myocardium lacks perfusion either between rest and stress studies or similar conditions in longitudinal studies.
Abstract: Image data fusion has been developed over the last decade as an important additional visual diagnostic tool to integrate the growing amount of imaging data obtained from different medical imaging modalities. The overwhelming amount of digital information calls for data consolidation to improve clinical treatment strategies based upon anatomical and physiological imaging. Three different low level image data fusion techniques are described and their characteristics are illustrated with some rare yet key examples. We used MR images to show neurodegeneration in the cerebral peduncle of the midbrain and found that image data fusion using colors can be a valuable tool to visually assess and quantify the loss of neural cells in the Substantia Nigra pars compacta in Parkinson's disease.
Abstract: RATIONALE AND OBJECTIVES: Segmented inversion recovery (IR) ratio imaging (SIRRIM) has been established as a sensitive tool to assess neurodegeneration of the substantia nigra pars compacta (SN(C)) in patients with idiopathic Parkinson disease (IPD). The obtained results suggest the possibility of magnetic resonance imaging (MRI) as a biological marker for IPD. The strength and a parsimonious analysis of the technique are discussed to assess the potential of using MRI as a biological marker for IPD and improve the differential diagnosis of sporadic Parkinson disease. Our hypothesis states that the magnetic resonance SIRRIM technique allows direct visualization and quantitation of neural cell loss in the SN(C) and therefore could become a reliable biological marker for Parkinson disease. To achieve this goal, some key aspects of data acquisition and data analysis need to be addressed. The clinical impact of the SIRRIM technique could be considerable, considering that it might become a viable surrogate to other techniques. PATIENTS AND METHODS: Twelve patients with IPD and 12 age-matched control subjects were imaged by using the SIRRIM technique based on two IR imaging sequences that were designed to suppress white and gray matter to assess loss of neural cells in situ by means of a ratio image (white matter suppressed image to gray matter suppressed image). The radiological index was correlated with the Unified Parkinson Disease Rating Scale (UPDRS) for patients with IPD. RESULTS: All patients with IPD were identified correctly, and full dichotomization between healthy volunteers and patients was obtained with our database. Our SIRRIM technique shows that it can be used to rule out Parkinson disease from essential tremor and other forms of Parkinsonism, such as progressive supranuclear palsy and multisystem atrophy. In addition, it is sensitive enough to identify patients with early-stage IPD. CONCLUSION: The hypothesis of using SIRRIM as a biological marker to assess IPD is supported by excellent correlation with clinical UPDRS scoring and has proved useful for the evaluation and quantitation of neurodegeneration with our SIRRIM technique, showing, in addition, that the differential diagnosis of IPD can be improved. Technical aspects of acquisition and data processing that need to be addressed can be overcome. It ultimately confirms that our objectives can be achieved and allows us to expect assessment of the progressive development of neurodegeneration in longitudinal studies and the putative neuroprotective approaches taken during the evolution of the disease.
Abstract: Segmented inversion recovery ratio imaging (SIRRIM) was introduced in previous works to investigate selective neurodegeneration in idiopathic Parkinson’s disease. Turbo GRAPPA inversion recovery is now explored to assess neurodegeneration in the substantia nigra.
Abstract: OBJECTIVE: Digitalization of analogue gamma cameras systems, using special acquisition boards in microcomputers and appropriate software for acquisition and processing of nuclear medicine images is described in detail. MATERIAL AND METHODS: Microcomputer integrated systems interconnected by means of a Local Area Network (LAN) and connected to several gamma cameras have been implemented using specialized acquisition boards. The PIP software (Portable Image Processing) was installed on each microcomputer to acquire and preprocess the nuclear medicine images. A specialized image processing software has been designed and developed for these purposes. This software allows processing of each nuclear medicine exam, in a semiautomatic procedure, and recording of the results on radiological films. RESULTS:. A stable, flexible and inexpensive system which makes it possible to digitize, visualize, process, and print nuclear medicine images obtained from analogue gamma cameras was implemented in the Nuclear Medicine Division. Such a system yields higher quality images than those obtained with analogue cameras while keeping operating costs considerably lower (filming: 24.6%, fixing 48.2% and developing 26%.) CONCLUSIONS: Analogue gamma camera systems can be digitalized economically. This system makes it possible to obtain optimal clinical quality nuclear medicine images, to increase the acquisition and processing efficiency, and to reduce the steps involved in each exam.
Abstract: RATIONALE AND OBJECTIVES: Recently developed MR imaging techniques using inversion recovery are a sensitive tool to identify and quantify morphologic changes in the substantia nigra due to neurodegeneration. Using a semi-automated computer segmentation technique to isolate the substantia nigra pars compacta (SN(c)), we propose a colored image fusion technique to visually assess the sites of damage in the SN(c) and integrate the information obtained from two implemented inversion-recovery sequences. PATIENTS AND METHODS: Six patients and six age-matched control subjects were scanned using a combination of two MR imaging inversion-recovery (IR) pulse sequences. A subgroup of them was used to develop our technique. Images were blended together into a final (RGBA) image, where A stands for the alpha channel describing transparency. RESULTS: Abnormalities in the SN(c) can be accurately assessed in location, shape, and variations of signal intensities within the segmented SN(c) by varying the transparency (alpha) channel of the color fusion image. Several previous findings such as the lateral-medial gradient of signal change and a ventral-dorsal broadening of the pars compacta are accompanied by an overall mild-to-severe heterogeneity of neurodegeneration patterns. CONCLUSION: Color fusion techniques revealed subtle changes in the neurodegeneration of the substantia nigra in Parkinson disease, which can be helpful for an objective and hence effective visual assessment of disease progression.
Abstract: OBJECTIVE: To assess the acute effect of a lung recruitment maneuver (LRM) on lung morphology in patients with acute lung injury (ALI) or acute respiratory distress syndrome (ARDS). PATIENTS: Ten patients with ALI/ARDS on mechanical ventilation. DESIGN: Prospective clinical study. SETTING: Computed tomography (CT) scan facility in a teaching hospital. INTERVENTIONS: An LRM performed by stepwise increases in positive end-expiratory pressure (PEEP) of up to 30-40 cm H(2)O. Lung basal CT sections were taken at end-expiration (patients 1 to 5), and at end-expiration and end-inspiration (patients 6 to 10). Arterial blood gases and static compliance (C(st)) were measured before, during and after the LRM. MEASUREMENTS AND MAIN RESULTS: Poorly aerated and non-aerated tissue at PEEP 10 cm H(2)O accounted for 60.0+/-29.1% of lung parenchyma, while only 1.1+/-1.8% was hyperinflated. Increasing PEEP to 20 and 30 cm H(2)O, compared to PEEP 10 cm H(2)O, decreased poorly aerated and non-aerated tissue by 16.2+/-28.0% and 33.4+/-13.8%, respectively ( p<0.05). This was associated with an increase in PaO(2) and a decrease in total static compliance. Inspiration increased alveolar recruitment at all PEEP levels. Hyperinflated tissue increased up to 2.9+/-4.0% with PEEP 30 cm H(2)O, and to a lesser degree with inspiration. No barotrauma or severe hypotension occurred. CONCLUSIONS: Lung recruitment maneuvers improve oxygenation by expanding collapsed alveoli without inducing too much hyperinflation in ALI/ARDS patients. An LRM during the CT scan gives morphologic and functional information that could be useful in setting ventilatory parameters.
Abstract: Lung computed tomography (CT) is being used increasingly to assess lung morphology in patients on mechanical ventilation. Lung CT under known levels of airway pressure (dynamic CT) can also assess the response of lung parenchyma to ventilatory therapy. We report a patient with acute respiratory distress syndrome secondary to descending necrotizing mediastinitis, in whom lung dynamic CT oriented ventilatory management. Independent lung ventilation improved gas exchange and helped patient recovery.
Abstract: RATIONALE AND OBJECTIVES: The authors designed a segmentation technique that requires only minimal operator input at the initial and final supervision stages of segmentation and has computer-driven segmentation as the primary determinant of lesion boundaries. The technique was applied to compute total T2-hyperintense lesion volumes in patients with multiple sclerosis (MS). A semi-automated segmentation technique is presented and shown to have a test-retest reliability of <5%. MATERIALS AND METHODS: The method used a single segmented section with MS lesions. A probabilistic neural net performed segmentation into four tissue classes after supervised training. This reference section was deconstructed into the entire set of possible 4 x 4-pixel subregions, which was used to segment all-brain sections in steps of 4 x 4-pixel, adjacent image blocks. Intra- and interimage variabilities were tested by using 3-mm-thick, T2-weighted, dual-echo, spin-echo MR images from five patients, each of whom was imaged twice on the same day. Five different reference sections and three temporally separated. training sessions involving the same reference section were used to test the segmentation technique. RESULTS: The coefficient of variation ranged from 0.013 to 0.068 (mean +/- standard deviation, 0.037 +/- 0.039) for results from five different reference sections for each brain and from 0.007 to 0.037 (mean, 0.027 +/- 0.021) for brains segmented with the same reference section on three temporally separated occasions. Test-retest (intra-imaging) reliability did not exceed 5% (except for a small lesion load of 1 cm3 in one patient). Interimaging differences were approximately 10%. CONCLUSION: The segmentation technique yielded intra-imaging variabilities (2%-3%, except for very small MS lesion loads) that compare favorably with previously published results. New repositioning techniques that minimize imaging-repeat imaging variability could make this approach attractive for resolving MS lesion detection problems.
Abstract: RATIONALE AND OBJECTIVES: To quantitate multiple sclerosis (MS) lesions in the brain by using computerized techniques. METHODS: MS lesions from five patients were quantitated with magnetic resonance (MR) imaging by using three approaches: a probabilistic neural network (PNN) approach, a semiautomated method that uses a bifeature space approach with operator intervention at each section, and the "gold standard" of manual outlining of lesions. Each patient underwent two MR studies in 1 day. RESULTS: The PNN approach allows reasonable quantitation of large data sets with minimal operator input. The mean intraobserver error for the PNN approach was competitive with the more time-consuming bifeature space approach (5.2% vs 4.4%, respectively). On average, both computer assisted methods performed better than the manual method (mean intraobserver error, 10.1%). CONCLUSION: The agreement between the two computerized quantitation approaches was good. The number of interactive steps was substantially reduced with the PNN technique, leading to minimal operator intervention time.
Abstract: RATIONALE AND OBJECTIVES: We computed generalized fractal dimensions for high-resolution computed tomography (HRCT) images to investigate their value in the discrimination and quantification of idiopathic pulmonary fibrosis (IPF) from normal lung parenchyma. METHODS: A probability distribution that was based on the pixel value in each image was used to compute capacity, information, and higher fractal dimensions for a series of 52 HRCT slices obtained from four patients. Qualitative classification of normal, mild, moderate, and severe IPF cases was achieved by computing the following parameter: DD = D0 - 2D1 + D2, where D0, D1, and D2 represents the capacity, information, and pair correlation dimensions, respectively. A multiple linear regression analysis using morphometric quantification for the set of 52 slices was tested for all possible combinations of the parameters D0, D1, D2, and D3. The generalizability of the model was tested by predicting the extent of IPF for each patient from a regression model computed with the remaining slices in the database. RESULTS: The best regression results were obtained using the independent parameters D1 and D2 to quantify the extent of diseased lung parenchyma. The technique was tested with 48 slices from 12 new patients. The results indicated that the extent of IPF could be predicted within the confidence limits given by the regression analysis. CONCLUSION: The extent of IPF can be predicted well within the 90% confidence interval given by the model. The width of the confidence interval decreases as the number of slices used in the linear regression model increases. This operator-independent quantitative technique may be useful in the follow-up of patients with IPF.
Abstract: "Few subjects in neurology have been associated with as much and paradox as the behavioral afflictions of the prefrontal cortex" (Marsel Mesulam, 2002).
The case of Phineas Gage, the first well-described patient with a prefrontal lesion, revealed that this sort of lesion could cause severe trouble in everyday life and a profound disturbance of personality. Disturbances of patients with prefrontal lesions are a consequence of disruptions in the main role of the prefrontal cortex:
executive control, i.e., a cognitive function underlying the human faculty to act or think not only in reaction to external events but also to internal goals and states. The neuropsychological study of patients with prefrontal lesions suggests the existence of three dimensions of executive control subserved by different prefrontal regions: emotional, motivational, and cognitive. Indeed, damage to the prefrontal cortex may lead to a set of symptoms collectively known as “dysexecutive syndrome,” characterized by changes in those dimensions. In this chapter, we discuss how the neuropsychological method, i.e., the study of brain–behavior relationship in patients with brain lesions, contributes to a better understanding of the role of the prefrontal cortex in behavior control.
