P. Waliszewski

Reducing infection rates after prostate biopsy

Over the years, prostate biopsy has become the gold-standard technique for diagnosing prostate carcinoma. Worldwide, several million prostate biopsies are performed every year, most commonly using the transrectal approach. Preoperative antibiotic prophylaxis with fluoroquinolones has been shown to be effective for reducing infection rates. However, in recent years, an increase in febrile infection rates after transrectal prostate biopsy (from 1% to 4%) has been reported in retrospective and prospective studies. The predominant risk factor for infection seems to be the presence of fluoroquinolone-resistant bacteria in faeces. Patients at risk of fluoroquinolone resistance should receive carefully selected antibiotics at sufficient concentrations to be effective. Targeted prophylaxis after rectal flora swabbing has been shown to be efficacious compared with empirical antibiotic prophylaxis. Several forms of bowel preparations are under investigation, although none have yet been shown to significantly reduce infection rates. Perineal prostate biopsy is currently being evaluated as a strategy for preventing the inoculation of rectal flora, but limited data support this approach at present.

On the relationship between tumor structure and complexity of the spatial distribution of cancer cell nuclei: a fractal geometrical model of prostate carcinoma.

A risk of the prostate cancer patient is defined by both the objective and subjective criteria, that is, PSA concentration, Gleason score, and pTNM‐stage. The subjectivity of tumor grading influences the risk assessment owing to a large inter‐ and intra‐observer variability. Pathologists propose a central prostate pathology review as a remedy for this problem; yet, the review cannot eliminate the subjectivity from the diagnostic algorithm. The spatial distribution of cancer cell nuclei changes during tumor progression. It implies changes in complexity measured by the capacity dimension D0, the information dimension D1, and the correlation dimension D2.

Methylation analysis of histone H4K12ac-associated promoters in sperm of healthy donors and subfertile patients

BackgroundHistone to protamine exchange and the hyperacetylation of the remaining histones are hallmarks of spermiogenesis. Acetylation of histone H4 at lysine 12 (H4K12ac) was observed prior to full decondensation of sperm chromatin after fertilization suggesting an important role for the regulation of gene expression in early embryogenesis. Similarly, DNA methylation may contribute to gene silencing of several developmentally important genes. Following the identification of H4K12ac-binding promoters in sperm of fertile and subfertile patients, we aimed to investigate whether the depletion of histone-binding is associated with aberrant DNA methylation in sperm of subfertile men. Furthermore, we monitored the transmission of H4K12ac, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) from the paternal chromatin to the embryo applying mouse in vitro fertilization and immunofluorescence.ResultsChromatin immunoprecipitation (ChIP) with anti-H4K12ac antibody was performed with chromatin isolated from spermatozoa of subfertile patients with impaired sperm chromatin condensation assessed by aniline blue staining. Fertile donors were used as control. DNA methylation analysis of selected H4K12ac-interacting promoters in spermatozoa was performed by pyrosequencing.Depletion of binding sites for H4K12ac was observed within the following developmentally important promoters: AFF4, EP300, LRP5, RUVBL1, USP9X, NCOA6, NSD1, and POU2F1. We found 5% to 10% hypomethylation within CpG islands of selected promoters in the sperm of fertile donors, and it was not significantly altered in the subfertile group. Our results demonstrate that the H4K12ac depletion in selected developmentally important promoters of subfertile patients was not accompanied by a change of DNA methylation.Using a murine model, immunofluorescence revealed that H4K12ac co-localize with 5mC in the sperm nucleus. During fertilization, when the pronuclei are formed, the paternal pronucleus exhibits a strong acetylation signal on H4K12, while in the maternal pronucleus, there is a permanent increase of H4K12ac until pronuclei fusion. Simultaneously, there is an increase of the 5hmC signal and a decrease of the 5mC signal.ConclusionsWe suggest that aberrant histone acetylation within developmentally important gene promoters in subfertile men, but not DNA methylation, may reflect insufficient sperm chromatin compaction affecting the transfer of epigenetic marks to the oocyte.

On complexity and homogeneity measures in predicting biological aggressiveness of prostate cancer; Implication of the cellular automata model of tumor growth

We propose a novel approach for the quantitative evaluation of aggressiveness in prostate carcinomas.

Fractal geometry in the objective grading of prostate carcinoma

ZusammenfassungHintergrundEin möglicher Ansatz komplexe Muster im Tumorgewebe objektiv klassifizieren zu können, ist die mathematische Erfassung der Verteilung von Tumorzellkernen, die als geometrische Repräsentation der Krebszellen dienen, durch fraktale Dimensionen. Die Existenz, sowie die Veränderungen der fraktalen Struktur der Verteilung der Zellkerne haben wichtige Konsequenzen für eine objektive Klassifizierung der Tumoren. Weiterhin kann auch die Komplexität des Tumorwachstums in verschiedenen Karzinomen sowie die interzellulären Interaktionen im Gewebesystem dadurch verglichen werden.ErgebnisseIn dieser Arbeit stellen wir eine theoretische Einführung in die fraktale Geometrie sowie in die Algorithmen, die auf der Rényi-Familie der fraktalen Dimensionen basieren, dar. Wir führen ein geometrisches Modell für die Bewertung von Prostatakarzinomgeweben ein und erklären den Zusammenhang zwischen dem geometrischen Tumormuster und den fraktalen Dimensionen der Rényi-Familie.AbstractBackgroundA possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other.ResultsWe present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.BACKGROUND A possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other. RESULTS We present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.

Fraktale Geometrie zur Objektivierung des Gradings beim Prostatakarzinom

ZusammenfassungHintergrundEin möglicher Ansatz komplexe Muster im Tumorgewebe objektiv klassifizieren zu können, ist die mathematische Erfassung der Verteilung von Tumorzellkernen, die als geometrische Repräsentation der Krebszellen dienen, durch fraktale Dimensionen. Die Existenz, sowie die Veränderungen der fraktalen Struktur der Verteilung der Zellkerne haben wichtige Konsequenzen für eine objektive Klassifizierung der Tumoren. Weiterhin kann auch die Komplexität des Tumorwachstums in verschiedenen Karzinomen sowie die interzellulären Interaktionen im Gewebesystem dadurch verglichen werden.ErgebnisseIn dieser Arbeit stellen wir eine theoretische Einführung in die fraktale Geometrie sowie in die Algorithmen, die auf der Rényi-Familie der fraktalen Dimensionen basieren, dar. Wir führen ein geometrisches Modell für die Bewertung von Prostatakarzinomgeweben ein und erklären den Zusammenhang zwischen dem geometrischen Tumormuster und den fraktalen Dimensionen der Rényi-Familie.AbstractBackgroundA possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other.ResultsWe present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.BACKGROUND A possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other. RESULTS We present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.

(Objective grading of prostate carcinoma based on fractal dimensions : Gleason 3 + 4 = 7a ≠ Gleason 4 + 3 = 7b.)

BACKGROUND Significant intra- and interobserver variability ranging between 40 and 80% is observed in tumor grading of prostate carcinoma. By combining geometric and statistical methods, an objective system of grading can be designed. MATERIAL AND METHODS The distributions of cell nuclei in two-dimensional patterns of prostate cancer classified subjectively as Gleason score 3+3, 3+4, 4+3, 4+4, 4+5, 5+4, and 5+5 were analyzed with algorithms measuring the global fractal dimensions of the Rényi family and with the algorithm for the local connected fractal dimension (LCFD). RESULTS The dimensions for global fractal capacity, information, and correlation (standard deviation) were 1.470 (045), 1.528 (046), and 1.582 (099) for homogenous Gleason grade 3 (n = 16), 1.642 (034), 1.678 (041), and 1.673 (084) for homogenous Gleason grade 4 (n=18), and 1.797 (042), 1.791 (026), and 1.854 (031) for homogenous Gleason grade 5 (n=12), respectively. The LCFD algorithm can be used to distinguish both qualitatively and quantitatively between mixed and heterogeneous patterns, such as Gleason score 3+4=7a (intermediate risk cancer) and Gleason score 4+3=7b (high-risk cancer). Sensitivity of the method is 89.3%, and specificity 84.3%. CONCLUSION The method of fractal geometry enables both an objective and quantitative grading of prostate cancer.

Fraktale Geometrie zur Objektivierung des Gradings beim Prostatakarzinom@@@Fractal geometry in the objective grading of prostate carcinoma

ZusammenfassungHintergrundEin möglicher Ansatz komplexe Muster im Tumorgewebe objektiv klassifizieren zu können, ist die mathematische Erfassung der Verteilung von Tumorzellkernen, die als geometrische Repräsentation der Krebszellen dienen, durch fraktale Dimensionen. Die Existenz, sowie die Veränderungen der fraktalen Struktur der Verteilung der Zellkerne haben wichtige Konsequenzen für eine objektive Klassifizierung der Tumoren. Weiterhin kann auch die Komplexität des Tumorwachstums in verschiedenen Karzinomen sowie die interzellulären Interaktionen im Gewebesystem dadurch verglichen werden.ErgebnisseIn dieser Arbeit stellen wir eine theoretische Einführung in die fraktale Geometrie sowie in die Algorithmen, die auf der Rényi-Familie der fraktalen Dimensionen basieren, dar. Wir führen ein geometrisches Modell für die Bewertung von Prostatakarzinomgeweben ein und erklären den Zusammenhang zwischen dem geometrischen Tumormuster und den fraktalen Dimensionen der Rényi-Familie.AbstractBackgroundA possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other.ResultsWe present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.BACKGROUND A possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other. RESULTS We present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.

Objektivierung des Tumorgradings bei Prostatakarzinomen anhand der fraktalen Dimensionen@@@Objective grading of prostate carcinoma based on fractal dimensions: Gleason 3 + 4 = 7a ≠ Gleason 4 + 3 = 7b@@@Gleason 3 + 4 = 7a ≠ Gleason 4 + 3 = 7b

BACKGROUND Significant intra- and interobserver variability ranging between 40 and 80% is observed in tumor grading of prostate carcinoma. By combining geometric and statistical methods, an objective system of grading can be designed. MATERIAL AND METHODS The distributions of cell nuclei in two-dimensional patterns of prostate cancer classified subjectively as Gleason score 3+3, 3+4, 4+3, 4+4, 4+5, 5+4, and 5+5 were analyzed with algorithms measuring the global fractal dimensions of the Rényi family and with the algorithm for the local connected fractal dimension (LCFD). RESULTS The dimensions for global fractal capacity, information, and correlation (standard deviation) were 1.470 (045), 1.528 (046), and 1.582 (099) for homogenous Gleason grade 3 (n = 16), 1.642 (034), 1.678 (041), and 1.673 (084) for homogenous Gleason grade 4 (n=18), and 1.797 (042), 1.791 (026), and 1.854 (031) for homogenous Gleason grade 5 (n=12), respectively. The LCFD algorithm can be used to distinguish both qualitatively and quantitatively between mixed and heterogeneous patterns, such as Gleason score 3+4=7a (intermediate risk cancer) and Gleason score 4+3=7b (high-risk cancer). Sensitivity of the method is 89.3%, and specificity 84.3%. CONCLUSION The method of fractal geometry enables both an objective and quantitative grading of prostate cancer.

Objektivierung des Tumorgradings bei Prostatakarzinomen anhand der fraktalen DimensionenObjective grading of prostate carcinoma based on fractal dimensions

BACKGROUND Significant intra- and interobserver variability ranging between 40 and 80% is observed in tumor grading of prostate carcinoma. By combining geometric and statistical methods, an objective system of grading can be designed. MATERIAL AND METHODS The distributions of cell nuclei in two-dimensional patterns of prostate cancer classified subjectively as Gleason score 3+3, 3+4, 4+3, 4+4, 4+5, 5+4, and 5+5 were analyzed with algorithms measuring the global fractal dimensions of the Rényi family and with the algorithm for the local connected fractal dimension (LCFD). RESULTS The dimensions for global fractal capacity, information, and correlation (standard deviation) were 1.470 (045), 1.528 (046), and 1.582 (099) for homogenous Gleason grade 3 (n = 16), 1.642 (034), 1.678 (041), and 1.673 (084) for homogenous Gleason grade 4 (n=18), and 1.797 (042), 1.791 (026), and 1.854 (031) for homogenous Gleason grade 5 (n=12), respectively. The LCFD algorithm can be used to distinguish both qualitatively and quantitatively between mixed and heterogeneous patterns, such as Gleason score 3+4=7a (intermediate risk cancer) and Gleason score 4+3=7b (high-risk cancer). Sensitivity of the method is 89.3%, and specificity 84.3%. CONCLUSION The method of fractal geometry enables both an objective and quantitative grading of prostate cancer.