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Prostate cancer (PCa) is one of the most common malignancies in male and the second leading cause of cancer-related death in adult men worldwide; in China, PCa ranks ninth in the incidence of male malignancies (1). According to CA-A CANCER JOURNAL FOR CLINICIANS ‘s forecast, there will be 288,300 new cases of PCa in the United States in 2023, and 34,700 patients will die of prostate cancer2200 (2). Nearly 30% of new cancer cases are PCa. More importantly, despite the continuous progress of prostate diagnostic technology, the incidence of PCa in China is increasing yearly, and the proportion of advanced prostate cancer is significantly higher than that in other countries. This may be due to the limitations of screening and the high rate of missed diagnosis. Many patients are elderly, and because of the subtle nature of PCa symptoms, they are diagnosed for the first time because of frequent urination and other lower urinary tract symptoms (LUTS). Therefore, the accurate screening of PCa in patients with benign prostatic hyperplasia is the most important method to improve the detection rate of PCa.

To date, the diagnosis of PCa mainly depends on two methods: the measurement of serum total prostate-specific antigen (TPSA) levels and multiparametric magnetic resonance imaging (mpMRI). In recent years, noninvasive methods, such as PSA measurements, have been developed for evaluating preoperative PCa lesions, and the diagnostic value of these methods for determining progression and prognosis has been evaluated. Although TPSA assays have high sensitivity, their low specificity has led to the overuse of prostate biopsy. Therefore, improving the efficiency of PCa diagnosis and avoiding unnecessary invasive examinations are pivotal components of the diagnosis and treatment of PCa. mpMRI of the prostate is currently another important component of noninvasive PCa diagnosis. mpMRI is not burdened by the economic costs associated with the surgical injury caused by prostate biopsy or false-positive results and can be comprehensively performed before surgery to assess the location, boundaries, and environment of the tumor. The apparent diffusion coefficient (ADC) value has also been discussed with regard to its relation to the pathological stage and prognosis of PCa (3). PI-RADS is currently one of the most widely used scoring criteria for PCa. It is used to evaluate the likelihood of focal prostate nodules to be PCa by scoring T2 and diffusion-weighted imaging (DWI) sequences. According to the difference in high and low signals and clarity, the PI-RADS divides the prostate score into five grades, of which the third grade represents possible PCa. Although patients with third grade tumors exhibit clear qualitative criteria, there are subjective differences to a certain extent, the requirements for the center are higher, and different radiologists may have different opinions. Moreover, some PCa lesions with 2- or 4-point characteristics are often included in the 3-point category, in which there are a large number of incorrect scores. In addition, there is still a debate about whether lesions with PI-RADS3 scores need invasive puncture. According to studies, the positive rate of PCa puncture with PI-RADS3 patients is only 20%, which greatly affects the detection of PCa. Previous studies have assessed the prevalence of PCa in PI-RADS3 lesions and found that PI-RADS scores do not provide accurate guidance for clinical management (with or without biopsies), and the rate of missed diagnosis is the main problem at present. For patients with PI-RADS3, the ambiguous PI-RADS score does not represent a better prognosis than the higher PI-RADS grade. Although the ADC value can help to judge the malignancy of malignant prostate tumors to some extent, it has obvious limitations. Some PI-RADS3 patients often have a very poor International Society of Urology Pathology (ISUP) grade, which seriously affects their survival and prognosis. Therefore, the two existing noninvasive examination items cannot provide effective guidance on the PI-RADS score, and the diagnosis of PI-RADS3 score of PCa is still in the exploratory stage (4–6). So far, many tools, such as biomarkers, associated with mpMRI have aimed to solved this particular problem, such as SelectMDx (7), 4Kscore, ExosomeDx™ (8) and PCA3 (9). These biomarkers can improve the specificity of PCa by combining with mpMRI, and have a significant improvement compared with traditional TPSA or prostate-specific antigen density (PSAD).

With the in-depth study of iron metabolism, increasing evidence has shown a correlation between iron metabolism and the occurrence and progression of malignant tumors (10). Iron is one of the basic nutrients needed by cancer cells. When tumor cells are in an iron-rich environment, the growth and invasion of cancer cells are significantly faster than those in an iron-deficient environment. However, too much iron can cause another problem: oxidative damage to cancer cells. When cancer cells are exposed to too much iron, iron promotes another phenomenon by activating oxidative damage: iron death, a mechanism that damages the structure of cancer cells. However, cancer cells form protective mechanisms against oxidative damage and iron death, which are different in all types of cancers and have similar mechanisms in PCa. In cancer cells, the activity of antioxidant enzymes is increased, so cancer cells do not immediately undergo the killing caused by fast-acting iron in the iron-rich environment, so a very large amount of iron is needed to cause the death of cancer cells. Cancer cells use iron for important biochemical reactions, such as DNA synthesis, mitochondrial metabolism, angiogenesis and metastatic cell proliferation. In PCa, iron is also very important for the occurrence and development of tumors. Like other tumors, the growth of PCa cells requires sufficient iron, which can activate enzymes that control the transcriptional activity of androgen receptor (AR) in PCa, which is an important initiating factor. Moreover, iron can reactivate the activity of enzymes in cancer cells, thereby increasing energy production and extracellular matrix degradation. Recent studies have confirmed that the content of iron in PCa cells is increased, while in normal cells near PCa cells, iron levels are lower (11). Many kinds of iron metabolism molecules have been shown to promote or inhibit the progression of PCa. For patients with PI-RADS3 prostate disease whose imaging results are unclear, whether the difference in iron metabolism can help to improve the detection rate of PI-RADS3 is a direction that needs attention to guide clinical diagnosis and treatment from a microscopic point of view.

Here, we introduce a less-used MR sequence in urology, since the unclear anatomical division, difficulty in parameter adjustment, small prostate volume and so on. The T2* mapping sequence was initially used to assess iron deposition in the heart and spleen (12). In the context of liver surgery, the T2* mapping sequence can be used to quantitatively determine liver iron deposition and iron overload based on the difference in T2 relaxation time and has better accuracy than liver biopsy (13). MRI signal decay is affected by the iron content of the tissue; the higher the iron content, the faster the signal decay. In turn, the T2* value represents the iron content as represented by the R2* relaxation rate (14). In the field of PCa, whether the T2* mapping sequence can increase the detection rate of PCa from a new perspective by predicting iron metabolism in patients with PI-RADS3 is unknown. In summary, the assessment of PI-RADS3 seems to have become a key challenge, and a large number of patients with PCa that cannot be diagnosed by TPSA or mpMRI based on T2+DWI sequences are included in this category. This limitation greatly affects the detection rate and prognosis of these patients, and a new method needs to be introduced to address this problem. In the field of urology, whether T2* mapping can be used to evaluate prostatic iron deposition to help diagnose prostate malignant tumors and even evaluate prognosis remains unknown. Therefore, the aim of this study was to prospectively evaluate the role of quantitative measurement of intratumoral iron deposition based on T2* mapping sequence as a noninvasive biomarker of iron metabolism in PCa with PI-RADS 3.

Prostate cancer morbidity and mortality are rising in Asia, with current diagnoses mainly relying on PSA, digital rectal exam (DRE) and mpMRI, as as reported above, posing a new challenge to PCa diagnosis. The focus of the diagnosis of PCa is to differentiate it from BPH, which is associated with symptoms that often mask the existence of PCa. With the advancement of MRI technology, mpMRI has become an effective modality for the noninvasive diagnosis of PCa. The existing routine sequence and the general qualitative PI-RADS scoring model are gradually becoming inadequate for meeting current requirements. Whether needle biopsy should be performed for a PI-RADS score of 3 and the positive rate of needle biopsy were not satisfactory. A 2016 multicenter prospective study showed that the detection rates of PCa were 13%, 31%, and 71% for lesions with a PI-RADS score greater than or equal to 3, respectively (16); other studies have made similar arguments (17–19). Interestingly, a study showed that for PI-RADS3 patients, dividing them into low-risk and high-risk groups according to the 0.5 ml threshold of lesion volume may help physicians make clinical decisions, but there is no large-scale central study to confirm this, and studies are mostly limited to the T1-2 clinical stage (20). Therefore, for PCa patients with PI-RADS 3, the lower detection rate of conventional MR sequences affects the diagnosis of early-stage PCa or clinically significant PCa. In the classic T2+DWI sequence, patients with PI-RADS 3 mostly showed heterogeneous low signals on T2 sequences and isointensity or mild hyperintensity on high b-value DWI sequences. In a previous study, the sensitivity of the T2 sequence + DWI sequence was significantly higher than that of the T2 sequence alone (81% vs. 54%, p<0.01), and the specificity of the T2 sequence + DWI sequence and T2 sequence alone was basically the same (21). DWI reveals obvious differences in the ADC values of patients with PCa and BPH, but there is a large overlap. Consequently, the ADC value alone is not recommended for the differential diagnosis of prostate diseases (22, 23). Models incorporating the qualitative ADC value and qualitative PI-RADS score have improved diagnostic efficiency over the PI-RADS score alone (24). At present, the detection rate of the conventional T2 sequence + DWI sequence is affected by the disease characteristics of the population, the quality of MR imaging, the experience of the reader, and the accuracy of prostate biopsy.

Angiogenesis and tumor metastasis are closely related to cellular iron metabolism. It has been proven that reducing intracellular iron metabolism inhibits tumor cell growth in both hormone-dependent and hormone-resistant cells (25). As a key factor in iron metabolism, hepcidin plays a crucial role, as it regulates the ferritin receptor on the cell membrane, preventing iron from leaving the cell. Subsequently, there is an increase in free iron production in tumor cells, which increases tumor cell invasiveness and promotes tumor cell growth. In this study, a higher level of serum hepcidin was found in the PCa group. In addition, the serum hepcidin levels were correlated with the ISUP grade. Elevated ferritin levels have been reported in other tumors (26–28), and in urine, ferritin heavy and light chains were confirmed to be different between the PCa and BPH groups. However, the effects of serum ferritin on PCa stage, progression, and prognosis need further experimental verification. In our study, the serum ferritin level was positively correlated with ISUP grade. Compared with systemic iron metabolism, local total Fe in prostate tissue can better reflect the significance of iron metabolism in PCa due to the presence of many confounding factors. At present, most studies have collected data on the trace iron in blood, and there are few studies on Fe in tissues. However, many experiments have confirmed that the iron content of PCa cells increases, and there is often iron overload (25). In this study, Fe level was positively correlated with ISUP grade and negatively correlated with T2* value; that is, the T2* value could reflect local iron metabolism in the prostate to a certain extent. In conclusion, for the first time, we identified the differences in iron metabolism in patients with PI-RADS 3. Although they had similar imaging findings, there were significant differences in iron metabolism in patients. The findings represent a considerable difference in iron metabolism that can be assessed during the diagnosis of PCa. The results showed that the levels of three indexes of iron metabolism were positively correlated with ISUP, suggesting that under similar imaging conditions, the degree of active iron metabolism in the tumor represents the prognosis of patients with PCa to some extent. It is interesting to note that there is also a significant negative correlation between the T2* value and the levels of three indicators of iron metabolism in patients with PCa, of which Fe concentration is the most significant, which means that the T2* value is similar to the prediction of liver iron deposition in the field of urology.

We assessed iron metabolism in prostate disorders using the T2* mapping sequence in mpMRI. We found that the T2* value was lower in the PCa group than in BPH group (p<0.001). In the PCa group, the T2* value was negatively correlated with ISUP grade, and patients with ISUP>2 tended to have a lower T2* value. Compared to the traditional ADC value, the TPSA and T2* values had better performance in distinguishing PCa and BPH and in distinguishing ISUP ≤ 2 and ISUP>2 (AUC=0.865 and 0.867, respectively). As a traditional PCa diagnostic index, TPSA still has good performance in diagnosing PCa (AUC=0.746), but there was no significant difference within the PCa group (p=0.08). The ADC value is used as a quantitative indicator; however, in identifying PCa, the diagnostic performance was not as good as TPSA or the T2* value (AUC=0.647), but it was able to achieve greater diagnostic performance within the PCa group (AUC=0.729), which is consistent with previous papers showing that the ADC value can be used to predict PCa staging, grading and prognosis (29, 30).

To verify whether the T2* value can represent iron metabolism, we added three iron metabolism-related indicators, hepcidin, ferritin, and Fe, to our study and found that the levels were significantly different between PCa and BPH (p<0.01). Notably, within the PCa group, the three metrics were still significantly different between the ISUP groups (p=0.002, 0.012, 0.001, respectively). In further ROC curve analysis, Ferritin (AUC=0.704), Hepcidin (AUC=0.667) and Fe (AUC=0.748) showed good performance in the diagnosis of prostate cancer. When considering the risk stratification of prostate cancer, the diagnostic efficiency of the Ferritin (AUC=0.743), Hepcidin (AUC=0.7) and Fe (AUC=0.771) is further improved, suggesting that even in patients with prostate cancer, different progression often has different iron metabolism. In the PCa group, the three indexes were all negatively correlated with the T2* value, indicating that the T2* mapping sequence could reflect iron metabolism in PCa to a certain extent and reflect the progression of the disease.

Through this study, we hope to drive the adoption of radiomics and metabonomics in the management of current PI-RADS3 patients. From a radiological standpoint, it might increase the overall diagnostic efficiency; on the other hand, it might allow us to rule out unnecessary biopsies from a clinical perspective, avoiding the risk of possible complications in selected patients.

Inevitably, this article has some limitations. First, the sample size was relatively small, and it is necessary to conduct a multicenter, prospective, large-scale study to confirm the current conclusions. Second, the article lacks prognostic follow-up data, and whether the T2* value can be used as a prognostic indicator remains to be explored. Finally, although the accuracy of sampling was adequate, there are still uncontrollable corresponding errors, and it is necessary to wait for better sampling methods.

In conclusion, the validation of tissue extraction and metabolic analysis based on T2* Mapping sequence could provide a practical basis for non-invasive preoperative evaluation of patients with prostate malignancies using this technology, and could provide the possibility to discover potential iron metabolism-related therapeutic targets in the future.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Medical Ethics Committee of the First Affiliated Hospital of Soochow University (Suzhou, China; 2021; No. 133). The patients/participants provided their written informed consent to participate in this study.

WD analyzed data and wrote the manuscript. YH and XZ developed the project. XW, WZ and GL edited the manuscript. GZL and YL performed MRI examinations. All authors contributed to the article and approved the submitted version.