Radiol Oncol 2024; 58(1): 23-32. doi: 10.2478/raon-2024-0014
23
research article 
Looking through the imaging perspective: 
the importance of imaging necrosis in glioma 
diagnosis and prognostic prediction − single 
centre experience
Hui Ma, Shanmei Zeng, Dingxiang Xie, Wenting Zeng, Yingqian Huang, Liwei Mazu, 
Nengjin Zhu, Zhiyun Yang, Jianping Chu, Jing Zhao
Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China
Radiol Oncol 2024; 58(1): 23-32.
Received 19 September 2023 
Accepted 01 December 2023
Correspondence to: Zhao Jing, Chu Jianping and Yang Zhiyun, Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 
No. 58 Zhongshan Er Road, Guangzhou, 510080, Guangdong Province, People’s Republic of China. E-mail: zhaoj23@mail.sysu.edu.cn
Ma Hui, Zeng Shanmei and Xie Dingxiang contributed equally.
Disclosure: No potential conflicts of interest were disclosed.
This is an open access article distributed under the terms of the CC-BY license (https://creativecommons.org/licenses/by/4.0/).
Background. The aim of the study was to investigate the diagnostic value of imaging necrosis (Imnecrosis) in grading, 
predict the genotype and prognosis of gliomas, and further assess tumor necrosis by dynamic contrast-enhanced MR 
perfusion imaging (DCE-MRI). 
Patients and methods. We retrospectively included 150 patients (104 males, mean age: 46 years old) pathologi-
cally proved as adult diffuse gliomas and all diagnosis was based on the 2021 WHO central nervous system (CNS) clas-
sification. The pathological necrosis (Panecrosis) and gene mutation information were collected. All patients underwent 
conventional and DCE-MRI examinations and had been followed until May 31, 2021. The Imnecrosis was determined by 
two experienced neuroradiologists. DCE-MRI derived metric maps have been post-processed, and the mean value 
of each metric in the tumor parenchyma, peritumoral and contralateral area were recorded. 
Results. There was a strong degree of inter-observer agreement in defining Imnecrosis (Kappa = 0.668, p < 0.001) and 
a strong degree of agreement between Imnecrosis and Panecrosis (Kappa = 0.767, p < 0.001). Compared to low-grade 
gliomas, high-grade gliomas had more Imnecrosis (85.37%, p < 0.001), and Imnecrosis significantly increased with the grade 
of gliomas increasing. And Imnecrosis was significantly more identified in IDH-wildtype, 1p19q-non-codeletion, and 
CDKN2A/B-homozygous-deletion gliomas. Using multivariate Cox regression analysis, Imnecrosis was an independent 
and unfavorable prognosis factor (Hazard Ratio = 2.113, p = 0.046) in gliomas. Additionally, extravascular extracellular 
volume fraction (ve) in tumor parenchyma derived from DCE-MRI demonstrated the highest diagnostic efficiency in 
identifying Panecrosis and Imnecrosis with high specificity (83.3% and 91.9%, respectively). 
Conclusions. Imnecrosis can provide supplementary evidence beyond Panecrosis in grading, predicting the genotype 
and prognosis of gliomas, and ve in tumor parenchyma can help to predict tumor necrosis with high specificity. 
Key words: glioma; necrosis; MRI; molecular markers; prognosis
Introduction
Necrosis is a common feature of human cancer and 
is often related to a poor prognosis, especially in 
glioblastomas.1-3 Though the importance of necro-
sis in gliomas has already been addressed, necro-
sis was first incorporated into the determinant of 
the diagnosis for glioma grade in the fifth edition 
of the 2021 WHO classification of Tumors of the 
central nervous system (CNS), which highlighted 
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction24
and underlined the significant value of necrosis in 
the diagnosis and prognosis of adult diffuse glio-
mas.4 According to the latest classification, once 
histological necrosis is identified, a diagnosis of 
WHO grade 4 astrocytoma or glioblastoma is sug-
gested. However, there is a diagnostic dilemma in 
grading gliomas by identifying necrosis.
Presently, necrosis is primarily determined by 
pathological examination, in which partial tumor 
specimens from specific sites of tumors obtained 
by surgery or biopsy at a single point in time are 
generally inspected.5 However, due to tumor het-
erogeneity and incompleteness of the pathological 
sample, some pathological necrosis is likely to be 
missed, which may result in an underestimation 
of tumor grades, especially when the molecular 
analysis is not available. As tumor grades influ-
ence therapeutic decisions and prognosis, it is im-
perative to make up for the problem of a missed 
diagnosis of necrosis on pathological evaluation. 
Magnetic resonance imaging (MRI) is utilized 
for routine, noninvasive, preoperative examina-
tion in diagnosing gliomas. Pathological necrosis 
usually has corresponding imaging features.6,7 
Imaging necrosis has been defined as a region 
within the tumor that does not enhance or shows 
markedly diminished enhancement, high signal 
intensity on T2WI, low signal intensity on T1WI, 
and an irregular border.6 Hence necrosis in glio-
mas, when substantially present, can be detected 
by conventional MRI and plays a vital role in di-
agnosing gliomas and predicting prognosis.6,8-13 
Moreover, conventional and advanced MRI can 
acquire comprehensive morphological and patho-
physiological images of entire tumors, which is im-
possible with pathological examinations. 
Taking all of this into account, we speculated 
whether necrosis diagnosed by MRI (hereaf-
ter termed “imaging necrosis”, abbreviated as 
Imnecrosis) could be used as a correction or a supple-
ment to necrosis diagnosed by pathological evalu-
ation (hereafter termed “pathological necrosis”, 
abbreviated as Panecrosis), especially when there is 
no evidence of Panecrosis owing to limited sampling 
sites and sampling amounts. Consequently, here-
in, we retrospectively reviewed MRI findings of 
adult diffuse gliomas that were diagnosed based 
on the 2021 WHO CNS classification and assessed 
the role of Imnecrosis in grading, predicting the geno-
type and prognosis of gliomas. We also attempted 
to analyse tumor necrosis by dynamic contrast-
enhanced MR perfusion imaging (DCE-MRI) to 
validate quantitative imaging markers for probing 
tumor necrosis. 
Patients and methods
Study participants
Patients with a primary diagnosis of glioma (June 
2013–May 2021) were retrospectively included. 
Inclusion and exclusion criteria are presented in 
Supplementary Figure 1. Clinical information of 
patients was retrieved from the electronic medical 
records, and follow-up information was obtained 
through clinical interviews. Follow-up survival 
data were available until May 31, 2021. Overall 
survival (OS) was calculated from the initial sur-
gery date to the date of death, or the date of the 
last follow-up visit if the patient was alive or lost 
to follow-up.
This retrospective analysis was in accordance 
with the ethical standards of the institutional and 
national research committee and was approved by 
the ethics committee of our institution ([2021]209). 
The requirement for written informed consent 
was waived due to the retrospective nature of this 
study. 
MRI parameters
Participants underwent conventional (T1/T2-
weighted images [T1WI/T2WI], T2-weighted fluid-
attenuated inversion recovery [T2WI-FLAIR] and 
sagittal view of contrast-enhanced three-dimen-
sional T1 MPRAGE images) and DCE-MRI imag-
ing using a 3.0T MR system (Magnetom Verio, 
Siemens Medical Solutions, Erlangen, Germany) 
with a 64-channel head-neck coil. The parameter 
details of the conventional MRI and the DCE-MRI 
were elaborated in Supplementary Appendix 1.
Image processing
All DCE-MRI data were transferred to the post-
processing workstation (detailed in Supplementary 
Appendix 2). Pharmacokinetic parameters, includ-
ing the transfer constant (ktrans), extravascular 
extracellular volume fraction (ve), rate constant 
(kep = ktrans/ve), and initial area under the curve 
in the first 60 s (iauc), were automatically generat-
ed. Regions of interest (ROIs) were selected across 
three consecutive maximum tumor parenchyma 
slices. At each slice, one ROI was put in tumor 
parenchyma (hereafter termed “tumor”), accord-
ing to T2WI-FLAIR, and enhanced T1WI, avoiding 
necrosis, cystic, and vessel areas. Another two ap-
proximate 2-mm-diameter ROIs were put in tumor 
peripheral zones (hereafter termed “edema”, with-
in a 1-cm distance from the outer enhancing tumor 
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction 25
margin) and contralateral normal-appearing brain 
tissues (hereafter termed “control”) (Figure 1). The 
mean values of each DCE-MRI metric was record-
ed. 
As mentioned in the introduction, examples 
of imaging necrosis, defined as a region within 
the tumor that does not enhance or shows mark-
edly diminished enhancement, high signal inten-
sity on T2WI, low signal intensity on T1WI, and 
an irregular border, are shown in Figure 2 and 
Supplementary Figure 2. Two experienced radiolo-
gists reviewed all conventional MRIs. Then they 
determined whether there was Imnecrosis by consen-
sus. One of these two experienced radiologists and 
a third radiologist repeatedly assessed 68 cases 
after the initial assessment to assess the inter-ob-
server agreement. The assessed images were ran-
domized within each type of pathology, and the 
observers were blinded to the clinical and patho-
logical information and thoroughly acquainted 
with the criteria. 
Pathological and molecular analysis
Panecrosis was defined according to pathological re-
ports provided by the Pathology department of our 
hospital, if available. The status of 1p19q codele-
tion, EGFR amplification, chr7 gain/10 loss (+7/-10), 
and CDKN2A/B homozygous deletion were deter-
mined by fluorescence in situ hybridization with a 
specific probe. IDH mutation was determined by 
high-throughput sequencing, including IDH1 and 
IDH2 mutations. The pathological diagnosis and 
grading of gliomas were reassigned according to 
the 2021 WHO CNS classification (Supplementary 
Figure 3).4,14,15 
Statistical analysis
Statistical Analysis Data were analyzed using IBM 
SPSS Statistics 26 software, the SPSSAU data sci-
entific analysis platform (https://spssau.com/), and 
the R programming language (version 4.1.2, The R 
Foundation for Statistical Computing). Normally 
distributed continuous variables were compared 
using unpaired t-tests, whereas non-parametric 
tests were used for non-normally distributed vari-
ables. Descriptive data are expressed as mean ± SD, 
except where otherwise stated. Unpaired t-tests, 
non-parametric tests, and chi-squared tests were 
used to compare differences between parameters. 
Receiver Operating Characteristics (ROC) curves 
FIGURE 1. Representative ROI delineations. A 53-year-old man was diagnosed with glioblastoma, IDH-wildtype. (A) contrast-
enhanced T1-weighted image (T1WI-CE); (B) the time-signal intensity curve; (C) the transfer constant (ktrans) image; (D) rate 
constant (kep) image; (E) extravascular extracellular volume fraction (ve) image; (F) initial area under the curve in the first 60 
s (iauc) image. On images, B-F, ROI 1 marked green represented tumor parenchyma, ROI 2 marked yellow represented the 
peripheral zones, and ROI 3 marked blue-turquoise represented contralateral normal-appearing brain tissues.
A B
C D E F
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction26
were used to evaluate diagnostic efficacy. Simple 
kappa was calculated to assess the consistency of 
different diagnoses and inter-observer agreement. 
Kaplan–Meier survival analysis was used to ana-
lyze survival data. Hazard ratios (HR) were esti-
mated according to the Cox proportional hazard 
method. A two-sided p value < 0.05 was considered 
significant. Detailed statistical methods are shown 
in Supplementary Appendix 3. 
Results 
Patients’ demographic and clinical 
findings
We initially identified 150 eligible patients (median 
age = 46 years, range 21–79 years), and 104 (69.33%) 
were male (Table 1). All the diagnoses assigned to 
the patients according to the latest integrated his-
to-molecular classification criterion were present-
ed in Supplementary Figure 3 and Supplementary 
Table 1. Panecrosis was identified in 70/76 of high-
grade gliomas (HGGs, CNS WHO grade 4) and 
3/43 of low-grade gliomas (LGGs, CNS WHO grade 
2 and 3) which were oligodendrogliomas, IDH-
mutant and 1p/19q-deleted, while Imnecrosis was 
identified in 70/76 of HGGs and 12/43 of LGGs. 
There was 1/77 HGG without enhancement 
but with positive status of EGFR amplification, 
thus diagnosed as glioblastomas, IDH-wildtype, 
while there were 32/45 LGGs with enhancement 
diagnosed as oligodendrogliomas, IDH-mutant 
and 1p/19q-deleted (n = 15) and astrocytoma, 
IDH-mutant (n = 17). And most HGGs were mani-
fested as ring enhancement, and most LGGs had 
patchy and punctate enhancement. All the clini-
cal information was presented in Table 1 and 
Supplementary Appendix 4. 
Interobserver agreement of imaging 
necrosis and correlation between 
imaging and pathological necrosis
In this study, the following four groups were de-
termined: Im+Panecrosis group (representing patients 
with both Imnecrosis and Panecrosis, n = 74), nonecrosis 
group (representing patients without Imnecrosis nor 
Panecrosis, n = 28), Only Imnecrosis group (represent-
ing patients with Imnecrosis but without Panecrosis, n = 
7), and Only Panecrosis group (representing patients 
with Panecrosis but without Imnecrosis, n = 4) groups. 
Detailed clinical, imaging and paychological in-
formation of Only Imnecrosis group and Only Panecrosis 
group were shown in Table 2. We found strong 
agreement between Imnecrosis and Panecrosis (Kappa = 
0.767, p < 0.001, 95%CI: 0.637–0.897). 
Besides, there was strong inter-observer agree-
ment in identifying imaging necrosis (Kappa = 
0.668, p < 0.001, 95%CI: 0.489–0.846). And the spot-
like, dotted, long-strip, long tubular, and fissural 
enhancements (Figure 3) which were easily mis-
diagnosed as imaging necrosis should be avoided. 
Association of imging necrosis with 
integrated glioma grading 
Most HGGs (85.37%) were found to have Imnecrosis, 
while most LGGs (83.78%) were without Imnecrosis. 
There were 4/30 WHO grade 2 patients with 
Imnecrosis. Of those, two were diagnosed as oligo-
dendrogliomas, IDH-mutant and 1p/19q-deleted, 
and two as astrocytomas, IDH-mutant.
Significant differences in the presence of Imnecrosis 
with a large effect size were found between HGGs 
and LGGs and among different grades of glio-
mas (Table 1, p < 0.001). Cochran–Armitage tests 
showed an upward trend in Imnecrosis from lower 
to higher grades of gliomas (p < 0.001). Multiple 
comparisons with Bonferroni correction showed 
that the difference between WHO grades (any two 
grades) and Imnecrosis was significant (all p < 0.01). 
Association of imaging necrosis and 
molecular profiles of gliomas
There were significant correlations between the 
expression of other molecular markers such as 
IDH, 1p19q, and CDKN2A/B and the presence of 
Imnecrosis. According to Table 1, the proportion of 
IDH-wildtype, 1p19q-non-codeletion, or CDKN2A/
B-positive cases with Imnecrosis was significantly 
higher than that of cases without Imnecrosis with 
a medium effect size, respectively (75.82% vs. 
A B C
FIGURE 2. Representative MR images with imaging necrosis derived from a 
53-year-old man with glioblastoma, IDH-wildtype. Shown from left to right by the 
order are T1WI (A), T2WI (B), and T1WI-CE (C).
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction 27
32.08%, 85.94% vs. 51.11%, 20% vs. 0, respectively). 
However, no significant correlation was found be-
tween Imnecrosis and EGFR amplification or +7/-10 
cytogenetic signature (p > 0.05) (Table 1). 
Association of imaging necrosis with 
patient prognosis
One-hundred and thirty patients were included 
in the final survival analysis. Compared with 
gliomas with Imnecrosis, patients without Imnecrosis 
had a significantly longer survival time (p < 
0.001, Figure 4A). By reference to the gliomas 
with Panecrosis, patients without Panecrosis had a sig-
nificantly longer survival time as well (p < 0.001, 
Figure 4B).
The differences among the OS of Im+Panecrosis, 
nonecrosis, Only Imnecrosis, and Only Panecrosis groups 
were statistically significant (p < 0.01, Figure 4C). 
Further, after Bonferroni correction, there were 
significant differences between Im+Panecrosis and 
nonecrosis groups (p < 0.001). According to Figure 4C, 
the OS of the Only Panecrosis group (n = 2) was short-
er than the OS of nonecrosis group (n = 28) and Only 
Imnecrosis group (n = 7). Between the two survival 
curves of nonecrosis and the Only Imnecrosis groups, 
there were marked crossovers, but within a cer-
tain period (time spanning about from 5-month 
TABLE 1. Participant demographic findings
Parameters Type
Imaging necrosis
Sum t/χ2b pNegative
n (%)
Positive
n (%)
Age (n = 150) - 40.54±11.08(n = 54)
50.39±12.47
(n = 96) - -4.829& p < 0.001
Sex (n = 150)
male 36(66.67) 68(70.83) 104
0.282 0.595
female 18(33.33) 28(29.17) 46
IDH (n = 144)
wildtype 17(32.08) 69(75.82) 86
26.649 p < 0.001
mutant 36(67.92) 22(24.18) 58
1p19q (n = 109)
non-codeletion 23(51.11) 55(85.94) 78
15.746 p < 0.001
codeletion 22(48.89) 9(14.06) 31
CDKN2A/B homozygous deletion  
(n = 63)
non-deletion 38(100.00) 20(80.00) 58
5.745b 0.017*
deletion 0(0.00) 5(20.00) 5
EGFR amplification 
(n = 81)
non-amplification 8(66.67) 45(65.22) 53
0.054a 0.817
amplification 4(33.33) 24(34.78) 28
chr7 gain/10 loss (n = 26)
negative 10(83.33) 13(92.86) 23
0.552b 0.457
positive 2(16.67) 1(7.14) 3
Grade (n = 119)
high-grade 6(16.22) 70(85.37) 76
52.828 p < 0.001
low-grade 31(83.78) 12(14.63) 43
WHO grade (n = 119)
WHO grade 2 26(70.27) 4(4.88) 30
62.664a p < 0.001WHO grade 3 5(13.51) 8(9.76) 13
WHO grade 4 6(16.22) 70(85.37) 76
Integrated histo-molecular diagnoses 
(n = 116)
Oligodendroglioma, 
IDH-mutant and 
1p/19q-deleted
17(45.95) 7(8.86) 24
41.238 p < 0.001Astrocytoma,
IDH-mutant 15(40.54) 12(15.19) 27
Glioblastoma,
IDH-wildtype 5(13.51) 60(75.95) 65
& = Student’s t statistic in this cell, and other cells in the same column represent Chi-square values. a and b = chi-square tests with continuity correction and Fisher’s exact 
tests, respectively; * = p < 0.05
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction28
to 40-month postoperatively), the OS of the Only 
Imnecrosis group was shorter than the OS of nonecrosis 
group. 
Further, when added significant variables such 
as age, IDH, 1p19q, and Imnecrosis into the multivari-
ate Cox proportional hazards regression analyses, 
only Imnecrosis (HR = 2.113, 95% CI: 1.015–4.402, p 
= 0.046) was significant and independently related 
to the patients’outcome, indicating that Imnecrosis is 
an independent and unfavourable prognostic fac-
tor.
Correlation of tumor necrosis and DCE-
MRI metrics 
Since pathology is the golden standard for necro-
sis diagnosis, we analyzed the associations with 
Panecrosis and DCE-MRI metrics. Most DCE-MRI 
metrics demonstrated a significant difference 
in identifying gliomas with Panecrosis with a very 
large effect size (Table 3). Kep was significantly 
higher for gliomas with Panecrosis than those with-
out Panecrosis, while other DCE-MRI metrics showed 
the opposite trend. ROCs analysis showed that 
the Tumor-ve-Mean displayed the best diagnostic 
performance with the largest AUC of 0.891 (95%CI: 
0.788–0.995, p < 0.0001), and the optimal cut-off 
point was 0.17 with a sensitivity of 96% and speci-
ficity of 83.3%. 
Similarly, we performed the analysis regard-
ing Imnecrosis (Table 3), and the Tumor-ve-Mean dis-
played the best diagnostic performance as well, 
with the most significant AUC of 0.929 (95%CI: 
0.872–0.986, p < 0.0001) and the optimal cut-off 
point was 0.17 with a sensitivity of 89.2% and spec-
ificity of 91.9%. 
Discussion
In this study, we investigated the clinical impli-
cation of imaging necrosis in the preoperative 
evaluation of glioma. We found strong agreement 
between Imnecrosis and Panecrosis. Moreover, Imnecrosis 
was found to be significantly related to glioma-
related key gene mutations, such as 1p19q non-
codeletion and CDKN2A/B homozygous deletion. 
And it is an independent imaging marker for pre-
dicting tumor prognosis. Additionally, tumor pa-
renchyma ve derived from DCE-MRI can help to 
predict tumor necrosis with high specificity.
Our study indicated strong agreement between 
the inter-observer agreement of Imnecrosis and 
Panecrosis. And during the analysis, we found that 
A
B
C
D
E
FIGURE 3. Some representative MRI images without imaging necrosis which 
was exactly confused in diagnosing imaging necrosis. Shown from left to 
right by the order are T1WI, T2WI, and T1WI-CE. (A) a 24-year-old man with an 
oligodendroglioma, IDH-mutant and 1p/19q-deleted, CNS WHO grade 2; (B) a 
39-year-old man with an oligodendroglioma, IDH-mutant and 1p/19q-deleted, 
CNS WHO grade 2; (C) a 55-year-old woman with an oligodendroglioma, IDH-
mutant and 1p/19q-deleted, CNS WHO grade 2; (D) a 45-year-old man with an 
astrocytoma, CNS IDH-mutant, WHO grade 2; (E) a 36-year-old woman with an 
oligodendroglioma, IDH-mutant and 1p/19q-deleted, CNS WHO grade 2. In this 
case (E), it showed multiple long tubular and filiform enhancement and there 
were some tumor areas with remarked decrease of reinforcement. But these 
areas are hyperintense, not hypointense, on the T1-weighted image. Comparing 
with CT images (not provided), calcification on these areas were just observed. 
So, there was no imaging necrosis in these conditions.
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction 29
the regions with an absence or marked decrease 
of enhancement inside the intensified areas were 
easily mistaken as Imnecrosis. While considering 
pathological samples were partial, imaging obser-
vation can capture full tumors. There was a patho-
logically proven astrocytoma, IDH-mutant, CNS 
WHO grade 2, with a very short OS (5 months). We 
reviewed the raw data and identified that this pa-
tient had a small extent of Imnecrosis, indicating high 
grade gliomas. The situation mentioned above 
can be avoided if a judgement of Imnecrosis is made, 
which is one unique advantage of radiographic ex-
amination. Besides, we identified seven patients 
with Imnecrosis who were diagnosed as oligoden-
drogliomas, IDH-mutant and 1p/19q-deleted, CNS 
WHO grade 2 or 3, indicating that necrosis plays 
a limited predictive value in oligodendrogliomas. 
Hence, if there is evidence of oligodendrogliomas, 
such as calcification and filiform or localized inter-
nal homogeneous enhancement, Imnecrosis does not 
indicate a high-grade tumor. Besides, Waqar et al. 
reported this kind of reinforcement as a “chicken 
wire” appearance with the explanation that oligo-
dendroglioma vasculature often was described as 
a network of regular fine branching capillaries.16,17
Previous studies have highlighted that Imnecrosis 
is an independent unfavorable prognosis fac-
tor.5,6,10,18-20 Our results were in accordance with 
their findings. Besides, the latest WHO CNS classi-
fication emphasizes the role of molecular markers, 
such as IDH, 1p19q, CDKN2A/B, 7+/10-, and EGFR, 
in the diagnosis and prediction of the prognosis 
of gliomas.4 From this prospect, Imnecrosis might be 
more critical than Panecrosis since it can be non-inva-
sively obtained before operation. However, there 
was no significant difference between the expres-
sions of 7+/10- cytogenetic signature or EGFR am-
plification and the presence of Imnecrosis. This nega-
tive result might be due to the small sample size 
and insufficient number of events. 
In this study, we also sought quantitative met-
rics for indicating tumor necrosis. Our results 
revealed that, compared with tumor without 
Imnecrosis/Panecrosis, DCE-derived metrics in tumor 
TABLE 2. Detailed clinical, imaging and pathological information of Only Imnecrosis group and Only Panecrosis group
Group Grade Sex Age OS (month)
IDH (0:wild; 
1:mutant)
1p19q (0:non-
codeletion; 
1:codeletion)
CDKN2A/B 
(0:non-
deletion; 
1:deletion)
EGFR amplification 
(0:non-
amplification; 
1:amplification)
chr7 gain/10 
loss(0:negative; 
1:positive)
Pathology
Only 
Panecrosis 
group
WHO 
CNS 
grade 4
female 63 2.5 1 0 0 NA NA Astrocytoma,IDH-mutant
Only 
Panecrosis 
group
CNS 
WHO 
grade 4
female 55 20 0 0 NA 0 NA Glioblastoma,IDH-wildtype
Only 
Panecrosis 
group
CNS 
WHO 
grade 2
female 36 NA 1 1 0 NA NA
Oligodendroglioma, 
IDH-mutant and 
1p/19q-deleted
Only 
Panecrosis 
group
NA female 34 NA 1 NA NA NA NA IDH-mutation, NOS
Only Imnecrosis 
group
CNS 
WHO 
grade 4
male 64 5 0 0 NA 1 NA Glioblastoma,IDH-wildtype
Only Imnecrosis 
group
CNS 
WHO 
grade 2
male 40 25 1 0 0 NA NA Astrocytoma,IDH-mutant
Only Imnecrosis 
group
CNS 
WHO 
grade 3
female 55 60.06 1 1 0 NA NA
Oligodendroglioma, 
IDH-mutant and 
1p/19q-deleted
Only Imnecrosis 
group
CNS 
WHO 
grade 2
male 26 5.39 1 0 0 0 0 Astrocytoma,IDH-mutant
Only Imnecrosis 
group NQ male 40 7.19 0 0 NA 0 NA IDH-wildtype, NOS
Only Imnecrosis 
group NA male 28 19.68 0 0 NA 0 0 IDH-wildtype, NOS
Only Imnecrosis 
group
CNS 
WHO 
grade 3
male 26 34.42 1 0 0 NA NA Astrocytoma,IDH-mutant
CNS = central nervous system; NA = not available; NOS = not otherwise specified
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction30
parenchyma, except kep, were significantly higher 
in gliomas with Imnecrosis/Panecrosis. And ve in tumor 
parenchyma demonstrated the highest diagnos-
tic efficiency in identifying tumor necrosis with 
high sensitivity and specificity. Significantly high 
DCE-MRI metrics may be attributed to gliomas 
growing uncontrollably fast, resulting in severe 
hypoxia and necrosis. Thus, an extensively hyper-
permeable vasculature is generated, resulting in 
inadequate oxygen and supplements delivery. The 
FIGURE 4. Survival curves for cases of imaging necrosis (A), cases of pathological necrosis (B), and cases of both pathological and imaging necrosis (C).
A B
C
TABLE 3. Representative results of non-parametric tests and ROC analyses between DCE-related data for gliomas with or without pathological 
necrosis/imaging necrosis 
Parameter p AUC (95% CI) Sensitivity Specificity Cut-off
Panecrosis
Tumor-ktrans-Mean < 0.001 0.824 (0.711 ~0.936) 0.94 0.625 0.07
Edema-ktrans-Mean 0.031* 0.655 (0.527 ~ 0.783) 0.833 0.46 0.03
Tumor-ve-Mean < 0.001 0.891 (0.788 ~ 0.995) 0.96 0.833 0.17
Edema-ve-Mean 0.002** 0.728 (0.613 ~ 0.842) 0.34 1 0.16
Tumor-kep-Mean < 0.001 0.872 (0.761 ~ 0.983) 0.833 0.86 2.48
Tumor-iauc-Mean < 0.001 0.899 (0.803 ~ 0.996) 1 0.75 0.07
Imnecrosis
Tumor-ktrans-Mean < 0.001 0.856 (0.772 ~ 0.939) 0.877 0.757 0.08
Tumor-ve-Mean < 0.001 0.929 (0.872 ~ 0.986) 0.892 0.919 0.17
Edema-ve-Mean 0.005** 0.667 (0.558 ~ 0.776) 0.708 0.595 0.06
Tumor-kep-Mean < 0.001 0.914 (0.857 ~ 0.971) 0.946 0.831 2.74
Tumor-iauc-Mean < 0.001 0.909 (0.844 ~ 0.974) 0.8 0.946 0.13
* = p < 0.05; ** = p < 0.01
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction 31
greater the levels of perfusion and permeability in 
the tumor tissue, the higher the ktrans and ve and 
the higher the degree of tumor malignancy.21-23 
Hence, DCE-MRI metrics, especially ve in tumor 
parenchyma (cut-off value: 0.17), might be a sup-
plementary metric to the morphological observa-
tion for delineating tumor necrosis. 
The current study has some limitations. First, 
since evidence of pathological necrosis was ob-
tained from pathology reports of the same hos-
pital, there may be an observation bias. However, 
this study, based on clinical real-world evidence, 
can exactly address the current clinical deficits. 
Second, this is a single-center study; subgroups 
analysis had a small sample, which might result 
in insufficient power to reach definite conclusions. 
Further multicenter studies with large sample siz-
es will help improve the efficacy of Imnecrosis in pre-
dicting the expression of molecular markers and 
prognosis.
Conclusions
Based on the latest WHO CNS guidelines, the 
present study depicted the importance of imag-
ing necrosis in diagnosing gliomas. Detection of 
imaging necrosis in gliomas probably suggests an 
HGG unless there is imaging evidence for oligo-
dendrogliomas, IDH-mutant and 1p/19q-deleted. 
Imaging necrosis was significantly associated 
with glioma-related key gene mutations, such as 
1p19q non-codeletion and CDKN2A/B homozygous 
deletion. And it is an independent imaging marker 
for predicting tumor prognosis. Additionally, the 
Tumor-ve-Mean derived from DCE-MRI can help 
to predict necrosis with high sensitivity and speci-
ficity. Overall, in this study, we re-evaluated the 
imaging necrosis in the assessment of gliomas and 
provided a feasible solution to solve the frequent 
diagnostic dilemma of gliomas. 
Acknowledgments 
This study was funded in part by the National 
Natural Science Foundation of China (grant num-
bers 82172015, 82202217), the Natural Science 
Foundation of Guangdong Province (grant num-
bers 2021A1515012279, 2022A1515011264), and the 
Science and Technology Program of Guangzhou, 
China (grant number 202201011244).
References
1. Yee PP, Wei Y, Kim SY, Lu T, Chih SY, Lawson C, et al. Neutrophil-induced 
ferroptosis promotes tumor necrosis in glioblastoma progression. Nat 
Commun 2020; 11: 5424. doi: 10.1038/s41467-020-19193-y
2. Hou J, Zhao R, Xia W, Chang CW, You Y, Hsu JM, et al. PD-L1-mediated 
gasdermin C expression switches apoptosis to pyroptosis in cancer cells and 
facilitates tumour necrosis. Nat Cell Biol 2020; 22: 1264-75. doi: 10.1038/
s41556-020-0575-z
3. Jiao D, Cai Z, Choksi S, Ma D, Choe M, Kwon HJ, et al. Necroptosis of tumor 
cells leads to tumor necrosis and promotes tumor metastasis. Cell Res 2018; 
28: 868-70. doi: 10.1038/s41422-018-0058-y
4. Wen PY, Packer RJ. The 2021 WHO classification of tumors of the central 
nervous system: clinical implications. Neuro Oncol 2021; 23: 1215-7. doi: 
10.1093/neuonc/noab120
5. Shao Y, Xiong S, Sun G, Dou W, Hu X, Yang W, et al. Prognostic analysis of 
postoperative clinically nonmetastatic renal cell carcinoma. Cancer Med 
2020; 9: 959-70. doi: 10.1002/cam4.2775
6. Wu CX, Lin GS, Lin ZX, Zhang JD, Chen L, Liu SY, et al. Peritumoral edema on 
magnetic resonance imaging predicts a poor clinical outcome in malignant 
glioma. Oncol Lett 2015; 10: 2769-76. doi: 10.3892/ol.2015.3639
7. Seidel C, Dörner N, Osswald M, Wick A, Platten M, Bendszus M, et al. 
Does age matter? - a MRI study on peritumoral edema in newly diagnosed 
primary glioblastoma. BMC Cancer 2011; 11: 127. doi: 10.1186/1471-2407-
11-127
8. Pierallini A, Bonamini M, Pantano P, Palmeggiani F, Raguso M, Osti MF, et 
al. Radiological assessment of necrosis in glioblastoma: variability and prog-
nostic value. Neuroradiology 1998; 40: 150-3. doi: 10.1007/s002340050556
9. Yee PP, Wang J, Chih SY, Aregawi DG, Glantz MJ, Zacharia BE, et al. 
Temporal radiographic and histological study of necrosis development in a 
mouse glioblastoma model. Front Oncol 2022; 12: 993649. doi: 10.3389/
fonc.2022.993649
10. Hammoud MA, Sawaya R, Shi W, Thall PF, Leeds NE. Prognostic significance 
of preoperative MRI scans in glioblastoma multiforme. J Neurooncol 1996; 
27: 65-73. doi: 10.1007/BF00146086
11. Nowosielski M, Gorlia T, Bromberg JEC, Sahm F, Harting I, Kickingereder P, 
et al. Imaging necrosis during treatment is associated with worse survival 
in EORTC 26101 study. Neurology 2019; 92: e2754-63-e63. doi: 10.1212/
WNL.0000000000007643
12. Pope WB, Sayre J, Perlina A, Villablanca JP, Mischel PS, Cloughesy T. MR 
imaging correlates of survival in patients with high-grade gliomas. AJNR Am 
J Neuroradiol 2005; 26: 2466-74. PMID: 16286386
13. Liu S, Wang Y, Xu K, Wang Z, Fan X, Zhang C, et al. Relationship between 
necrotic patterns in glioblastoma and patient survival: fractal dimension 
and lacunarity analyses using magnetic resonance imaging. Sci Rep 2017; 7: 
8302. doi: 10.1038/s41598-017-08862-6
14. Weller M, van den Bent M, Preusser M, Le Rhun E, Tonn JC, Minniti G, et 
al. Author Correction: EANO guidelines on the diagnosis and treatment 
of diffuse gliomas of adulthood. Nat Rev Clin Oncol 2022; 19: 357-8. doi: 
10.1038/s41571-022-00623-3
15. Weller M, van den Bent M, Preusser M, Le Rhun E, Tonn JC, Minniti G, 
et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas 
of adulthood. Nat Rev Clin Oncol 2021; 18: 170-86. doi: 10.1038/s41571-
020-00447-z
16. Waqar M, Lewis D, Agushi E, Gittins M, Jackson A, Coope D. Cerebral and 
tumoral blood flow in adult gliomas: a systematic review of results from 
magnetic resonance imaging. Br J Radiol 2021; 94: 20201450. doi: 10.1259/
bjr.20201450
17. Cha S, Tihan T, Crawford F, Fischbein NJ, Chang S, Bollen A, et al. 
Differentiation of low-grade oligodendrogliomas from low-grade astrocy-
tomas by using quantitative blood-volume measurements derived from dy-
namic susceptibility contrast-enhanced MR imaging. AJNR Am J Neuroradiol 
2005; 26: 266-73. PMID: 15709123
18. Hong EK, Choi SH, Shin DJ, Jo SW, Yoo RE, Kang KM, et al. Comparison of 
genetic profiles and prognosis of high-grade gliomas using quantitative and 
qualitative MRI features: a focus on G3 gliomas. Korean J Radiol 2021; 22: 
233-42. doi: 10.3348/kjr.2020.0011
Radiol Oncol 2024; 58(1): 23-32.
Ma H et al. / the importance of imaging necrosis in glioma diagnosis and prognostic prediction32
19. Shen G, Wang R, Gao B, Zhang Z, Wu G, Pope W. The MRI features and 
prognosis of gliomas associated with IDH1 mutation: a single center study in 
southwest China. Front Oncol 2020; 10: 852. doi: 10.3389/fonc.2020.00852
20. Li Y, Qin Q, Zhang Y, Cao Y. Noninvasive determination of the IDH status 
of gliomas using MRI and MRI-based Radiomics: impact on diagnosis and 
prognosis. Curr Oncol 2022; 29: 6893-907. doi: 10.3390/curroncol29100542
21. Cosma I, Tennstedt-Schenk C, Winzler S, Psychogios MN, Pfeil A, 
Teichgraeber, et al. The role of gadolinium in magnetic resonance imaging 
for early prostate cancer diagnosis: a diagnostic accuracy study. PLOS ONE 
2019; 14: e0227031
22. ncoronato M, Grimaldi AM, Mirabelli P, Cavaliere C, Parente CA, Franzese 
M, et al. Circulating miRNAs in untreated breast cancer: an exploratory mul-
timodality morpho-functional study. Cancers 2019; 11: 876. doi: 10.3390/
cancers11060876
23. Tao WJ, Zhang HX, Zhang LM, Gao F, Huang W, Liu Y, et al. Combined applica-
tion of pharamcokinetic DCE-MRI and IVIM-DWI could improve detection 
efficiency in early diagnosis of ductal carcinoma in situ. J Appl Clin Med Phys 
2019; 20: 142-50. doi: 10.1002/acm2.12624.