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T Achenbach

Publications and source records attributed to T Achenbach.

12 recordsLinked to original sources
PubMed2006

Dissemination of hepatocellular carcinoma is mediated via chemokine receptor CXCR4.

In different tumour entities, expression of the chemokine receptor 4 (CXCR4) has been linked to tumour dissemination and poor prognosis. Therefore, we evaluated, if the expression of CXCR4 exerts similar effects in human hepatocellular carcinoma (HCC). Expression analysis and functional assays were performed in vitro to elucidate the impact of CXCL12 on human hepatoma cells lines. In addition, expression of CXCR4 was evaluated in 39 patients with HCC semiquantitatively and correlated with both, tumour and patients characteristics. Human HCC and hepatoma cell lines displayed variable intensities of CXCR4 expression. Loss of p53 function did not impact on CXCR4 expression. Exposure to CXCL12 mediated a perinuclear translocation of CXCR4 in Huh7/Hep3B cells and increased the invasive potential of Huh7 cells. In HCC patients, CXCR4 expression significantly correlated with progressed local tumours (T-status; P=0.006), lymphatic metastasis (N-status; P=0.005) and distant dissemination (M-status; P=0.009), as well as with a decreased 3-year-survival rate (P=0.01). In summary, strong expression of CXCR4 is significantly associated with progressed hepatocellular cancer.

Active Transport, Cell Nucleus↗
PubMed2006

[Quantification of pulmonary emphysema in multislice-CT using different software tools].

PURPOSE: The data records of thin-section MSCT of the lung with approx. 300 images are difficult to use in manual evaluation. A computer-assisted pre-diagnosis can help with reporting. Furthermore, post-processing techniques, for instance, for quantification of emphysema on the basis of three-dimensional anatomical information might be improved and the workflow might be further automated. MATERIALS AND METHODS: The results of 4 programs (Pulmo, Volume, YACTA and PulmoFUNC) for the quantitative analysis of emphysema (lung and emphysema volume, mean lung density and emphysema index) of 30 consecutive thin-section MSCT datasets with different emphysema severity levels were compared. The classification result of the YACTA program for different types of emphysema was also analyzed. RESULTS: Pulmo and Volume have a median operating time of 105 and 59 minutes respectively due to the necessity for extensive manual correction of the lung segmentation. The programs PulmoFUNC and YACTA, which are automated to a large extent, have a median runtime of 26 and 16 minutes, respectively. The evaluation with Pulmo and Volume using 2 different datasets resulted in implausible values. PulmoFUNC crashed with 2 other datasets in a reproducible manner. Only with YACTA could all graphic datasets be evaluated. The lung volume, emphysema volume, emphysema index and mean lung density determined by YACTA and PulmoFUNC are significantly larger than the corresponding values of Volume and Pulmo (differences: Volume: 119 cm(3)/65 cm(3)/1 %/17 HU, Pulmo: 60 cm(3)/96 cm(3)/1 %/37 HU). Classification of the emphysema type was in agreement with that of the radiologist in 26 panlobular cases, in 22 paraseptalen cases and in 15 centrilobular emphysema cases. CONCLUSION: The substantial expenditure of time obstructs the employment of quantitative emphysema analysis in the clinical routine. The results of YACTA and PulmoFUNC are affected by the dedicated exclusion of the tracheobronchial system. These fully automatic tools enable not only fast quantification without manual interaction, but also a reproducible measurement without user dependence.

Adolescent↗
PubMed2005

[Self-organizing neural networks for automatic detection and classification of contrast (media) enhancement of lesions in dynamic MR-mammography].

PURPOSE: Investigation and statistical evaluation of "Self-Organizing Maps," a special type of neural networks in the field of artificial intelligence, classifying contrast enhancing lesions in dynamic MR-mammography. MATERIAL AND METHODS: 176 investigations with proven histology after core biopsy or operation were randomly divided into two groups. Several Self-Organizing Maps were trained by investigations of the first group to detect and classify contrast enhancing lesions in dynamic MR-mammography. Each single pixel's signal/time curve of all patients within the second group was analyzed by the Self-Organizing Maps. The likelihood of malignancy was visualized by color overlays on the MR-images. At last assessment of contrast-enhancing lesions by each different network was rated visually and evaluated statistically. RESULTS: A well balanced neural network achieved a sensitivity of 90.5 % and a specificity of 72.2 % in predicting malignancy of 88 enhancing lesions. Detailed analysis of false-positive results revealed that every second fibroadenoma showed a "typical malignant" signal/time curve without any chance to differentiate between fibroadenomas and malignant tissue regarding contrast enhancement alone; but this special group of lesions was represented by a well-defined area of the Self-Organizing Map. DISCUSSION: Self-Organizing Maps are capable of classifying a dynamic signal/time curve as "typical benign" or "typical malignant." Therefore, they can be used as second opinion. In view of the now known localization of fibroadenomas enhancing like malignant tumors at the Self-Organizing Map, these lesions could be passed to further analysis by additional post-processing elements (e.g., based on T2-weighted series or morphology analysis) in the future.

Algorithms↗
PubMed2005

[Does HRCT-emphysema index represent the entire lung?].

PURPOSE: : Comparison of emphysema index derived of thin section MD-CT of the entire lung volume and HRCT, simulated by calculation of every twentieth image of the whole data-set. MATERIALS AND METHODS: Pulmonary emphysema was quantified by semiautomatic, segmentation of lung borders and assessment of lung volume and emphysema volume within these borders. The emphysema index (pixel index) was calculated. Statistical analysis was done by the sign-test and Bland-Altman-analysis. RESULTS: Median lung volume, emphysema volume and emphysema index are significantly higher in simulated HRCT. Median lung volume (emphysema volume) calculated by HRCT is 5118 ml (407 ml) and 5040 ml (367 ml) calculated by the entire MD-CT data-set, representing differences of 1 and 8 % related to the median lung and emphysema volumes. Emphysema index is 0.09 (HRCT) and 0.08 (MD-CT). CONCLUSION: HRCT overrates emphysema index compared to thin section MD-CT of the entire lung volume.

Adolescent↗
PubMed2004

[Fully automatic detection and quantification of emphysema on thin section MD-CT of the chest by a new and dedicated software].

PURPOSE: Introduction of a novel software tool (YACTA -- yet another CT analyzer) for detection and quantification of pulmonary emphysema in thin-slice chest MDCT data sets. MATERIALS AND METHODS: Consisting of grey-level threshold-based algorithms (e. g., region-growing), expert rules and morphological image postprocessing YACTA segments the tracheobronchial tree prior to the detection and quantification of pulmonary emphysema. In addition to general parameters, such as the mean lung density (MLD) and the emphysema index (EI -- also described as pixel index PI), the previously described bullae index (BI) is transformed into a three-dimensional parameter for a morphological description of emphysema. A first evaluation of chest MDCT data sets of 11 patients was performed as well as a comparison of MLD, lung volume (LV), emphysema volume (EV) and PI calculated with two established commercial tools of Siemens Medical Solutions (Volume and Pulmo). Furthermore, the BI was calculated with YACTA. RESULTS: YACTA processed the image data without manual interaction and demonstrated more user-comfort than Volume and Pulmo software, which require manual correction especially for lung segmentation at the hilar regions to separate central airways from lung parenchyma. MLD, LV, and EV values calculated with YACTA were systematically higher (Pulmo: + 50 HU/+ 597 ml/+ 159 ml; Volume: + 32 HU/+ 110 ml/+ 155 ml). Different segmentation algorithms are responsible for this: YACTA includes areas not assessed by mere threshold-based techniques. Constantly lowered LV values of Pulmo are caused by a missing dilatation algorithm. The error correction as a special feature of YACTA results in increased emphysema volumes and indices. The segmentation of the tracheobronchial tree lowers the part of airways falsely classified as emphysema. CONCLUSION: The new developed software shows higher user comfort as established by semi-automated tools. RESULTS: of LV, EV, MLD and PI are comparable or moderately different. Automatic calculation of a BI is possible, providing information about bullous morphology of pulmonary emphysema. Further studies are necessary to correlate data with clinical or pathological parameters.

Adult↗
PubMed2003

[Computer aided diagnosis in chest radiology - current topics and techniques].

The proliferation of digital data sets and the increasing amount of images, e. g. through the use of multislice spiral CT or multiple follow-up examinations in the context of new therapies, are ideal prerequisites for computer-aided diagnosis (CAD) in chest radiology. Multiple studies have described the applications and advantages of computer assistance in performing different diagnostic tasks. More powerful computers will enable the introduction of these systems into the clinical routine and could provide an enormous increase in morphological and functional information. The commercial introduction of tools for detection and visualization of pulmonary nodules has already begun. This is one of the most widely-reported applications in view of the ongoing studies on lung cancer screening. The next generation of tools will improve the diagnosis of emphysema through detection, quantification and classification. Many more uses are being developed, for instance the detection and classification of infiltrates, volume measurements or functional pulmonary imaging (e. g. dynamic ventilation CT or (3)Helium-MRI). Grossly simplified, most systems use a three level structure consisting of segmentation/feature extraction, classification of extracted features and an output unit. The output can be mere visualization through color-coding, volume measurements or calculated probabilities. The output supports the radiologist in establishing his findings and preparing differential and final diagnoses as well as providing quantitative data for follow-up studies. Different techniques are used for segmentation of lung areas as the basis for a variety of applications. Some commonly-used techniques for this and other tasks are density masks and threshold-based algorithms. Data processing is predominantly carried out with Bayesian classifiers or neural networks. This article describes the current status of research and provides insight into the common schemes and capabilities of the systems. It focuses particularly on common topics such as segmentation, volume measurement, detection of pulmonary nodules, quantification of emphysema and analysis of ground glass opacities.

Diagnosis, Computer-Assisted↗
PubMed2003

Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography.

The aim of this study was to evaluate the capability of improved artificial neural networks (ANN) and additional novel training methods in distinguishing between benign and malignant breast lesions in contrast-enhanced magnetic resonance-mammography (MRM). A total of 604 histologically proven cases of contrast-enhanced lesions of the female breast at MRI were analyzed. Morphological, dynamic and clinical parameters were collected and stored in a database. The data set was divided into several groups using random or experimental methods [Training & Testing (T&T) algorithm] to train and test different ANNs. An additional novel computer program for input variable selection was applied. Sensitivity and specificity were calculated and compared with a statistical method and an expert radiologist. After optimization of the distribution of cases among the training and testing sets by the T & T algorithm and the reduction of input variables by the Input Selection procedure a highly sophisticated ANN achieved a sensitivity of 93.6% and a specificity of 91.9% in predicting malignancy of lesions within an independent prediction sample set. The best statistical method reached a sensitivity of 90.5% and a specificity of 68.9%. An expert radiologist performed better than the statistical method but worse than the ANN (sensitivity 92.1%, specificity 85.6%). Features extracted out of dynamic contrast-enhanced MRM and additional clinical data can be successfully analyzed by advanced ANNs. The quality of the resulting network strongly depends on the training methods, which are improved by the use of novel training tools. The best results of an improved ANN outperform expert radiologists.

Algorithms↗
PubMed2002

Chemoembolization for primary liver cancer.

AIMS: For most patients with primary liver cancer surgical treatment is not feasible and prognosis without treatment is poor. We aimed to assess the morbidity and efficacy of transarterial chemoembolization (TACE) with lipiodol and mitomycin C in these patients in a prospective case-control study. METHODS: From August 1996 to May 2000 22 patients with non-resectable hepatocellular carcinoma were treated with TACE. In case of radiological or tumour-marker response, treatment was repeated after 4--6 weeks, up to seven times per patient. RESULTS: Morbidity was 23% and usually minor, no patient died within 30 days of treatment. A decrease in size of the reference tumour or constant tumour-size in CT-scan were observed in 14 of 20 patients (70%) and of the 19 patients with elevated AFP-serum levels 12 (63%) had an AFP reduction following treatment. The median survival time was 14 months with a 1- and 2-year survival rate of 69% and 29%, respectively. Survival was not different in radiological or AFP responders vs non-responders. CONCLUSION: While TACE with lipiodol and mitomycin C for primary liver cancer is associated with considerable antitumoural efficacy, as demonstrated by tumour marker and radiological response, an effect on patient survival is not evident. New treatment options with an impact on survival are needed for these patients.

Aged↗
PubMed2000

Cryotherapy for liver metastases.

Cryotherapy is undergoing a renaissance in the treatment of nonresectable liver tumors. In a prospective case control study we assessed the morbidity, mortality, and efficacy of hepatic cryotherapy for liver metastases. Between January 1996 and September 1999 a total of 54 cryosurgical procedures were performed on 49 patients (median age 66 years, 21 women) with liver metastases. Patient, tumor, and operative details were recorded prospectively. Liver metastases originated from colorectal cancer (n=37), gastric cancer (n=3), renal cell carcinoma (n=2), and other primaries (n=7). Median follow-up was 13 months (1-32). The median number of liver metastases was 3 (range 1-10) with a median diameter of 3.9 cm (range 1.5-11). Twenty-one patients (43%) had cryoablation only, and 28 (57%) had liver resection in combination with cryoablation. One patient (2%) died within 30 postoperative days. Another 13 patients (27%) developed reversible complications. In 19 of 25 patients (76%) with preoperatively elevated serum CEA and colorectal metastases it returned to the normal range postoperatively. Twenty-eight patients (57%) developed tumor recurrence, eight of which with involvement of the cryosite. Overall median survival patients was 23 months, and survival in patients with colorectal metastases was 29 months. Hepatic cryotherapy is associated with tolerable morbidity and mortality. Efficacy is demonstrated by tumor marker results. Survival data are promising; however, long-term results must be provided to allow comparison with other treatment modalities.

Adult↗
PubMed1990

The Mother-Infant Transaction Program. The content and implications of an intervention for the mothers of low-birthweight infants.

A brief, economic neonatal intervention based on the transactional model of development and influenced predominantly by the conceptual design of the Neonatal Behavioral Assessment Scale was implemented in an intensive care nursery with the mothers of a group of low-birthweight infants. The development of the intervention group was compared with that of a similar group of low-birthweight infants who did not receive the intervention and contrasted with that of a group of normal-birthweight infants. The intervention had a significant effect on maternal adjustment and perception of the infant at 6 months. No significant effect on infant cognitive development was apparent until 36 months (that is, 31 months after the intervention had ceased). The intervention effect was even more significant at 48 months. It appeared that the two low-birthweight groups had progressively diverged after 12 months, the intervention group rising until it approximated the normal-birthweight group in cognitive development, whereas the low-birthweight control group deteriorated. The economical nature of the MITP, its unique (although delayed) benefits, and the apparent durability of the intervention effect, suggest that this intervention program has important theoretical and practical implications and potentially far-reaching applications.

Child Development↗