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\begin{document}

\title{Pathology Associated with Adherent Perirenal Fat and its Clinical Effect}



\author[1]{Erman Ceyhan}%
\author[1]{Fatih Ileri}%
\author[1]{Fazıl Tuncay Aki}%
\author[1]{Mustafa Sertac Yazici}%
\author[1]{Musturay  Karcaaltincaba}%
\author[2]{Dilek Ertoy Baydar}%
\author[1]{Cenk Yucel Bilen}%
\affil[1]{Hacettepe University Faculty of Medicine}%
\affil[2]{Koc Universitesi}%


\vspace{-1em}



  
  \date{May 20, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Introduction The dissection of perirenal fat is of critical importance
to kidney surgery and ease of dissection is more important when using
minimally invasive approaches. This study aimed to determine the
clinical, radiological, and pathological significance of adherent
perirenal fat(APF). Materials and Methods This prospective study
included 22 patients scheduled for partial nephrectomy and 40 patients
for donor nephrectomy. Intra-operative fat dissection time was recorded
and the complexity of perirenal fat dissection was surgeon-classified as
easy, moderate, and difficult. Perirenal fat and subcutaneous fat
thickness was measured. Measurement of perirenal fat depth, and the
Hounsfield unit(HU) for both perirenal and subcutaneous fields was
performed using CT images. All specimens were submitted for
histopatological analysis. Researchers in each arm were blinded to other
researchers' data. Results Mean age of the patients was 51.3\selectlanguage{ngerman}±12.7years.
Mean perirenal fat dissection time was 15.0±13.5min. Patient
demographics, BMI, nor occupational status differed between the 3
complexity of perirenal fat dissection groups. Radiological findings
showed that there was a significant correlation between perirenal fat
depth and complexity of perirenal fat dissection(p\textless{}0.05), but
not with HU measurements or subcutaneous fat thickness. Surgeon
classification of the complexity of perirenal fat dissection was in
accordance with the duration of dissection(p\textless{}0.05).
Perinephric fat contained more fibrous tissue in the patients with
histologically proven APF than in those without(p\textless{}0.05).
Conclusions APF is a challenge during kidney surgery. Difficult
dissection prolongs the duration of surgery, which can lead to
complications. Perirenal fat thickness measured via pre-operative CT
might be used to predict APF.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


Pathology Associated with Adherent Perirenal Fat and its Clinical Effect

\emph{Erman CEYHAN} \textsuperscript{1o}, Fatih
ILERI\textsuperscript{1}, Fazil Tuncay AKI\textsuperscript{1}, Mustafa
Sertac YAZICI\textsuperscript{1}, Musturay
KARCAALTINCABA\textsuperscript{2}, Dilek ERTOY
BAYDAR\textsuperscript{3}, Cenk Yucel BILEN\textsuperscript{1}

\textsuperscript{1}Hacettepe University, School of Medicine, Department
of Urology, Ankara, Turkey

\textsuperscript{2}Hacettepe University, School of Medicine, Department
of Radiology, Ankara, Turkey

\textsuperscript{3}Ko\selectlanguage{ngerman}ç University, School of Medicine, Department of
Pathology, Istanbul, Turkey

Running title: Adherent Perirenal Fat

Declarations of interest: None.

Acknowledgments: This study did not received any funding. Authors have
nothing to declare.

Manuscript word count: 2985

Abstract word count: 250

Author contributions:

Research conception and design: EC, FI, MK, DEB, . Data acquisition: EC,
FI, FTA, MSY, MK, DEB, . Statistical analysis: EC, FI, DEB,. Data
analysis and interpretation: EC, DEB, . Drafting of the manuscript: EC,
DEB, CYB. Critical revision of the manuscript: EC, FTA, MSY, DEB, CYB.
Obtaining funding: N/A. Administrative, technical, or material support:
EC,. Supervision: DEB, CYB. Approval of the final manuscript: EC, FI,
FTA, MSY, DEB, CYB .

\textsuperscript{o} Corresponding author: Asst. Prof. Erman Ceyhan M.D.,
FEBU

Mailing address: Baskent University Konya Hospital, Department of
Urology

Hocacihan Mah. Saray Cad. No: 1, 42080 Selçuklu, Konya / Turkey

Tel: 0090 332 257 0600 / 3532 -- 3536

Fax: 0090 332 257 0637

Mobile phone: 0090 535 587 36 88

E-mail:\emph{erman\_ceyhan@yahoo.com}

Pathology Associated with Adherent Perirenal Fat and its Clinical Effect

\textbf{Abstract}

\textbf{Introduction}

The dissection of perirenal fat is of critical importance to kidney
surgery and ease of dissection is more important when using minimally
invasive approaches. This study aimed to determine the clinical,
radiological, and pathological significance of adherent perirenal
fat(APF).

\textbf{Materials and Methods}

This prospective study included 22 patients scheduled for partial
nephrectomy and 40 patients for donor nephrectomy. Intra-operative fat
dissection time was recorded and the complexity of perirenal fat
dissection was surgeon-classified as easy, moderate, and difficult.
Perirenal fat and subcutaneous fat thickness was measured. Measurement
of perirenal fat depth, and the Hounsfield unit(HU) for both perirenal
and subcutaneous fields was performed using CT images. All specimens
were submitted for histopatological analysis. Researchers in each arm
were blinded to other researchers' data.

\textbf{Results}

Mean age of the patients was 51.3±12.7years. Mean perirenal fat
dissection time was 15.0±13.5min. Patient demographics, BMI, nor
occupational status differed between the 3 complexity of perirenal fat
dissection groups. Radiological findings showed that there was a
significant correlation between perirenal fat depth and complexity of
perirenal fat dissection(p\textless{}0.05), but not with HU measurements
or subcutaneous fat thickness. Surgeon classification of the complexity
of perirenal fat dissection was in accordance with the duration of
dissection(p\textless{}0.05). Perinephric fat contained more fibrous
tissue in the patients with histologically proven APF than in those
without(p\textless{}0.05).

\textbf{Conclusions}

APF is a challenge during kidney surgery. Difficult dissection prolongs
the duration of surgery, which can lead to complications. Perirenal fat
thickness measured via pre-operative CT might be used to predict APF.

\textbf{Keywords} : Perirenal fat; dissection; nephrectomy; minimally
invasive surgical procedures; kidney

What is already known about this topic?

The ways of prediction of adherent perirenal fat before surgery have
been studied previously with complex scoring systems but there is only
one study which adresses the histopathology under this phenomenon.

What does this article add?

Results of this study revealed that there is no need for complex scoring
systems in order to predict adherent perirenal fat. Perirenal fat
thickness measured via pre-operative CT can predict adherent perirenal
fat single handedly. Also detailed histopathological investigation under
adherent perirenal fat has been reported by this study.

\emph{Abbreviations:}

APF: Adherent perirenal fat

CT: Computed tomography

BMI: Body mass index

HU: Hounsfield unit

MAP: Mayo Adhesive Probability

\textbf{Introduction}

The dissection of perirenal fat is of critical importance to kidney
surgery, especially in cases of partial and donor nephrectomy. Good
dissection of perirenal fat provides good exposure, easy manipulation,
and shorter surgical duration\textsuperscript{1,2}. In 10.6\%-55.2\% of
cases perirenal fat tissue is adhered to the kidney, which makes it
difficult to dissect; this phenomenon is referred to as adherent
perirenal fat(APF) or sticky perirenal fat\textsuperscript{2}.

Patient-related factors, including gender, and visceral and perinephric
fat thickness are clinically associated with the complexity of surgery
and surgical outcome\textsuperscript{1,3}. For predicting the complexity
of perirenal fat dissection many researchers suggest using such tools as
renal scoring systems and pre-operative computed tomography (CT)
measurement\textsuperscript{4,5}. Prediction of APF can help in choosing
the optimal surgical approach. Severe APF can complicate and hinder
minimally invasive surgery.

All relevant studies in the literature have emphasized the prediction of
APF pre-operatively, with very little attention to the underlying
pathophysiology. Recently, Dariane et al. published a study on the
histological changes linked to APF\textsuperscript{6}. The present study
aimed to determine the clinical, radiological, and pathological
significance of APF.

\textbf{Materials and Methods}

\textbf{Patient selection}

This prospective study included patients that were scheduled for partial
nephrectomy or donor nephrectomy between October 2016-June 2017.
Patients with a history of renal interventions and recurrent urinary
tract infection, and those without CT images were excluded from the
study. After exclusion of 6 patients, the remaining 62 adults were
included, of which 22 underwent partial nephrectomy and 40 underwent
donor nephrectomy. Type of surgical approach was chosen according to
surgeons preference and experience. The study was carried out with 3
arms; clinical phase; radiological measurement; histopathological
examination. The researchers in each arm were blinded to each other's
data. The study protocol was approved by our institutional ethics
committee (IRB No:GO16/669-26). All the patients provided written
informed consent before undergoing surgical intervention.

\textbf{Data collection}

Clinical data collection and intra-operative measurements were performed
by the same researcher(EC). Patient demographics, weight, height, body
mass index(BMI), and occupational status were recorded. Occupational
status was categorized as light workers and heavy workers. Patients that
worked in jobs requiring physical strength, such as construction,
farming, delivery, were categorized as heavy workers, whereas office
employees, housewives, and the unemployed were categorized as light
workers.

Surgery was performed by experienced surgeons (FTA, CYB or MSY). All
nephrectomies were performed via the transperitoneal approach. In order
to record surgical data the researcher in charge (EC) and an
observer(FI) were present during all surgical procedures. Perirenal fat
dissection time was recorded by a time observer (FI). The complexity of
perirenal fat dissection was classified by EC and divided into 3
categories; easy, moderate, and difficult. This classification was based
on the difficulty of dissection, capsular trauma during dissection,
bleeding, and unintentional injuries during removal of perirenal fat
from the kidney. In addition, maximum perirenal fat thickness(mm) and
maximum subcutaneous fat thickness(mm) were measured intra-operatively
by EC. The removed perirenal fat tissue was sent for histopathological
examination after measurement.

\textbf{Radiology}

All radiological measurements were performed by the same
radiologist(MK). Perirenal fat thickness was measured at the level of
the renal vein, from the posterior renal capsule to the posterior
abdominal wall using CT images. These measurements from CT images are
referred to as perirenal fat depth to eliminate confusion. The perirenal
field Hounsfield unit(HU) and subcutaneous fat HU(at the level of the
hilus) were recorded according to a circular region of interest
measuring 1 cm in diameter, using a PACS workstation and pre-operative
CT images.

\textbf{Pathology}

Following overnight fixation in 4\% formaldehyde at room temperature,
resected fat tissue was subjected to a routine paraffin embedding
procedure. Sections 5 \selectlanguage{greek}µ\selectlanguage{english}m thick were obtained from paraffin blocks and
initially stained with hematoxylin-eosin using a Shandon Varistain
Gemini\selectlanguage{ngerman}®(Shandon, Frankfurt) automated slide stainer. Additional
histochemical staining with periodic acid methenamine silver and
Masson's trichrome was performed to assess morphology and the degree of
fibrosis in greater detail. All light microscopic evaluations were
conducted using an Olympus BX53® optical microscope. Measurements were
performed using digital photos captured using an Olympus SC50 CMOS®
camera and the drawing line tools in CellSens Entry Imaging
v.1.13®(Olympus Europa SE \& Co. KG, Hamburg). Adipocyte diameter was
manually drawn and individually measured. In total, 350 adjacent
adipocytes were measured in each patient. Cells\textless{}35~\selectlanguage{greek}μ\selectlanguage{english}m were
excluded from analysis to avoid immature multilocular adipocytes.
Maximum adipocyte diameter and the presence of brown fat were noted
separately.

During microscopic examination the presence of fibrosis was observed in
some cases, primarily in the septae between fat lobules(i.e.,
perilobular fibrosis), around blood vessels(i.e., perivascular
fibrosis), and/or in the outermost Gerota's fascia(Figure 1). Collagen
fibers were organized in bundles of variable thickness and some
exhibited spiculated infiltration to the periphery of the fat lobules,
isolating a few adipocytes from the remainder of the tissue. Moreover,
some cases exhibited pericellular fibrosis consisting of thinner
collagen fibrils surrounding adipocytes, localized in areas far from
fibrotic bundles(Figure 2). The presence or absence of these features
was recorded in each case. Additionally, maximum thickness of the
collagen at Gerota's fascia and wall thickness of the thickest
vessel(from the endothelia to adventitia) in the resected fat were
measured, as described above. The number of vessels with a thick
wall(\textgreater{}100 \selectlanguage{greek}µ\selectlanguage{english}m) in a 1-cm\textsuperscript{2} area varied
according to patient and was scored as follows: 1: \textless{}3 vessels;
2: 3-5 vessels; 3: [?]6 vessels . Minimal inflammatory infiltrates that
contained a small number of lymphocytes and/or histiocytes existed in a
few cases and was also recorded.

Immunohistochemical staining with primary anti-CD31 antibody(Leica
Biosystems\selectlanguage{ngerman}®; dilution,1:100; product code: NCL-L-CK7-560), an
endothelial marker, was performed to evaluate microvessel density in
perinephric fat. The Leica BOND-Max® automated staining platform (Leica
Microsystems, Wetzlar, Germany) and Bond Polymer Refine Detection
Kit®(Leica Biosystems, Newcastle Ltd., Newcastle Upon Tyne, UK; cat. no:
DS9800) were used for this purpose. In each case, 3 fields with the
highest number of~microvessels were identified at low power. In these
areas mean capillary~density (ACD) at 400× magnification was determined
and expressed as the number of~CD31-positive capillaries per high power
field.

Specimens were qualified for histopathological examination in 55(88.7\%)
of the 62 cases; 7 samples were excluded from the study due to poor
sampling or technical problems.

\textbf{Statistical analysis}

Statistical analysis was performed using IBM SPSS Statistics for Windows
v.23® (IBM Corp., Armonk, N.Y., USA). Continuous variables are shown as
mean ± SD and median(range). One-way ANOVA was used to analyze
parametric variables, versus the Kruskal-Wallis test for non-parametric
quantitative variables. Comparison of categorical variables was
performed using the Chi-square test. Correlation between non-parametric
data was analyzed by Spearman' correlation analysis. The level of
statistical significance was set at p\textless{}0.05.

\textbf{Results}

Mean age of the patients was 51.3±12.7 years and the male to female
ratio was 34:28. Mean BMI was 28.6± 5.2; among the 62 patients, 23 were
overweight and 26 were obese. In total, 3/62 patients had diabetes
mellitus, 15/62 had hypertension, and 2/62 were smokers. Among the
patients, 90.3\%(n=56/62) were light workers. Among the 22 partial
nephrectomies, 17(77.3\%) were performed via an open approach and
5(22.7\%) were performed laparoscopically. All 40 donor nephrectomies
were performed laparoscopically, of which 36/40(90\%) were hand
assisted. Most of the nephrectomies were performed on the left
side(52/62). Mean tumor diameter was 35.8±16.7mm(n=22).

The distribution of cases according to dissection complexity was as
follows: easy: n=27(43.5\%); moderate: n=20(32.3\%); difficult:
n=15(24.2\%). Mean perirenal fat dissection time was 15.0±13.5 min. Mean
dissection time in the cases with easy, moderate, and difficult
dissection complexity was 5.6±2.9, 12.7±2.1, and 35.1±13.0min
respectively. Dissection complexity classification(as easy, moderate and
hard) was in correlation with the time required for the
dissection(p\textless{}0.05).

There wasn't a significant difference in perirenal fat dissection
complexity between the male and female patients(p=0.074). Similarly,
correlations between weight, height, and BMI were not significant.
Moreover, there wasn't a correlation between perirenal fat dissection
complexity, and surgical side, the presence of diabetes mellitus, the
presence of hypertension, smoking status, or occupational
status(p\textgreater{}0.05).

The was a significant difference in perirenal fat dissection complexity
between open and laparoscopic nephrectomies(p\textless{}0.05); most of
the difficult dissection complexity cases underwent open surgery.
Subcutaneous fat thickness measured intra-operatively did not differ
according to dissection complexity(p=0.87); however, intra-operative
measurement of perirenal fat thickness and dissection complexity were
significantly correlated, such that median perirenal fat thickness was
lowest in the cases with easy dissection complexity(median: 10,4-20)
group and highest in those with difficult dissection complexity(median:
17, 10--28, p\textless{}0.05).

Radiological findings showed that there was a significant relation
between perirenal fat depth and perirenal fat dissection complexity;
thewith a higher difference was greatest in the difficult dissection
complexity patients(p\textless{}0.05); however, HU for the perirenal
field and subcutaneous fat measured via CT showed that there wasn't a
significant difference according to dissection complexity(p=0.88 and
p=0.52, respectively). The radiologically measured perirenal fat depth
and intra-operative measurement of perirenal fat thickness were
significantly correlated (r=0.363, p=0.005).

Perinephric fat exhibited evidence of histological fibrosis more
commonly in the patients with severe APF(Table). All 4 parameters that
we explored for fibrosis were higher in the patients with difficult
dissection complexity. The median thickness of Gerota's fascia at its
thickest part was~251\selectlanguage{greek}µ\selectlanguage{english}m (range:80-716\selectlanguage{greek}µ\selectlanguage{english}m) in the patients with easy
dissection complexity, versus 196\selectlanguage{greek}µ\selectlanguage{english}m(range:67.6-652\selectlanguage{greek}µ\selectlanguage{english}m) and
384.5\selectlanguage{greek}µ\selectlanguage{english}m(range:151-910.4\selectlanguage{greek}µ\selectlanguage{english}m) in those with moderate and difficult
dissection complexity, respectively(p=0.006). In all, 8(34.8\%) of the
23 patients with easy dissection complexity, 5(29.4\%) of the 17 with
moderate dissection complexity, and 12(80\%) of the 15 with difficult
dissection complexity had perivascular fibrosis(p=0.007).~Intercellular
collagen accumulation was observed in~8.7\% (2/23) of the patients with
easy dissection complexity, 11.8\%(2/17) of those with moderate
dissection complexity, and 80\%(12/15) of those with difficult
dissection complexity(p=0.000).

Spicules or bands of collagen radiating from the outer fascia,
interlobular septae, and perivascular fibrous tissue were more common in
the patients with APF(22\%,~47\%, 87\% in the easy, moderate, and
difficult dissection complexity patients, respectively, p=0.000). There
weren't any significant differences in inflammation, or mean and maximum
adipocyte diameter according to perirenal fat dissection complexity.~Fat
tissue in the severe APF patients contained a higher number of blood
vessels with wall thickness \textgreater{}100\selectlanguage{greek}µ\selectlanguage{english}m(p=0.039).~There wasn't a
significant difference in small capillary density according to perirenal
fat dissection complexity(p\textgreater{}0.05).

\textbf{Discussion}

APF is a clinical phenomenon without a direct effect on patients, yet
for surgeons it complicates dissection and release of the
kidney\textsuperscript{7,8}. Dissection of perirenal fat is an important
component of partial nephrectomy and donor nephrectomy. APF can cause
excessive hemorrhaging during surgery, trauma to the renal capsule,
iatrogenic vascular injury, and prolongation of operative
time\textsuperscript{6,8,9}. Hemorrhaging from fatty tissue and vascular
injury can complicate endourological manipulations. During laparoscopic
and robot-assisted partial nephrectomy APF impedes kidney dissection.
Furthermore, prolonged surgery time and renal capsular trauma can
interfere with the renal transplantation process. Thusly, APF is a
challenging phenomenon, both for open and endoscopic procedures. In
addition to the radiological features, the present study focused on the
pathological aspects of APF.

In the most recent studies APF was qualified as present or absent; only
Narita et al. classified cases as non-APF, APF, and severe APF, as in
the present study\textsuperscript{10-12}. We acknowledge that APF
differs in severity from patient to patient. Dissection in some patients
is sometimes so difficult that decapsulation occurs multiple times and
occasionally complete removal of perirenal fat cannot be achieved;
however, in some cases with APF dissection is managed with only minimal
trauma and hemorrhaging. For the aforementioned reasons we find that it
is appropriate to characterize APF as easy, moderate, and difficult.

The correlation between perirenal fat dissection complexity and
dissection time in the present study confirms the pertinence of the
dissection classification used. Zheng et al. classified APF according to
dissection duration, as \textless{}10 min, 10-20 min, and
\textgreater{}20min\textsuperscript{13}. Their dissection time groupings
were comparable to those in the present study, in which mean dissection
time in the easy, moderate, difficult dissection complexity patients was
5.6\selectlanguage{ngerman}±2.9min, 12.7±2.1min, and 35.1±13.0min, respectively.

Retroperitoneal fat thickness is reported to affect duration of surgery,
as it did in the present study. In addition to male gender, Ito et al.
showed that retroperitoneal fat thickness is positively correlated with
surgical duration\textsuperscript{3}. In a prospective study of 100
robotic partial nephrectomies it was reported that surgery time in
patients with APF was longer than in those without
APF\textsuperscript{12}. A study that included 92 donor nephrectomies
observed that APF and severe APF significantly prolonged
surgery\textsuperscript{10}. In the present study dissection time was
significantly affected by APF; dissection time was longest in the
patients with difficult dissection complexity. Total duration of surgery
was not a focus of the present study because it can be deceptive. Total
surgery time in donors during the transplantation process is affected by
many factors; as such, we think that dissection time is a more reliable
measurement for assessment of APF.

For the prediction of APF the image-based Mayo Adhesive Probability(MAP)
score has been introduced\textsuperscript{4}. This 5-point scoring
system uses posterior perinephric fat thickness and perinephric fat
stranding. The utility of the MAP score has been verified by several
researchers\textsuperscript{7,14}. Furthermore, many studies show that
there is a clear association between APF and perirenal fat
thickness\textsuperscript{6,10,11}. Perirenal stranding observed in
radiological images is not always an indicator of APF and stranding is a
subjective parameter. To assess the clinical relevance of the perirenal
field's radiological features, the perirenal field's HU was measured in
the present study, and there wasn't a significant correlation between
the perirenal field's HU and APF, yet perirenal fat depth differed
significantly according to the complexity of perirenal fat dissection.
Based on the present findings, we think use of perirenal fat depth
measured via pre-operative CT is sufficient for presurgical prediction
of APF.

Obesity is thought to play a role in APF, yet there wasn't a significant
correlation between APF and BMI in the present study. Correspondingly, 2
other studies did not note an association between BMI and APF; however,
others have observed a marked association\textsuperscript{6,8,11,14,15}.
Some studies considered waist circumference a predictor of
APF\textsuperscript{6}. The present study analyzed subcutaneous fat
thickness as an indicator of internal fat burden, which is assumed to be
a more objective parameter than waist circumference, but there wasn't a
significant association between subcutaneous fat thickness and APF.

In addition to a high BMI, many other factors are associated with APF.
Khene et al. assessed APF in 202 patients that underwent robot-assisted
partial nephrectomy and reported that male gender, old age, a high BMI,
smoking, and hypertension are risk factors for APF\textsuperscript{8}.
Similarly, Kawamura et al. reported the same risk factors for
APF\textsuperscript{14}. Kocher et al. noted a significant association
between APF, and increased age and male gender\textsuperscript{11}. In
the present study there wasn't a correlation between APF and any of the
aforementioned factors. The donor population in the present study might
account for these differences, as the renal donors were for the most
part fit and healthy non-smokers.

Radiologically measured posterior fat thickness is a predictor of
APF\textsuperscript{10,11}. Additionally, a prospective study that
included 125 patients reported that lateral fat thickness was greater in
patients with APF\textsuperscript{6}. Moreover, increased posterior fat
thickness, visceral fat area, and perinephric fat area are reported to
be risk factors for APF\textsuperscript{10,15}. In the present study
perirenal fat thickness and perirenal fat depth measured via CT differed
significantly according to perirenal fat dissection complexity. In the
present study measurement of actual perirenal fat thickness was
performed in order to detect the thickest part of the fatty tissue and
perirenal fat depth was measured in order to use a more standardized
measure. HU measurements of the perirenal field and subcutaneous fat via
CT in the present study showed no significant difference according to
dissection complexity. Histopathological findings supported this
finding, no difference was observed in small capillary density according
to dissection complexity. Bylund et al. reported a similar finding;
however, Dariane et al. indicated the density of fat was an independent
predictor of APF\textsuperscript{6,15}.

Histopathlogical analysis in the present study show increased fibrous
tissue in the perirenal fat of APF patients, in contrast to the findings
reported by Dariane et al\textsuperscript{6}. This seems to be the major
underlying factor that can lead to surgical difficulty. Thicker Gerota's
fascia, and more collagen around blood vessels and in between fat cells
focally were observed in the present study's severe APF patients, but
what caused this variance is not clear. Metabolic disorders, such as
obesity and diabetes, and collagen vascular diseases or other systemic
problems might have led to an increase in collagen deposition in the
tissues; however, the present study's APF and non-APF patients did not
differ in these respects. Additionally, there wasn't a significant
difference in mean fat cell diameter, indicating that obese or
overweight patients have not accumulated on one arm of the study set.
Furthermore, we could not attribute to an inflammatory process for the
explanation of fibrosis as both groups of patients have only a very few
mononuclear cells over and there. In fact, we think that the amount of
fibrous tissue might have been innate and related to the individual's
features. The present finding that the APF patients had a higher number
of blood vessels with wall thickness \textgreater{}100\selectlanguage{greek}µ\selectlanguage{english}m might be
considered supportive of this hypothesis.

The primary limitation of the present prospective study is the small
number of patients. As living donor nephrectomy is performed less
frequently, the study also included partial nephrectomies. Pathological
examination might have been more objective if it had been conducted in
donors only.

\textbf{Conclusions}

APF is a challenge for kidney surgeons. Difficult perirenal fat
dissection prolongs surgical duration and can lead to complications.
Predicting APF pre-operatively helps in choosing which patients qualify
for minimally invasive surgery. Perirenal fat thickness measured via
pre-operative CT can predict APF. There is a positive correlation
between perirenal fat thickness and perirenal fat dissection complexity.

Acknowledgments: This study did not received any funding. Authors have
nothing to declare.

Disclosure of interest: The authors report no conflicts of interest.

\textbf{REFERENCES}

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5. Martin L, Rouviere O, Bezza R, et al. Mayo adhesive probability score
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6. Dariane C, Le Guilchet T, Hurel S, et al. Prospective assessment and
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7. Ishiyama R, Kondo T, Takagi T, et al. Impact of the Mayo adhesive
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Table. Analysis of histological findings.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Variables}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Easy Dissection Complexity Group} (n = 23)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Moderate Dissection Complexity Group} (n = 17)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Difficult Dissection Complexity Group} (n = 15)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
p value\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Presence of inflammation, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2 (8.7\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
3 (17.6\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
4 (26.7\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.344\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Presence of perivascular fibrosis, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
8 (34.8\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
5 (29.4\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
12 (80\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.007\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Capillary density (per unit area)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
20 (10-40)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
17 (12-33)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
15 (10-50)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.641\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Presence of brown fat, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
6 (26.1\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
6 (35.3\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1 (6.7\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.158\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
The average adipocyte diameter, ?m (range)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
101 (56.5-150)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
84.8 (62-153)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
109 (72-203)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.130\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Maximum adipocyte diameter, ?m (mean \selectlanguage{ngerman}± SD)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
146.4 \selectlanguage{ngerman}± 31.5\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
139.1 \selectlanguage{ngerman}± 30.2\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
154.7 \selectlanguage{ngerman}± 17.0\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.299\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Number of vessels with thick walls* (\textless{}3, 4-5, [?]6,)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textless{}3: 7/23 (30.4\%) 4-5: 15/23 (65.2\%) [?]6: 1/23 (4.3\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textless{}3: 0/17 (0\%) 4-5: 16/17 (94.1\%) [?]6: 1/17 (5.9\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\textless{}3: 1/15 (6.7\%) 4-5: 12/15 (80\%) [?]6: 2/15 (13.3\%)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.039\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Wall of the thickest vessel, \selectlanguage{greek}µ\selectlanguage{english}m (range)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
60 (22-862)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
51 (21.4-128)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
53 (24.3-149.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.913\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Exterior fascia thickness,** \selectlanguage{greek}µ\selectlanguage{english}m (range)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
251 (80-716)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
196 (67.6-652)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
384.5 (151-910.4)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.006\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Presence of intercellular collagen, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2 (8.7\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2 (11.8\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
12 (80\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.000\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Presence of spiculer fibrosis and/or bands of collagen, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
5 (22\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
8 (47\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
13 (87\%)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.000\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

*Thickness \textgreater{}100 \selectlanguage{greek}µ\selectlanguage{english}m. **Measurements at the thickest point.

\textbf{FIGURE LEGENDS}

Figure 1. Cases showing increased fibrous tissue in the septae
surrounding fat lobules (a), around the blood vessels (b) and in the
Gerota fascia (c). Spicular infiltration of collagen into the fat
lobules can be noted (a: Masson's trichrome stain x 200; b: Masson's
trichrome stain x 100; c: H-E stain x 100).

Figure 2. Intercellular collagen deposition was noted in some cases
expanding the distance between individual adipocytes (Left: H-E stain x
100; Right: Masson's trichrome stain x 400).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}

\selectlanguage{english}
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\end{document}

